Public Health & Medicine

You may have noticed that if someone pushes you to do something, it often makes you feel less inclined to do it. This is a phenomenon known as psychological reactance: a reflex reaction to being told what to do, or feeling that your freedom is under threat. It can occur in personal, professional or social settings when you feel that you need to regain a sense of control over your autonomy. Controlling someone else’s sense of freedom can trigger anger, and motivate them to regain it. As a decision-maker, it is important to recognise that if you push people too hard, you may end up prompting them to do the opposite of what you wanted them to do. Understanding psychological reactance, and finding ways to positively impact others’ motivation, is therefore important in both professional and personal settings. Let’s have a look. A fear of losing our personal freedom The concept of psychological reactance was formulated by psychologist Dr. Jack Brehm in 1966. He defined reactance as “the motivation to regain a freedom after it has been lost or threatened.” It causes individuals to rebel against the pressure they are put under.  It is often the thought of someone else exerting control, rather than the request itself, that leads to psychological reactance. As individuals, we want to feel that we have the freedom to do as we please. This means that when a circumstance arises which threatens our sense of freedom, reactance emerges as a form of motivational arousal. For example, being told that you cannot use a mobile phone at school may increase your desire to do so, even if you previously did not have any desire to look at your phone. Being forced to pay fees for something that was previously free may reduce your desire to buy a product for which the cost can easily be justified. You may work diligently and conscientiously to complete tasks at work without complaint. However, when your manager specifically requests a piece of work, you may start to feel your resistance growing. Despite completing similar tasks previously without issue, you may now feel the urge to react against the request simply because it has now been mandated by your manager. The perceived threat to your autonomy makes the work feel unappealing and so you may put it to the bottom of your list, or even argue against doing it at all. This reactance is a direct effort to eradicate the new restrictions imposed upon you. Reactance can occur whenever our emotional freedom is challenged. Research suggests that it can be triggered by external threats, such as being asked to complete a chore, or by internal threats or dialogue. Furthermore, the intensity of reactance experienced may depend on how significant you perceive the threat to be. The greater the threat to your autonomy, the more likely you are to refuse to yield to social or professional influence. Similarly, if more than one freedom is threatened simultaneously, reactance will increase. How to manage psychological reactance Threats to freedom, and the resultant reactance, can occur in all facets of our lives. As a decision-maker, it is likely that your role will involve making requests or attempting to motivate others to work in a certain way. Finding ways to support the autonomy of others to prevent reactance from occurring is therefore vital. 1. Accommodate autonomy. Of course, you will sometimes need to make decisions that others have less input on. However, it’s essential to treat the people you collaborate with as autonomous agents. For example, if a new process will be implemented at work, give your team the opportunity to provide their thoughts and suggestions. This way, it will feel less likely freedom is being taken away, and more like power is being given. Research even suggests that “threatened individuals who feel powerful free themselves from the threatening situation and manage to reorient themselves.” 2. Set healthy constraints to breed creativity. It has been shown that having too few constraints breeds complacency, while excessive constraints can be detrimental to creativity and innovation: a moderate level of guidance “frames the task as a greater challenge and, in turn, motivates experimentation and risk-taking.” By finding a healthy middle ground between complete freedom and micromanaging, you can maximise creativity and encourage your team to investigate non-traditional solutions. 3. Use reactance as a motivator. In some situations, it may be possible to encourage others to achieve more by restricting their freedom in some way. For instance, a researcher may be driven to attend more conferences when told that they can only enrol on three per year. However, this strategy must be used with caution, as excessive or unfair infringement on freedom could result in resentment rather than motivation. As you have seen, psychological reactance occurs as a response to a perceived restriction on our personal freedom. Being told not to do something, or having requests made of us, can cause us to rebel against the situation. However, it is possible to prevent reactance from occurring, and even to use it as a motivator. By accommodating autonomy, using healthy constraints to encourage imaginative thinking, and applying reasonable restrictions as a stimulus for action, reactance can be directed in a way that improves creativity and productivity in the workplace — as long as leaders ensure that team members do not feel controlled, but instead feel empowered to achieve more. The post Psychological reactance: how we react to the threat of losing our freedom appeared first on Ness Labs.

Our perception of progress can impact our overall drive to reach a goal. The goal gradient hypothesis posits that our efforts increase as we get closer to achieving a goal: when the reward is in sight, we feel incentivised to reach the finish line. Designers and decision-makers can effectively use goal gradients as a motivational tool. The concept of a goal gradient The goal gradient hypothesis was first introduced by Clark Leonard Hull in 1932. He tested his theory on rats, noting that the rodents ran faster the closer they got to a food reward. This phenomenon can also be observed in marathon runners of all abilities who, despite exhaustion, find a sudden burst of energy once the finish line is in sight. In 2006, researchers Ran Kivetz, Oleg Urminsky and Yuhuang Zheng followed up on Hull’s work. They investigated the goal gradient hypothesis and its relevance to purchase acceleration and customer retention for businesses. Customers were either given a 12-stamp coffee card which included two stamps to get them started, or an empty 10-stamp card. The study confirmed that those given the 12-stamp card completed it faster than those who were given an empty card, despite both groups needing to collect 10 stamps in total. The research team also noted that the frequency of coffee purchases increased as individuals approached their free coffee reward. Motivation therefore intensifies with proximity to a goal.  The impact of the goal gradient hypothesis Goal gradients do not only impact our motivation. In 2013, it was demonstrated that goal gradients could also impact how helpful or socially minded we might be. Researchers found that people were more likely to donate to charitable campaigns if the fundraiser was already close to reaching its target. Donations made in the late stage were made not only out of kindness or to relieve negative emotions, but because donors found “satisfaction from having personal influence in solving a social problem.” Those who make a charitable donation in the late stage of a campaign may feel that their contribution has a more personal impact on achievement of the fundraising target. The prosocial act of donating becomes an “influential source of satisfaction”. However, research suggests that the impact of a goal gradient can be affected by your power status. Those who perceive themselves to be in a position of low social or professional power are more likely to be motivated by proximity to a goal. For example, if a senior member of the team tells you that you can use examples from a previous job as credits towards your current goal, this can boost your motivation to complete any professional requirements.  Conversely, goal proximity may be of less importance to those who feel more powerful. If you are financially comfortable, two extra stamps on a coffee card may have less impact on your motivation to earn a free coffee than it might for someone who must budget carefully.  How you can motivate others to achieve their goals The great thing about goal gradients is that they can be used as an effective tool to motivate those around you to succeed. Whether you are a manager, designer or decision-maker, certain strategies can help you to encourage your employees, customers, or users to reach a goal. 1. Offer a head start. At the beginning of a project, it can feel like there is a marathon ahead. It can be hard to imagine getting to the finish line, and so giving those around you a head start can increase motivation. For example, you could offer a head start by creating pre-filled templates or example answers so that it appears that some of the work has already been completed, while also providing inspiration for the rest of the task, or by acknowledging previous studies and allowing a student to use them as credits for their current training. 2. Track and acknowledge progress. In the depths of a project, it can be hard for someone to see how close they are to achieving their goal. Track your colleagues progress manually or using a project management tool, and show them just how close they are to reaching the finish line. Hearing your manager tell you that you are almost there can be the motivation that is needed to finalise a project more quickly than if your progress had not been acknowledged. Consumers may also be encouraged to achieve a goal more quickly if they are made aware of their progress. If you want to encourage customers back into your coffee shop, sending an email update of the points they have accrued on their online loyalty card will not only tempt them back, but could also increase the rate at which they then reach the required points to qualify for a free coffee. This is also why progress bars are so common in mobile apps and online forms. 3. Break down milestones. Someone who perceives that a project is a long way off completion may feel demotivated. Breaking down the project into smaller milestones and celebrating micro-wins can make the goals feel more achievable. Rather than feeling overwhelmed by the volume of work left to do, your team will feel encouraged and motivated by the satisfaction that comes from ticking small victories off each day. Customer loyalty can be encouraged by the insertion of small milestones on the way to the main milestone. For example, a customer might be rewarded with a half-price coffee when they reach 5 stamps, and then a free coffee once all 10 stamps have been collected. Closing the gap between the start and finish line, with small milestones in between, can make the goal feel more attainable. As you have seen, the goal gradient hypothesis increases motivation to cross the finish line. By making projects appear easier, quicker, or simpler to complete, we feel incentivised to strive to reach our goals. But don’t keep this secret to yourself — your team can benefit as well for using goal gradients! To help boost the motivation of those around you, you can offer a head start, acknowledge someone’s progress, and create smaller milestones to help maintain focus and enthusiasm. The post Using the goal gradient hypothesis to help people cross the finish line appeared first on Ness Labs.

Did you know that the more you are interested in how the brain works, the more likely you are to believe in neuromyths? Neuromyths are common misconceptions about the brain. Their source can be innocent — people who genuinely believe in those myths — or plain unethical, such as the case of marketers promoting brain fiction so they can sell dubious products to help customers achieve their full potential. Neuromyths are particularly prevalent in education. Researchers from the Department of Educational Neuroscience at Vrije Universiteit Amsterdam explain: “Teachers who read popular science magazines achieved higher scores on general knowledge questions. More general knowledge also predicted an increased belief in neuromyths. These findings suggest that teachers who are enthusiastic about the possible application of neuroscience findings in the classroom find it difficult to distinguish pseudoscience from scientific facts.” As we will see, while the sources of neuromyths can sometimes be innocent, their effects can be harmful, especially in a learning environment. But the good news is: anyone can become a brain myth buster and contribute to dispelling neuromyths, whether in education, at work, or in their daily lives. Brain fact versus brain fiction According to a systematic review of 24 scientific articles investigating the prevalence of neuromyths, some of the most common ones among teachers, educators, and trainers include the beliefs that… People learn better when they receive information in their preferred learning style. The first three years of a child’s life determine whether or not they will grow into a successful person (also known as the 3-year myth). Differences in hemispheric dominance can help explain individual differences among learners, for instance “right-brained” people are thought to be better at artistic expression and creativity, and left-brained people to be more comfortable with logical thoughts and calculations. We only use 10% of our brain capacity. Children are less focused after consuming sugary drinks or snacks. Listening to classical music helps make us smarter (also known as the Mozart Effect) And the list goes on. In a fascinating study about brain myths, researchers asked more than 3,800 people whether they believed in specific statements about the brain. Some of the participants were educators, others were scientists and doctors, and yet others were just members of the general public. The results of the study were striking. Almost 80% of scientists and doctors believed in one of the brain myths, 43% of them believed in the Mozart Effect — which, as we’ve seen, has no basis in scientific evidence — and almost 50% of educators believed that people are either right-brained or left-brained. As you can see, neuromyths are very common. The problem is that they are also very dangerous. The dangers of brain fiction There’s a popular saying that goes: “It’s not so much the things we don’t know that get us in trouble, it’s the things we think we know that aren’t so.” There are lots of things we think we know about the brain that aren’t so. But what kind of trouble are we talking about? Believing in neuromyths may seem harmless, but it really isn’t. Neuromyths can lead to: Wasted potential. If a student is struggling with mathematics and their teacher believes that people are either right-brained or left-brained, that teacher may just stop supporting the student with mathematics — focusing instead on areas where the student is more comfortable. Many talented people did not find their craft easy at first, and believing that believing that some brains are just not “designed” for certain skills may prevent some students from exploring less obvious learning paths. Misspending. Brain fiction also makes us waste money — whether it’s corporate money, government money, or personal money. Companies are paying for expensive training based on neuromyths, and governments are heavily investing in pseudoscientific educational programmes (a famous example is Brain Gym in the United States). Discrimination. Finally, brain fiction can be leveraged to support discriminatory practices in education. For example, Leonard Sax, who used to run the National Association for Single Sex Public Education in the U.S., said that boys and girls should be taught differently and separately because of differences in their brains (“girls are using the cerebral cortex while boys are using the hippocampus”). Whether it’s to avoid wasted potential, misspending, or discrimination, dispelling those dangerous misconceptions about the brain is important for the future of education. And anyone — that means you too — can join the fight. Becoming a brain myth buster To become a brain myth buster, we need to ask ourselves: why do we believe in brain fiction? Several factors contribute to the emergence and proliferation of neuromyths. First, these are remarkably appealing ideas. To believe in the 10% myth is to believe that we may have some untapped potential which we could unlock should we use the right techniques or tools. To believe we are right-brained or left-brained offers a practical excuse to focus on our strengths rather than aim for a well-rounded education. Researchers have also blamed the inaccessibility of empirical research, which is often hidden behind paywalls, fostering an increased reliance on media reports rather than the original research, as well as the lack of professionals trained to bridge the disciplinary gap between education and neuroscience. Becoming a brain myth buster requires critical thinking, curiosity, and access to evidence-based sources of information about the brain. Whenever you hear a new claim about the brain, look it up using one of the following resources: BrainFacts.org — And in particular their neuromyths database which answers questions such as “Can you learn in your sleep?”, “Does using your non-dominant hand make you smarter?” and more. The website is run by a group of global nonprofit organizations (the Kavli Foundation, the Gatsby Charitable Foundation, and the Society for Neuroscience)  as a public information initiative, not by marketers trying to sell you a brain-training app. OECD database — The Centre for Educational Research and Innovation at the OECD has published a collection of neuromyths which they thoroughly debunk. These include neuromyths around multilingualism, learning styles, enriched environments, and more. Books about neuromyths — There are two books that are particularly interesting if you want to learn about some of the most common myths. The first one is Great Myths of the Brain, which takes more of a neuroscientific angle, and the second one is 50 Great Myths of Popular Psychology, which is an easier read and includes many myths rooted in psychology. Blogs of brain myth busters — There are many blogs that are excellent resources, such as Neurocritic, Neurobollocks, and Neurobonkers. Dr Christian Jarrett, the author of the Great Myths of the Brain book has a blog about brain myths. While not updated anymore, Neuroskeptic offers an amazing collection of articles debunking brain fiction and getting the brain facts straight. Applied neuroscience resources — You could also learn more about applied neuroscience by taking a course from a reputable university, or joining one of the many professional organizations offering training that can help you become a brain myth buster. For example, the Centre for Educational Neuroscience regularly hosts events about neuromyths. After you are done checking a claim about the brain, you can even make a note of it by adding it to your note-taking app and tagging it as “brain fact” or “brain fiction” — after a while you will have your own personal database of information about the brain, which you can use to quickly look up a claim while having conversations with colleagues, friends, or family. Finally, of course, there is Ness Labs! To celebrate Brain Awareness Week, we hosted an interactive session about brain fiction where we dispelled some of the most common myths. You can watch the recording here and download an editable template to host your own brain myth busting game. Have fun becoming a brain myth buster! The post How to become a brain myth buster appeared first on Ness Labs.

Like the rest of New Things Under the Sun, this article will be updated as the state of the academic literature evolves; you can read the latest version here. Audio versions of this and other posts: Substack, Apple, Spotify, Google, Amazon, Stitcher. Evolution via natural selection is a really good explanation for how we gradually got successively more complex biological organisms. Perhaps unsurprisingly, there have long been efforts to apply the same general mechanism to the development of ever more complex technologies. One domain where this has been studied a bit is in computer programming. Let’s take a look at that literature to see how well the framework of biological evolution maps to (one form of) technological progress. Share Simulating Technological Evolution We’ll start with Arthur and Polak (2006), who look at how ever more sophisticated logic circuits can, in principle, evolve via a blind process process of mutation, selection, and recombination. The paper reports the results of a large number of digital simulations that do precisely that. These simulations have three main components. First if you’re going to simulate evolution, you need your organism, or in this case, your technology. Arthur and Polak start with a very elementary logic gate, in most simulations a Not-And (NAND) gate. This is a circuit with two binary inputs and one binary output. If every input is 1, then it spits out 0; otherwise it spits out 1. From this seed, much more sophisticated circuits will digitally evolve. From Arthur and Polak (2006) The second thing you need in order to simulate evolution is a way to modify the organism or technology. We might think the natural way to do this is to allow for slight mutations in these circuits, which is how we often think of biological evolution (single base-pairs being switched from one to another). But Arthur and Polak believe recombination is the essence of technological change, rather than mutation. So their model of digital evolution is much more explicitly combinatorial. In every period, sets of 2-12 technologies are picked and randomly wired together in sequence, though any individual circuit is also allowed to mutate a bit on its own. Third, to model evolution you need a way to evaluate the fitness of your organisms, or circuits in this case. If we’re trying to understand technological evolution, then fitness should be related to whether or not humans find technologies to be useful. Arthur and Polak come up with a list of desired functions it is reasonable for people to want circuits to fulfill. These range from very simple to very complex. For example, one simple function is just a NOT gate: it just returns the opposite of its input (1 for 0, 0 for 1). A more complex function is a 15-bit adder: if you put in two 15-bit numbers, it outputs their sum. Arthur and Polak next come up with a way to score circuits based on how close they get to giving the right answer: every time the circuit gives the right answer for a set of inputs, it scores better, every time it gives the wrong answer, it scores worse. And if two circuits perform equally well, the one that does it with fewer components scores better. In every period, the highest scoring circuits and their components gets retained. Next period, the simulation draws components from this basket of retained circuits and wires them together to see if any of the resulting combinations do a better job fulfilling the desired tasks. Finally, Arthur and Polak let this system run for 250,000 periods, 20 different times, and watch what happens. We learn a few things from the results of this exercise. First, the experiment is an existence proof that you don’t need inventors with reasoning minds to get sophisticated technologies; this blind recombinant evolution can also do the job. In 250,000 period these simulations don’t discover everything Arthur and Polak define as desirable, but it does go well beyond the simplest circuits. For example, the simulation successfully discovered circuits that can add 4-bit numbers and and circuits that can indicate if one (and only one) of 8 inputs is 1.  Second, in the experiment, technological advance tends to be lumpy. Desirable circuits tend to be discovered in clusters, after key component pieces are discovered which unlock lots of new functionality. But in between these sprints can be long periods of technological stagnation, even as under the surface the ferment of experimentation and “R&D” is going on invisible to us. Third, their simulations give a nuanced picture about the importance of path dependency. This is the idea that where our technologies start has a big impact on where they finish. If we start along one technological trajectory, we’re more likely to continue on it, and end up with a completely different basket of technologies, than if we started elsewhere. In Arthur and Polak’s experiments, one way they can investigate this is to see how different simulations evolve, when different circuits are discovered first. For example, most of the time, a “not” circuit is found before an “imply” circuit. But not always. In the rarer cases when “imply” circuits are found first, many subsequent technologies build on the imply circuit than the “not” circuit. Over time, however, the program still sniffs out the best overall approaches for different functions, and this begins to chip away at the initially atypical dominance of “imply” components. The importance of where you start matters for a time, but then begins to fade. Fourth, technological innovation, like biological innovation, is red in tooth and claw. Better technologies constantly supplant obsolete ones and sometimes this leads to waves of extinction. For example, suppose some technology x is comprised of 12 other circuits, and each of these component circuits is further comprised of 2-12 subcomponents, which are in turn comprised of sub-subcomponents and so on. If technology x is replaced by a superior technology y, then technology x naturally goes “extinct.” And if the components and subcomponents, and sub-subcomponents that comprised x are not part of any other technology that is the highest scoring on some function (and therefore retained), than they too can go extinct, leading to the collapse of an entire ecosystem of supportive circuits. Lastly, Arthur and Polak’s digital experiment illustrates the importance of intermediate goals in the evolution of technological complexity. In their simulations, if Arthur and Polak remove key desirable circuits of intermediate complexity, the simulations get trapped and unable to advance to more complex designs. Evolution needs stepping stones to get from simple to complex. Evolution in MatLab Contests This is an intriguing experiment, but it’s doesn’t demonstrate that these mechanisms are important in the actual development of technology. For that, I am a big fan of two papers from 2018 and 2020 by Elena Miu, Ned Gully, Kevin Laland, and Luke Rendell. These papers study 19 online programming competitions operated by MathWorks over 1998-2012. This is still an artificial setting, but we now have real people solving real programming problems, and as we’ll see, these contests have some important elements that make them worth studying. In these contests, nearly 2000 participants (average of 136 per contest) competed over the course of a week to write programs in MATLAB that could find the best solution to a problem in which it was impossible to find an exact solution in the time given. For example, in a 2007 contest participants wrote code to play a kind of peg-jumping game, where there is a grid of pegs (all worth different points) and an empty space, and you can remove a peg by jumping over one peg and into an empty space. A program’s score was based on three factors: the number of points it got in the game; how fast it ran, and how complex the code is (with more complex code penalized). Participants could submit their programs at any time and receive a score. They could then modify their code in response to the score they received, and this iterative improvement was an important part of the contest. But there is a catch: programs and their scores were publicly viewable by all participants. So submitting a program and getting feedback on its performance also discloses your program to all the other contest participants, who are free to borrow/steal your ideas. This is a great setting to study technological evolution, for a few reasons. As in the real world, there is robust competition, and inventions can be reverse-engineered and copied. Unlike Arthur and Polak, we have reasoning minds designing and improving programs, rather than blind processes of recombination and selection. But perhaps most importantly, for the purposes of studying technological evolution, we can see the complete “genotype” of computer programs by reading their code. And with standard text-analysis packages, Miu and coauthors can see exactly which lines and blocks of code are copied and how similar programs are to each other. Lastly, because programs are explicitly scored (and players care about these scores; they are actively seeking the highest score), Miu and coauthors also know exactly how “good” a program is. The figure below tracks how scores improve for a sample of 4 contests. In the figure, each dot is a program. The horizontal axis is time (each contest runs 7 days) and the vertical is the score (lower is better). Clearly the best programs improve over time, in fits and starts. From Miu et al. (2018) When Miu and coauthors peer into the underlying dynamics, in their 2018 paper they see that the most common type of program that is submitted is a program that is very similar to the current leader, but with minor tweaks. In their 2020 follow-up, they also document that when two programs have the same score, people are more likely to copy the one submitted by the participant who tends to score higher in...

This is an audio read-through of the initial version of Progress in Programming as Evolution. To read the initial newsletter text version of this piece, click here. Like the rest of New Things Under the Sun, this underlying article upon which this audio recording is based will be updated as the state of the academic literature evolves; you can read the latest version here.

Welcome to this edition of our Tools for Thought series, where we interview teams on a mission to help us make the most of our minds. Scrintal is an app that combines mind mapping with the power of networked note-taking. It helps you see your thoughts at a glance so you can convert cluttered ideas into connected information. In this interview, we talked about the power of bi-directional linking, the challenges when setting up a Zettelkasten, the anxiety caused by folders systems, the relationship between design and functionality, how to best connect notes together, and much more. Enjoy the read! Hi Ece, Furkan, and Arda, thank you so much for agreeing to this interview. Knowledge builders often struggle visualizing how their thoughts connect to each other. Can you tell us more about your mission? Ece: Thanks so much for having us here! The biggest challenge for any thinker is finding connections between ideas. We jot down ideas all day long, but how do they link with one another? What are the opportunities that we miss as we can’t put the puzzle pieces together?  We started with these challenges, thinking that the hardest part in each knowledge management system is to organize and connect things. We designed Scrintal in a way that it combines mind mapping with the power of networked note-taking. Scrintal is powered by the bi-directional links and provides a fully functioning canvas to effortlessly connect ideas. Our mission is to support clear thinking, creative writing, and organized knowledge. I think many research-minded people will love the idea. What inspired you to build Scrintal? Ece: I was doing my PhD on climate change at Stockholm University when I developed an interest in tools for thought. I was reading tremendously and conducting interviews for my research. This was the first time I set up my personal knowledge management system via a Zettelkasten. I was diving deep and then kept switching tools, all in the search for a space where I could both link my ideas and spread them to have a better overview.  After some point, the same thing happened again and again. My notes were not surfacable anymore. I was using bi-drectional links to come across my older notes serendipitously. However, 90% of my time was going into creating these bi-directional links when I only used 10% to go back to these links and have encounters. I wasn’t getting anything out of the graph views, either.   The “aha” moment came when I started talking to my colleagues at the university. Some were even saying they consider spreading all their ideas on papers on the floor to find a structure and a flow. The mind maps were not enough, as creating mind maps breaks the flow, you focus on the visuality more than you want, and the text editors are not powerful enough. Whereas in networked note taking, we miss an essential part of the creative flow, working with ideas freely.  With my co-founders Arda and Furkan, we conducted more than a hundred interviews before we started building Scrintal. In the end we decided to combine the easy organization and findability of the networked tools, while keeping the flexibility of visual tools. And how does Scrintal work exactly? Ece: We solve two challenges; keep the creative float of visual tools, but solve the challenge of searchability and easy organization generally found in visual tools; and keep the networked thoughts, but make them more surfacable, memorable and recognizable.  How we achieve this is that you have a daily visual desk that you can create mid-size cards with one-click. These cards are very flexible, you can make them full screen size to focus on what you are writing or even fold them if you want to make them look like post-its or a mind map.  There is a fully-fetched text editor in these cards where you can add video and images and extract them from the cards if you’d like to open them separately and take notes at the same time. To keep the serendipity, and the Zettelkasten philosophy of “you only have one brain”, you have one daily desk in Scrintal. You bring what you are working on to your desk through the archive where all your notes live. You link cards through bi-directional links, rather than creating arrows in mindmaps. This helps you to be in the flow while writing and sets the base of the visual map without you giving extra effort.  You can then visually organize these cards in the way that you like, if you don’t want to organize them yourself, the built-in graph algorithm does the job for you. When you are happy with the visual organization you create, you can save it on a board and share it with others so they can interact with what you created.  Many note-taking tools treat notes as isolated units. Can you tell us more about how Scrintal makes it easier to connect ideas together? Ece: Knowledge work starts from capturing ideas, then you connect them and then develop them. The biggest problem usually lies in forgetting our older notes and not knowing what to connect with what.  We worked on making it much easier and fun to see the connections between your ideas. Firstly you can link notes bi-directionally to indicate a direct connection. We do not have a folder structure, as folders are rigid and break the possibility to fluidly connect ideas. You have a “where do I put this?” anxiety in a folder system. The second layer of connecting ideas is done through the tags. Tags are for grouping relevant notes. Using tags based on the context you’d like to find them again is the best way to go. In Scrintal then comes the connecting notes in visual ways. You can lay out your notes on your visual desk and change their colors which instantly gives a visual segmentation.   In the end, you can have a final piece of work, showing the whole plot of your next novel, strategic plan of your company, research on a specific topic, or all your meeting notes in one screen. This gives you the power of seeing all your connected thoughts at one glance.  This actually seems to be perfect to apply the Zettelkasten method! Ece: Yes! As you can see the cards on your board, it pushes you to write one idea or topic per card. Scrintal is actually the closest version to a digital Zettelkasten. You can think of the cards in Scrintal as index cards and the nice thing is you can just lay them on your digital desk as if you are overlooking your index cards. Seeing cards visually next to one another makes creating connections much easier. Also not having a folder structure makes Scrintal an ideal tool to implement Zettelkasten. Whenever an idea pops into your mind, you can create a card, tag it if you like, rather than having to think: where shall I put this new note? This bottom-up approach is what makes Scrintal suitable for a Zettelkasten.  Knowledge builders sometimes feel reluctant to invest too much into a specific tool for fear of getting trapped in a silo. How does Scrintal integrate within the existing ecosystem? Ece: I totally understand this concern! In Scrintal we focus on shareability of your knowledge. In terms of being able to share anything you create in Scrintal, you can publicly share your whole desk, or single notes within them. This way anyone, without creating a Scrintal account can interact with your board, go deeper into each note and see the total overview at the same time. We will release the Markdown import and export options soon, which will make our current users very happy I believe. That sounds great. Can you share a bit more about your design philosophy? Furkan: We prioritize a simple and functioning design. Building a tool that is visually appealing is extremely important given the number of hours we spend looking at our screens. Our design principles are… Nothing unnecessary. We remove all the fluff. When it comes to design, less is more. We do not follow the trend of adding more features just because it makes us look cooler. Just because we can do something cool, doesn’t mean we have to do it. Simple is beautiful. We have infinite ways of expressing ourselves — but only a few ways of actually communicating effectively with people. We embrace simplicity in our design and communication because we are here to build trust with our users and this starts with communicating clearly without any white noise. Functionality first. Functionality precedes design because functionality solves the problem for us and our users — design merely facilitates functionality. Almost always there are multiple ways to express the same functionality in design; what matters is that the functionality works well, rather than how it looks on the outside (as long as it looks good). As an inherent philosophy, anything we add in Scrintal should be solving a problem, should be simple, should not be creating new problems while being a solution. And how do you incorporate your user’s perspective in the design process? Arda: Understanding the user’s perspective has been an important part of the product development process since day one. We believe user interviews are a great way to understand what people think and feel about our product, as well as their experience with similar products. Since we have released Scrintal’s first version, we have onboarded several tranches of groups who have been using Scrintal for different use cases. Once they have enough time to try the tool in their daily lives, we meet again to listen to their feedback. This user-centric approach gave us insights into what problems people have, what they appreciated and what crucial features were missing. Once we get those insights, we cluster them into groups and conduct a brainstorming workshop as a tem where each member shares their thoughts. We then decide what to prioritize next and start building those features. We’re in the process of building a community in which our early users are able to send us immediate feedback and request new features. Community building has been an integral component ...

Cognitive distortions are thought patterns that can affect our perception of reality. One such distortion is emotional reasoning. This is a thought pattern in which our emotional reactions, or our feelings, lead us to believe that something is true even when the empirical evidence tells us otherwise.  Emotional reasoning is very common in the workplace. If you have ever found yourself thinking, “I know this project will fail because I feel scared,” or “I know my manager must dislike me because I feel unappreciated,” or “I know my colleague has been hiding something because I feel suspicious,” then you have already experienced emotional reasoning. Taking our emotions as information Recent research described emotional reasoning as a mechanism that “can lead people to take their emotions as information about the external world, even when the emotion is not generated by the situation to be evaluated.” This leads to inaccurate emotional truths which directly contradict any objective, perceptual truths. Emotional reasoning was first coined by the American psychiatrist Aaron Beck in the 1970s. In a career that spanned more than 65 years, Beck studied cognitive theory and therapy, and is considered the founder of cognitive behavioural therapy (CBT). Beck’s extensive clinical career, and related research, illuminated the way in which our emotions sway the way we feel. For example, Beck found that his depressed patients were plagued by self-criticism and regret, whereas those with anxiety experienced fear-filled thoughts. Beck referred to thought responses to an emotion as “automatic thinking”. His research suggested that the content of automatic thoughts was often linked to the diagnosis a patient had. However, it is likely that automatic thoughts will be relevant to your state of mind, even if you do not specifically struggle with your mental health. For example, if you have been feeling anxious about a project at work, your automatic thoughts may be based on that anxiety. When presenting your findings to colleagues you may assume that they are disappointed with your progress. As a result of emotional reasoning, this automatic thought will occur in the absence of any objective proof to suggest that your colleagues are perceiving your work negatively. Furthermore, studies have shown that isolated automatic thoughts can result in negative thought cycles. Emotional reasoning such as “I am sure I am doing a bad job at work because I feel anxious about it every day,” aggravates your fear or apprehension. Increasing anxiety can begin to negatively impact your performance. You may struggle to focus, make mistakes, or see a decline in your output. This becomes a self-fulfilling prophecy, and a cycle of negative thoughts is set in motion. How to avoid emotional reasoning If your beliefs have become founded on emotional reasoning rather than logical facts, it is vital to search for objectivity to manage this cognitive distortion. Taking control of automatic thoughts will help to prevent emotional reasoning from derailing your efforts in your professional and personal life. The process involves challenging your emotional beliefs so that automatic thoughts are thoroughly interrogated before being accepted. There are several ways you can investigate the source of any discouraging thoughts to avoid unnecessary negativity or anxiety. 1. Practice validity testing. Validity testing is key to checking whether you are experiencing emotional reasoning. If you feel sure that your work has not been of the expected standard, you must search for objective evidence to prove that this belief is true. Ask yourself if anyone has questioned your work, and reflect on any recent appraisals or informal feedback you have received. In the absence of negative feedback or criticism, you may find that your thoughts cannot be upheld and are therefore unlikely to reflect the truth. 2. Write in a journal. Journaling is a great way to pay attention to your thought patterns. Specifically, you should record the difficult situations you face, and which emotions or thoughts a dilemma provokes. If a colleague requests a meeting with you without giving you any context, use your journal to document the automatic thoughts that appear. You might automatically assume that they want to talk because your performance has been below average, or that you are facing redundancy, despite there being no evidence for this.  Recording your feelings in this way will allow you to reflect on your natural thought patterns so that you can start to identify when emotional reasoning is affecting you. This provides an opportunity to reject negative thoughts before they take hold. 3. Discuss your emotions. If you feel anxious about work, you may struggle to accurately assess your performance. Talking to a trusted colleague or friend about your concerns could give you a much-needed objective view. It can be illuminating to learn that others speak highly of you or your work, and this can help to dispel cognitive distortions. Emotional reasoning is a form of distorted cognition that can lead to an unwarranted negative opinion of your ability or character. By generating negative thoughts, a downward spiral of anxiety can cause a self-fulfilling prophecy of worsening performance. Learning to probe emotional beliefs to check their validity can help to avoid unnecessary negative thoughts and self-talk. Discussing your beliefs with someone you trust, using a journal to understand your thought patterns, and practising validity testing can all help you to avoid the pitfalls of using your emotions as a form of proof. The post The danger of emotional reasoning and using our emotions as proof appeared first on Ness Labs.

Mae Jemison is the first African American woman to orbit the earth. She knew that she wanted to be a scientist since kindergarten. Not only did she grow up reading books about space, but she also loved science fiction books where black women were the heroes of the story. At 16, Jemison graduated from high school and studied chemical engineering and African studies at Stanford University. Eventually, she became a doctor and traveled the world to care for patients. However, Jemison always held on to her love for space and space travel. So when NASA opened a new search for astronauts in 1987, she seized the opportunity and was accepted into the program.  In 1992, Jemison stepped foot on the space shuttle Endeavor as the science mission specialist, a new role for NASA that focused on conducting experiments in space. In seven days on the Endeavor, Jemison and her team conducted 44 experiments on motion sickness and weightlessness. She stayed with NASA for six years before turning her sights on business, education, and writing. Let’s learn from the way she approached challenges and navigated the world. This article is part of the Brilliant Thinkers series, which explores the thought processes, working habits, and decision-making principles applied by intellectuals who profoundly impacted the world with their discoveries and the way they challenged the status quo. Mae Jemison’s thinking strategies It takes all types of unique thinking strategies to become the first Black female astronaut in American history. Here are three of those strategies and how we can apply them in our lives and work. 1. Learning from everywhere. Aside from her studies, Jemison learned by doing many activities growing up. She was a part of student government, acted in school plays, and studied dance. She choreographed a performing arts piece called Out of the Shadows in college, which brought attention to the African American experience. She knew the value of learning from everywhere and anywhere, and her experiences in the arts and government taught her how to be graceful and the value of hard work.  2. Becoming a multi-hyphenate. Doctor, astronaut, entrepreneur, writer, teacher, and artist — all of these words describe Jemison and her phenomenal career. Before joining NASA, Dr. Jemison cared for patients in Cuba and a Taiwanese refugee camp. She joined the Peace Corps in 1983 and served as a medical officer in Liberia and Sierra Leone.  After her career as an astronaut, Jemison taught at Dartmouth College and ran the newly founded Jemison Institute for Advancing Tech in Developing Countries. She also founded the Dorothy Jemison Foundation for Excellence, which supports several programs, including a space camp and the 100 Year Starship program. Jemison even found time to write a book about her life, published in 2001. She was a true multi-hyphenate. 3. Opening new doors. Jemison was bothered that there were no women astronauts when she was growing up. She also experienced racial discrimination in her schooling and her career. Therefore, Jemison created opportunities for youth of color to become a part of the scientific community. For instance, the Earth We Share- Space Race program bolsters science education for teens in Los Angeles, CA. Her memoir, Find Where the Wind Goes, is also aimed at teens to inspire their journeys into science. How to think like Mae Jemison Jemison’s experiences as a performer and choreographer helped her develop hard and soft skills that she used throughout her career. Research shows that participating in the arts can help us with emotional regulation and reduce feelings of isolation. If arts are not a part of your life, try picking up a new craft, pulling out your old guitar, or playing around with your kids’ paints. As Jemison has demonstrated, engaging in creative expression can teach us valuable lessons for our careers and personal growth. Another way to think like Mae Jemison is to “multi-hyphenate” yourself. Odds are, you are already a multi-hyphenate. Consider the different tasks that you do daily in your work life. Identify your descriptors and share those “hyphens” with your personal and professional network. Your unique skill set could open doors to new professional experiences. Next, ask yourself: any other skills that you would like to explore? What are some adjacent areas that may not be obvious but will make your skill set more useful and valuable? Finally, use your skills and your network to be an agent of change. Jemison used her influence to remove barriers and create opportunities for disadvantaged youth interested in sciences. What challenges have you faced in your education, employment, or personal life that you would be willing to share with others? How can you use those experiences to lower barriers for others who may face similar challenges? Brainstorm ways you can contribute to changing the status quo. Mae Jemison’s unique and influential career as a doctor, astronaut, entrepreneur, and artist serves as inspiration for anyone who wants to do it all. To follow her lead, try your hand at something new, embrace all the things that make you who you are, and figure out ways to support future generations. The post Mae Jemison: the power of developing multifaceted skills appeared first on Ness Labs.

Rosalind Franklin was a groundbreaking scientist whose story is tied to the discovery of the double-helix structure of DNA. Franklin and her Ph.D. student used x-ray technology to photograph DNA that showed the molecule’s structure. However, when two other well-known scientists published a paper about the double-helix findings, they never gave Franklin credit for her contributions. Those scientists – Crick and Watson – went on to win a Nobel Prize. Franklin was never acknowledged.  While this story is well-known, Rosalind Franklin did much more than DNA research. Many scientists specialize in one field, but Franklin’s research included biology, chemistry, and physics. She studied coal, DNA, and viruses that caused harm to humans and plants. Her thorough work and the practical applications of her findings earned her an international reputation amongst her fellow scientists.  Unfortunately, Franklin died at the age of 37 of ovarian cancer. Her brief life made a lasting impact on the sciences and people’s everyday lives. Franklin used many thinking strategies to earn her reputation across fields, which we can learn to emulate. This article is part of the Brilliant Thinkers series, which explores the thought processes, working habits, and decision-making principles applied by intellectuals who profoundly impacted the world with their discoveries and the way they challenged the status quo. Rosalind Franklin’s thinking strategies Rosalind Franklin has accomplished so much during her short life, there are many strategies we can extract from her accomplishments. Let’s explore three of those lessons and how we can apply them to our everyday lives and work. 1. Aim for practical innovation. Franklin always wanted her work to have practical applications, not just sit in a lab or a journal that few people would read. During World War II, Franklin worked at the British Coal Utilization Research Association and studied the porosity of coal. At first glance, that topic may seem a little dry. But her research allowed British troops to estimate fuel performance in their vehicles. Her findings also helped improve the soldiers’ gas masks. The gas masks had activated charcoal filters to protect the soldiers, but Franklin’s work increased their effectiveness. Another example comes from her virus research. Franklin became an expert in creating clear x-ray diffraction images of different viruses. These images paved the way for scientists to break the genetic code and use DNA sequencing to understand viruses. These methods are still used today to investigate viruses such as COVID-19. 2. Be a global connector. Not only did Franklin want to find practical applications for her work, but she also understood the importance of sharing that work with others. For her, that meant working with partners from across the globe and sharing her work at international scientific conferences, which she tried to attend as many as possible.  3. Explore your passions. Franklin never limited herself by studying only biology or only chemistry. Her work across disciplines allowed her to impact many different fields. She also highly valued having hobbies, and would spend her free time playing sports, sewing, and traveling. How to think like Rosalind Franklin One of the keys to emulating Rosalind Franklin is to broaden your impact. Franklin never limited herself to a single subject and made incredible impacts on several fields, including energy and medicine. How can you use your talents, expertise, and experience to impact multiple domains? For example, say you are a marketing expert. Perhaps you can volunteer to write marketing materials for a charity organization close to your heart or offer to help them with data analysis. If you are an online course creator, maybe you can brainstorm ways to convert your educational content into a book. The possibilities are endless. Another important strategy you can borrow from Franklin is to proactively get connected. We no longer need to travel worldwide like Franklin to have a global impact. Social media platforms can help you find potential collaborators and international audiences for your work. There are also many groups whose goals are to foster connections between professionals with similar interests across the globe. Don’t be shy, join one of them and become an active participant. Finally, stay curious! Not everything has to be about work. Franklin followed her passions in what she studied and how she spent her leisure time. What are some things you are interested in learning about or experiencing that are unrelated to your work life? Setting aside time for reading, listening to podcasts, even checking out YouTube videos are a great way to fulfill your curiosity and enrich your life with new knowledge. Rosalind Franklin made significant contributions to science that paved the way for the innovations of today. Her unbounded curiosity had a global impact while still making time to enjoy the activities that she loved. The lessons we learn from her life should encourage us to pursue our interests, seek connections beyond our borders, and consider the ways we can broaden our impact. The post Rosalind Franklin: the power of unbounded curiosity appeared first on Ness Labs.

Vera Rubin was a powerhouse in astrophysics, though she rarely gets the credit she deserves. Rubin is responsible for discovering dark matter, which makes up 84% of the material that exists in the universe. Born in 1928, a young Vera became enthralled with space while staring at the stars outside her bedroom window. After receiving a full ride to Vassar College, Vera went on to study how galaxies move in space and found some unexpected results. Rubin expected galaxies to move in the same way planets revolve around the sun. Objects closer to the sun move faster than those that are further away. However, using her keen observational skills, she discovered that all objects in a galaxy move at the same speed, no matter how far they are from the center. Dark matter is responsible for this phenomenon, and Rubin’s discovery set the course for modern astronomy studies. Her approach to problem-solving and innovation holds many lessons for us today. This article is part of the Brilliant Thinkers series, which explores the thought processes, working habits, and decision-making principles applied by intellectuals who profoundly impacted the world with their discoveries and the way they challenged the status quo. Vera Rubin’s thinking strategies Vera Rubin had a unique way to navigate the world, ask questions, and make connections. Three strategies in particular have helped make immense contributions to science. 1. Practicing visual thinking. Rubin’s interest in visual thinking started when she was young. She would stare out of her bedroom window and watch the stars as they moved. She drew maps of meteor showers showing the direction of the streaks that fell from the sky. As her observational skills improved, Rubin continued to rely on drawings to understand what was happening in the universe. While collecting data about galaxies at the Carnegie Institute, Rubin used visual thinking to explain the perplexing results. Using the data printed out on punch cards, she made sketches to help her figure out how to explain the results. Even when she looked at different galaxies, the same pictures would emerge repeatedly. These pictures validated her observations and gave her results even more credibility. 2. Trusting the evidence. Rubin had difficulty convincing her colleagues that her findings were valid. As such, she produced the same evidence for over a decade to quiet the (mostly male) critics. Her years of careful, precise observations and documentation ensured her work was irrefutable. 3. Seeing the bigger picture. Not only did Rubin shape modern astronomy, but she was also a fierce advocate for women in science. She pushed for more women to participate in scientific committees and conferences. She was also a strong advocate for equal pay. Rubin once wrote a letter to Nature, a highly influential scientific publication, to complain about a job listing that explicitly offered women applicants a lower salary than men. She understood that more brilliant minds in astronomy would mean more scientific discoveries. How to think like Vera Rubin Visual thinking may sound intimidating, but you can use various strategies to represent complicated problems or projects visually. Draw a timeline for your projects, use a mind map, or practice your infographic skills to shed light on solutions to everyday issues. No need for museum-quality artwork here! Focus less on drawing skills and more on creating the most useful visuals for you. To think like Vera Rubin is to follow the evidence. Whatever questions you are trying to answer, look for factual information, and keep on analyzing the data from different perspectives, connecting it across various areas of knowledge. Even if your colleagues doubt your results, you will know your work is based on evidence. Finally, another theme that emerges from Vera Rubin’s life is the importance of not only focusing on your own success, but instead stepping up for others. Rubin took her negative experiences as a woman in science and found ways to create change. Ask yourself: what challenges have you faced in your career? How can you turn your experiences into opportunities for newcomers in your field? Rubin’s observational skills, dedication, and persistence made her one of the most influential figures in science. By practicing visual thinking, following the evidence, seeing the big picture, we can also make profound impacts in our fields and on our personal and professional growth. Which strategy will you use today? The post Vera Rubin: The power of evidence-based visual thinking appeared first on Ness Labs.

Born in 1821, Elizabeth Blackwell did not intend to become a physician. In her book Pioneer Work in Opening the Medical Profession to Women, she shared that “the very thought of dwelling on the physical structure of the body and its various ailments filled me with disgust.” But the course of her life changed when a close family friend became terminally ill. Her friend shared that she believed she would not have suffered as much if her doctor had been a woman instead of a man. This experience inspired Blackwell to become a physician, though most medical schools were not open to women at the time. Blackwell overcame all the challenges she faced to become the first woman to qualify as a doctor in the United States, be included in the British General Medical Council’s medical register, and publish in a medical journal in the US. Blackwell also opened her own clinic and wrote numerous books about women in medicine. Let’s explore Blackwell’s thinking strategies and how we can apply them to the way we navigate our work and life. This article is part of the Brilliant Thinkers series, which explores the thought processes, working habits, and decision-making principles applied by intellectuals who profoundly impacted the world with their discoveries and the way they challenged the status quo. Elizabeth Blackwell’s thinking strategies What made Elizabeth Blackwell’s mind remarkable was her ability to get off the beaten path, her efforts to invest in both self-education and traditional education, and her willingness to create learning opportunities for others, thus building a virtuous intellectual circle. Here are three principles she followed throughout her life. 1. Having the courage to be the first. Blackwell’s biggest challenge was getting to medical school in the first place. Every medical school she applied to rejected her because they did not accept female students. The only school that accepted her was Geneva Medical College in New York. However, even this success was mired in sexism; school administrators allowed the male students to vote on her admission, and the majority voted “yes” as a joke. Ultimately, the joke was on them. Blackwell’s commitment and talents ultimately earned the respect of her peers and professors by the time she graduated, becoming the first woman in America to do so. When she had difficulty finding patients and jobs at local hospitals because she was a woman, she opened a clinic with her sister instead. It takes bravery to create your own path to success, but Blackwell did this every single day of her career. 2. Investing in your education. Blackwell understood the importance of investing time and money into her education. To save for medical school, she taught music to children at a school in North Carolina. The school’s leader was a former doctor who knew about Blackwell’s interest in becoming a physician. So, when she was not teaching, Blackwell prepared for med school using her doctor’s old medical textbooks. She ultimately saved $3,000 from her teaching job to pay for her education. 3. Creating opportunities for others. Learning from her experiences as a woman in medicine, Blackwell ensured that other women did not have to go through the same challenges. When she and her sister opened their clinic, their goals were two-fold: care for poor women in the community and provide working opportunities for women doctors. Blackwell was also a consistent advocate for women in medicine, writing several books on the topic and continuing her advocacy even after retiring.  How to think like Elizabeth Blackwell A great way to emulate Elizabeth Blackwell is by carving your own path, even when it is not obvious and even more when it’s not well traveled. Imagine if Blackwell allowed the men in her field to shake her confidence. Elizabeth knew that people’s unfounded opinions should never stop you from achieving your goals. The only person who knows everything that you are capable of is you.  Another important strategy is to focus on your growth. Blackwell invested in becoming a medical pioneer. How can you use your time and other resources to further your professional or personal development? Perhaps now is the time to take that online training or sign up for that class you have been thinking about for six months. As Blackwell shows us, investing in yourself can not only benefit you, but also the people in your community. Finally, make sure to open doors for others. Blackwell carved a path that made it easier for women to enter the medical field. How can you help others get on the same career path? There are many ways to do this, from hiring interns to joining a professional association to connecting with local schools to work with students. Consider how other people have opened doors for you and how you can pay it forward today.  Elizabeth Blackwell was a courageous woman and a pioneer in the medical community. She defied expectations to become a woman of firsts in her field. She also paid it forward to the next generation of women in medicine, helping them avoid and overcome obstacles she faced in her career. To follow Blackwell’s path, we should practice trusting our abilities, invest in our growth, and consider what we can do to welcome the next generation into our fields. The post Elizabeth Blackwell: the power of applied education appeared first on Ness Labs.

Born in 1908, Simone de Beauvoir was an influential writer, feminist, social theorist, and philosopher. She is best known for her 1949 book, The Second Sex, which upended traditional notions of the role of women in society. Beauvoir made the case that women have always been treated as an “other” and advocated for women’s liberation. Beauvoir also authored the Manifesto of the 343, which set the stage for legalizing birth control and abortion in France. The demands came from a gathering of 343 women that she organized to share their experiences with reproduction rights in the country. Beauvoir was also deeply engaged in politics and was one of the original editors of the left-wing French publication Les Temps Modernes, along with Jean-Paul Sartre and Claude Lazzman. There are many strategies we can learn from the mind of this revolutionary figure. This article is part of the Brilliant Thinkers series, which explores the thought processes, working habits, and decision-making principles applied by intellectuals who profoundly impacted the world with their discoveries and the way they challenged the status quo. Simone de Beauvoir’s thinking strategies Simone de Beauvoir was known to always challenge expectations, to be comfortable with dealing with ambiguous situations and addressing conflicting ideas simultaneously, and to embrace the “intellectual” label associated with her work. 1. Challenging the status quo. Beauvoir challenged societal expectations of women from the beginning. As a secondary school teacher, she was fired from multiple jobs for teaching about feminism. Schools accused her of “morally corrupting” the youth in the community.  When The Second Sex was published, Beauvoir presented a series of novel arguments to prove the existence of women’s oppression. She tied together creation myths, which suggested women were sinful and weak, with men’s treatment of women based on those myths. She also suggested that the idea of what makes a woman is a social construct, saying that “One is not born a woman, but becomes one.” These claims which challenged the status quo have become extremely influential. 2. Embracing ambiguity. When discussing social ills, some people exclusively blame individual behavior, while others focus only on systemic problems. Beauvoir, who published a book called Ethics of Ambiguity, was known for keeping individual and systemic issues in balance in her work. She recognized that social problems result from systemic oppression and individual actions. Instead of focusing one one perspective only and ignoring seemingly contradictory ideas, she was comfortable addressing conflicting viewpoints simultaneously when dealing with ambiguous situations. 3. Celebrating intellectualism. While some people may associate intellectualism with the negative connotation of a single-minded focus on thinking, Simone de Beauvoir embraced the intellectual quest of deriving knowledge from reason. She was an extremely active presence in the French intellectual community. In addition to her books, she wrote novels, essays, plays, and memoirs, and believed in the power of intellectualism to contribute to societal reform. How to think like Simone de Beauvoir A principle visible throughout Simone de Beauvoir’s work is that great thinking does not need to be neutral thinking. Beauvoir’s activism in the form of her writings brought awareness to the struggles facing women all over the globe. Her ideas paved the way for reproductive rights in France and the second wave of the feminist movement. Ask yourself: what are topics you are passionate about? What are areas where you would like to contribute to changing minds and fostering innovation? Next, write down public engagement skills that you are comfortable with – writing, speaking, teaching, organizing – and consider how you might use them to support causes that are important to you. Maybe you can launch a newsletter about climate change, start teaching decision-makers at your company about mental health in the workplace, or give a talk about the importance of inclusive design. Simone de Beauvoir is a great example of how rigorous thinking is compatible with advocacy. Another way to think like Simone de Beauvoir is to get more comfortable with ambiguity. Beauvoir wrote extensively about ethics in ambiguous situations and took great care to balance arguments in her work. Recognize the role of ambiguity in your life and increase your tolerance to ambiguity tolerance by studying the ambiguity effect. Finally, practice inclusive thinking. In her work, Beauvoir always made sure to include the voices of people who were often excluded from intellectual conversations. Whenever you are working on a project, consider how you will practice inclusion. Whose voices are being overlooked in decision-making processes? What steps can you take to make the project more inclusive? Simone de Beauvoir was an intellectual powerhouse whose stance against oppression sparked a movement. She challenged the status quo with the stroke of her pen and the power of her ideas. We can take inspiration from her by finding ways to use our talents to advocate for causes we care about, to think about our relationship with ambiguity, and to build more inclusive environments. The post Simone de Beauvoir: the power of intellectual advocacy appeared first on Ness Labs.

You have likely heard of Socrates and Plato, two of the most well-known ancient Greek philosophers. The names Pericles and Cicero may also ring a bell. But Aspasia, a little-known female philosopher with the gift of persuasion, is rarely mentioned in history books. However, she was one of the most influential philosophical figures in Athens. Aspasia’s father provided her with an education. However, she was forced to leave her home in Miletus, now modern-day Turkey, and found refuge in Athens. Aspasia could not become an Athenian citizen upon arrival. Since she did not have to conform to expectations for Athenian women, Aspasia could do many things that other women could not. She opened a salon where great thinkers of the day gathered to discuss philosophy and current events. Aspasia was always a part of the discussion and was an intellectual equal. She shared her gift of persuasive speech with Socrates, who later credited her as one of his teachers. Aspasia also taught rhetoric to young girls in Athens and encouraged them to seek more education. There are many lessons we can learn from this fearless philosopher. This article is part of the Brilliant Thinkers series, which explores the thought processes, working habits, and decision-making principles applied by intellectuals who profoundly impacted the world with their discoveries and the way they challenged the status quo. Aspasia’s thinking strategies Aspasia cultivated a life designed around productive debate, collective learning, and community building. In particular, there are three strategies she applied to become one of the most connected philosophers of her times. 1. Turning challenges into opportunities. Instead of seeing her lack of citizenship as an insurmountable barrier, Aspasia saw it as an opportunity. She seized the freedom to design her life outside of traditional expectations, hosting her private salons and building her very own school for young girls. 2. Delighting in debate. Rhetoric is the art of speaking and writing persuasively. While the term has come to have negative connotations, it used to be considered a civic art which Aristotle defined as “a combination of the science of logic and of the ethical branch of politics.” As you can imagine, the art of rhetoric was mostly considered a masculine affair, but Aspasia ignored the traditional expectations of women in Athens, and delighted in the heated conversations she held at her salons. She embraced debate as a powerful learning tool. 3. Establishing a knowledge-sharing hub. Great thinking partners make for great learning opportunities. Aspasia’s logic, debating skills, conversation, and eloquent speech attracted not only fellow philosophers but also artists and scientists. Her followers and supporters held significant positions of power in Athens. Not only did her salons help her grow her own knowledge, but they gave Athenian intellectuals an opportunity to share ideas across disciplines. She also developed an unusual partnership with military general Pericles. While the two could not marry because of Aspasia’s lack of citizenship (and Pericles was already married), the couple lived together and respected each other as equal parties. Pericles often consulted Aspasia on political matters, which was highly unusual at a time when women were not considered equals. How to think like Aspasia Aspasia saw challenges as an opportunity to take the road less traveled. To think like Aspasia is to embrace challenges and to defy societal expectations that can inhibit our ambitions. If you believe the world needs your work, keep on persevering the same way she did with her salons and her school for young girls. Another of Aspasia’s thinking skills you can draw inspiration from is to develop your power of persuasion. The ability to persuade people is an invaluable skill to succeed in your professional and personal life. Some strategies to strengthen your rhetoric skills include understanding what motivates your audience, identifying and bringing up needs your audience may not have thought of, and using storytelling to convey your point. While it is likely Aspasia mostly practiced her verbal skills, you can also write down your arguments to better spot ways to improve them. Finally, create or join a learning community. Aspasia created a space for people to share knowledge across disciplines and debate new ideas. With the ability to create a community online or in-person, the opportunities to gain insights and engage with other passionate people are endless. Try finding communities of diverse people who share your thirst for knowledge. Aspasia was a brilliant philosopher who used her outsider status to defy expectations about what women could accomplish. Even in the face of harsh critiques, she turned challenges into opportunities thanks to the power of persuasion. To follow her influence, we should embrace healthy debates, fight against artificial expectations that limit us, and foster safe spaces to learn together. The post Aspasia: the power of debate and collective learning appeared first on Ness Labs.

Katherine Johnson was always passionate about mathematics. She started taking classes at West Virginia State College at 13 years old and started her career as a math teacher. Then in 1953, Johnson became a part of a group of Black women mathematicians known as “human computers” at the Langley Research Center. Her equations sent the first American into space, allowed John Glenn to orbit the Earth, and let Neil Armstrong and Buzz Aldrin explore the moon safely. Johnson developed a reputation for precision and was never afraid to ask questions. However, no one knew who she was for decades until Margot Lee Shetterly documented Johnson’s extraordinary career in the book Hidden Figures. In 2015, Johnson won the Presidential Medal of Freedom for her contributions to space programs, and Hidden Figures was adapted into an Academy Award-nominated film. This article is part of the Brilliant Thinkers series, which explores the thought processes, working habits, and decision-making principles applied by intellectuals who profoundly impacted the world with their discoveries and the way they challenged the status quo. Katherine Johnson’s thinking strategies There are many lessons we can learn from Katherine Johnson’s incredible career and her experiences as a Black female mathematician. Three principles in particular have been recurring themes in her life and work. 1. Questioning the rules. Because things have been working a certain way doesn’t mean they ought to stay the same. Despite being indispensable contributors to space flight programs, Johnson and her Black female colleagues were not allowed to attend meetings about their projects. The reasoning? No girls allowed. Johnson famously questioned her male colleagues about this rule, asking if there was a law against women in meetings. Since there was no such law, Johnson persistently asked her colleagues to attend the meetings until they eventually let her in. She was the only woman to participate in these meetings. As time went on, her male colleagues increasingly relied on her insights. In addition to gender discrimination, Johnson also had to fight against racism. For instance, while the cafeteria was segregated by race, Johnson and her colleagues often ignored the signs telling them where to sit. Consistently questioning the rules was a core principle followed by Katherine Johnson. 2. Learning from the best. Instead of trying to study on her own, Johnson developed a network of mathematicians who supported her and inspired her. As a high school student, Johnson took a class with Angie Turner King. Turner King was one of the first Black women in America to earn a Master’s degree in mathematics and chemistry. She showed Johnson that it was possible to be a Black woman in this white, male-dominated field. While in college, Johnson jumped on the opportunity to learn from William Schieffelin Claytor. He was the third Black person to earn a Ph.D. in mathematics in America. Claytor encouraged Johnson to become a mathematician, even though at the time there were only 100 women in the profession. He even developed special classes just for Johnson to prepare her for a career in mathematics. Johnson later expressed gratitude for Clayton for supporting her career path. 3. Becoming an educator. Teaching is one of the most powerful ways to keep on learning. Johnson started her career as a math teacher. After 30 years with NASA, she continued to support the next generation of mathematicians. Johnson advocated for math education, supporting volunteer programs and math teachers. She also visited schools, spoke at events, and even responded to letters from students who wanted to become mathematicians. When she received the Presidential Medal of Freedom Award, NASA Administrator Charles Boden said that Katherine Johnson “is a big part of the reason that my fellow astronauts and I were able to get to space; it’s also a big part of the reason that today there is space for women and African-Americans in the leadership of our nation, including the White House.” How to think like Katherine Johnson One of the most obvious ways to think more like Katherine Johnson is to always question the rules. Cultivate a mindset of pushing back wherever you witness or experience outdated practices. If you see a colleague falling prey to the authority bias, call them out. Use Katherine Johnson as an inspiration to ask difficult questions and be an agent of change. However, the pursuit of progress does not need to be a solitary journey. Finding your role models and learning from them will accelerate how fast you acquire new knowledge, skills, and even relevant professional connections. Ask yourself: who are the experts in your field that could serve as inspiration, and who you could learn from? Identify these experts, make a list, then spend a bit of time familiarizing yourself with their work. In some cases, you may even be able to contact them and ask them a few questions. Or, even better, if you’re enrolled in a course as a student — whether independently or as part of a formal education programme — you may be able to connect with some of the best instructors in your field and learn directly from them. Finally, make sure to pay it forward. Just as we must learn from those who came before us, we should also share what we have learned with the next generation. You don’t have to wait until you’re an expert to start inspiring other students. It can take on different forms: mentoring a younger colleague, visiting schools, advocating for more educational programs in your field, publishing tutorials, sharing what you learn on social media. You may become the one person to inspire the next Katherine Johnson. Katherine Johnson was extraordinarily persistent, curious, and brave. She refused to let artificial barriers prevent her from making a lasting impact in her field. You can apply some of Johnson’s thinking strategies by always questioning the rules, connecting with the best experts in your fields, and by becoming an educator to in turn inspire the next generation of brilliant thinkers. The post Katherine Johnson: the power of questioning the rules appeared first on Ness Labs.

Scientist Jane Goodall always watched the world around her. As a child, she would spend hours watching jumping spiders and keep all kinds of pets. She also gave her parents quite a scare when she went missing as a child. But her parents eventually found her in the henhouse observing the chickens. Jane just wanted to know how they laid their eggs. Goodall’s curiosity, patience, and powerful observation skills ultimately led her to Tanzania’s Gombe Stream Game Reserve. She established relationships with chimpanzees in the reserve and watched them search for food, find mates, and tend to their babies. She wrote the book The Chimpanzees of Gombe: Patterns of Behavior in 1986 and completely upended our understanding of chimpanzees’ behavior. Goodall eventually left the field to advocate for captive chimpanzees and sustainable development. There is a lot we can learn from this keen observationist, prolific writer, and environmental activist. This article is part of the Brilliant Thinkers series, which explores the thought processes, working habits, and decision-making principles applied by intellectuals who profoundly impacted the world with their discoveries and the way they challenged the status quo. Jane Goodall’s thinking strategies Jane Goodall had a deep understanding of the importance of immersing ourselves in the world around us and the value of taking our time. She also showed trust in her research when faced with rebuttal from fellow scientists. Here are three strategies she applied throughout her extraordinary life and career. 1. Immersing yourself in the world. Like other young women in the 1950s, Goodall began her career as a secretary. So how did she become a renowned scientist? While working as a secretary in Nairobi, Goodall met paleontologist and anthropologist Louis Leakey. Leakey was so impressed by Goodall’s knowledge and understanding of the natural world that he brought her on as a researcher to study chimpanzees in Tanzania. Goodall eventually earned her Ph.D. in Ethology in 1965, becoming one of the only people to do so without a Bachelor’s degree. She is proof that not all groundbreaking scientists start in a lab; there is much to be learned just by looking at the world around us. 2. Taking your time. It took 25 years for Goodall to publish her definitive book on chimpanzees’ behavior. Each discovery she made was the result of patiently looking for patterns. For instance, Goodall once observed a chimp using a blade of grass to pull termites from a mound. If she stopped there, she might have noted that one chimp used grass to feed himself. But the next day, Goodall witnessed the same chimp pull leaves off a twig to get at the termites. The chimp made a tool. That novel discovery would not have happened without a lot of time spent in the field and several focused observations. 3. Having the courage of your evidence-based convictions. In academia, Goodall faced challenges with men who belittled her work or did not accept her findings. In a 2014 interview, Goodall explained that these critiques from men did not matter because she was confident in her work and results. She said: “My mother always taught us that if people don’t agree with you, the important thing is to listen to them. But if you’ve listened to them carefully and you still think that you’re right, then you must have the courage of your convictions.” How to think like Jane Goodall The outside world can become invisible when we focus on solving specific problems. For example, it is very common for startups to build solutions in search of a problem. To think like Jane Goodall, pick your head up and look around you. Do you see any patterns? How are people navigating the world? You can learn a lot from pure observation. Another important ingredient in Jane’s thinking toolkit is patience. Remember, her definitive book on chimpanzee behavior took 25 years to publish. It takes time to learn new things and develop mastery of a new skill, topic, or process. Give yourself grace when you are still in the knowledge-building phase. Finally, stand up for yourself, especially when facts and data are on your side. Follow the advice from Jane’s mother. If someone disagrees with you, listen to their reasoning. After listening, if you believe you are right, be willing to say so. Be especially wary of those who seem to disagree with you based on factors that have nothing to do with your actual work. Jane Goodall’s patience, curiosity, and confidence made her one of the most influential scientists of our time. The lessons we can learn from her remarkable career should inspire us to be more present in the world around us. Goodall’s life also highlights the rewards that come with taking our time and the benefits of standing firm in our beliefs. What can you do today to follow in her footsteps? The post Jane Goodall: the power of experimentation and conviction appeared first on Ness Labs.

Ada Lovelace is considered the world’s first computer programmer. In 1842, Lovelace translated an Italian publication about Charles Babbage’s Analytical Engine into English. However, this was no ordinary translation. Lovelace added extensive notes of her own, suggesting ways the Analytic Engine could be programmed to calculate certain equations using a series of punch cards. Her insights ultimately inspired Alan Turing’s work on the first modern computers in the 1940s. Ada Lovelace is a brilliant thinker because she defied many stereotypes of mathematicians. She was not a “human calculator” who lacked social skills or knowledge of other disciplines. Let’s have a look at Lovelace’s key thinking strategies and how we can apply these to our own lives. This article is part of the Brilliant Thinkers series, which explores the thought processes, working habits, and decision-making principles applied by intellectuals who profoundly impacted the world with their discoveries and the way they challenged the status quo. Ada Lovelace’s thinking strategies Not only was Ada Lovelace wildly imaginative, but she also valued her relationships in the scientific community and frequently connected science and literature. Throughout her life, she applied three key strategies to grow her knowledge and make new discoveries. 1. Investing in mentorship. Lovelace understood the importance of cultivating relationships. After attending a house party in her teens at the home of Charles Babbage, a mathematician and inventor, Ada became enthralled with his plans to develop an early version of the modern computer called the Analytical Engine. Eventually, the relationship grew into one Ada could rely on for mentorship and support. For instance, after her mathematical journey was interrupted by marriage and family, Lovelace reached out to Babbage to return to mathematics. Babbage connected her to a professor at the University College of London, where she learned how to perform calculus by exchanging letters. Her ongoing professional relationship with Babbage was critical to her studies and success. 2. Building bridges across knowledge areas. Ada was the daughter of Annabelle Milbanke and Lord Byron (yes, that Lord Byron, Romantic poet and author of Don Juan, among other works). After separating from Ada’s father, Annabelle ensured Ada received a rigorous education in math and science. However, Ada also studied literature and other disciplines. Ada had the unique ability to use poetic, pattern-based language to describe mathematical insights. She often used metaphors to explain scientific theories, seeing no need to separate poetry from the sciences. For example, when explaining how the Analytical Engine could calculate equations, Lovelace said that the engine “weaves algebraic patterns, just as the Jacquard loom weaves flowers and leaves.” 3. Using your imagination. Ada Lovelace had a unique perspective on the role of creativity and imagination in math and science. She described creativity as having two key components, the ability to find commonalities between seemingly unrelated subjects, and the ability to conceptualize and visualize ideas that do not yet exist. Mathematics is not always about what is in front of us but also shows us what could be. That’s why Lovelace described imagination as a “discovering faculty” that allows us to see unseen worlds in science.  How to think like Ada Lovelace It can be tough for those who are proudly self-reliant to ask for help, let alone to develop a mentor-mentee relationship. Take small steps towards supportive relationships by emulating Ada and making relationship cultivation easier for yourself with those three steps: Identify people you already know whose work you admire and can help you improve your knowledge or assess your ideas. Figure out how to reach out to them you think will be most respectful of their time. You can start by a short message explaining why you would like to connect, and offering some options. Make sure to be specific so you avoid sending one of these vague pick-your-brain requests. If they agree to connect with you, prepare three questions for them in advance of the discussion, as well as your next steps to move the relationship forward after the meeting. Another way to think like Ada Lovelace is to expand your “expertise base” outside of your core discipline. Ask yourself: what are some of your interests outside of work? Increasing your knowledge about other subject areas can help you expand your circle of competence and practice networked thinking by understanding relationships across disciplines. Finally, make sure to regularly flex your creative muscles. Being creative does not mean you need to become the next Picasso. Small practices like spending time outside and getting a good night’s sleep can help you think more creatively and fire up your imagination. In line with what Ada Lovelace was practicing, an article from the American Psychological Association suggests several ways to bolster your creativity, including jotting down new ideas in a notebook, taking on challenging tasks, like developing a new hobby, and developing relationships with people who are outside of your field to diversify your thinking. Ada Lovelace was a pioneer in mathematics who brought the arts and sciences together to bring modern computing to fruition. With support from her mentor and an endless imagination, she was able to accomplish incredible feats in her field. To follow our inner Ada, we should do our best to seek support and mentorship from our peers, connect ideas across disciplines, and purposefully nurture our creativity. The post Ada Lovelace: the power of imagination and poetical science appeared first on Ness Labs.

Marie Curie was a woman of firsts. Born in 1867 in Warsaw, Poland, she was a child prodigy in literature and mathematics. She worked as a governess until the age of 24 to save money for school, where she became the first woman in France to earn her Ph.D. She studied uranium, a radioactive element that was not well understood at the time. Curie discovered two new elements, radium and polonium, and concluded that these elements are responsible for uranium’s radioactive properties. She went on to apply her findings to create cancer treatments and advance x-ray technology. Curie became the first woman to win a Nobel Prize in 1903. Then, in 1911, she became the first person to win two Nobel Prizes, and still holds the record as the only woman who has earned two Nobel Prizes in two different fields (Physics and Chemistry). It’s an understatement to say that she profoundly impacted the world with her ideas, and there is a lot to learn from her approach to problem-solving. Let’s have a look at how you can learn to think more like Marie Curie, and apply her thinking strategies in your daily life and work. This article is part of the Brilliant Thinkers series, which explores the thought processes, working habits, and decision-making principles applied by intellectuals who profoundly impacted the world with their discoveries and the way they challenged the status quo. Marie Curie’s thinking strategies An extraordinary scientist, Marie Curie relied on three key strategies to navigate the world, make decisions, collaborate with others, and explore new ideas. 1. Embracing the unknown. Science operates in a world of unknowns. Still, even scientists struggle with accepting new thoughts or approaches that conflict with their understanding of the world. However, Marie Curie was not afraid of new ideas. She proffered her own “daring hypothesis” early in her career that caused a scientific stir.  At the time, scientists thought that radiation came from interactions between two molecules. However, they were not sure which molecules or how the interactions occurred. Curie proposed that radiation did not come from two molecules; instead, it came from sub-molecules. This idea challenged the widely-held belief that atoms did not have any sub-particles.  Undeterred, Curie continued her work and found the two sub-particles that caused radiation: radium and polonium. She won the Nobel Prize for this research in 1903.  2. Making radical bets. Sometimes, the most radical bet you can make is the bet you make on yourself. Marie Curie had the confidence to bet on herself, despite a cascade of misogynistic criticism that gave her husband and lab partner, Pierre Curie, much credit for their work. When Pierre died unexpectedly, colleagues expected Marie to accept her widow’s pension and step down from the lab. Instead, she did the exact opposite; believing in her abilities, she stayed at the university, Sorbonne, and took over the lab herself.  3. Sharing her ideas. Marie Curie was not interested in keeping her research isolated in the laboratories of chemistry or physics departments. Instead, she would work with anyone interested in radiation, including people in healthcare. In fact, during World War I, Curie used her work to equip ambulances with x-ray machines. She even drove the ambulances herself to help soldiers who needed medical care. How to think like Marie Curie We live in an unpredictable world filled with unknowns. However, fear of the future can paralyze us, making it difficult to engage in creative problem-solving and strategizing. Also, if we create work cultures that are too risk-averse, we can unintentionally stymie innovative contributions. Thinking like Marie Curie requires rethinking our relationship with risk. It also requires learning how to bet on ourselves. Marie Curie did not let other people’s prejudices against women get in the way of her work. She made decisions about her career because she valued the power of science. Betting on ourselves means believing in ourselves and making choices based on our values. Finally, we may not want to share our ideas before they are “ready.” However, sharing ideas can be a great way to connect with others inside and outside your field. Sharing also provides an opportunity to receive feedback from many different perspectives. Sharing doesn’t have to be scary. It can mean a call to a trusted colleague or a post in a LinkedIn group; whatever feels the most comfortable for you. Here are three practical questions you can ask yourself in order to think like Marie Curie: What is a small risk that you can take right now to improve your work or personal life? What might happen if you take that risk? Focus on the possible positive outcomes to encourage yourself to act. Are your work, school, or personal decisions aligned with your personal values? Are you making decisions based on these values? If not, what small steps can you take to become better aligned? How comfortable do you feel sharing your ideas with the world, even when they are half-baked? Is there an idea you have been sitting on that you could share with someone to get their feedback? Marie Curie remains one of the most important scientific figures in history. She embraced the unknown, always bet on herself, and took her findings out of the lab and into the world. To follow her lead, we must be willing to face an uncertain future, have the confidence in ourselves to tackle whatever challenge comes our way, and surround ourselves with a community that allows for free, open exchange of ideas. The post Marie Curie: the power of sharing radical ideas with the world appeared first on Ness Labs.

Can you imagine a pink elephant? Is it big or small? Hot pink or pastel pink? Does it look happy, sad, tired, or excited? Give your pink elephant as much detail as you can. Now that you have got your pink elephant clear in your head, it is time to stop thinking about it. Think about any other topic for 30 seconds, and observe where your thoughts take you. How long did you last without the pink elephant creeping back into your mind? For most of us, that pink elephant will appear back in our thoughts within seconds. The same is true of unwanted and intrusive thoughts: the more you try to suppress them, the more they will bother you. This is called the Pink Elephant Paradox. Learning how to manage obsessive or intrusive thoughts can help you to avoid the associated pitfalls of negative emotions, distractibility, and poor decision-making. From white bear to pink elephant In 1987, the Journal of Personality and Social Psychology published a paper entitled ‘Paradoxical effects of thought suppression’. The study involved participants taking part in two experiments in which they verbalised their stream of consciousness for five minutes. As part of the first experiment, the participants were asked not to think about a white bear. In the second experiment, participants were asked to think about a white bear.  The researchers found that participants were more preoccupied with thinking about a white bear in the first experiment, despite being asked to not think of one. This suggests that trying to suppress a thought “has paradoxical effects as a self-control strategy,” and can lead to obsession or preoccupation despite an individual’s best efforts to ignore the thought. As writer Fyodor Dostoevsky famously put it in Winter Notes on Summer Impressions: “Try to pose for yourself this task: not to think of a polar bear, and you will see that the cursed thing will come to mind every minute.” Whether it’s a white bear, a pink elephant, or any other thought, this psychological process whereby our deliberate attempts to suppress certain thoughts make them more likely to surface has been named “ironic process theory” by scientists. For example, when your life hits a bump in the road, family or friends may recommend that you “just stop thinking about it”. However, their advice to suppress your thoughts could paradoxically serve only to strengthen your intrusive thoughts. The Pink Elephant Paradox can not only intensify intrusive thoughts, but it can also impact the way we think, feel and make decisions. You have probably experienced this phenomenon if you have ever felt more distracted or less productive at work because of a ruminating thought or unresolved issue. The impact of the Pink Elephant Paradox There are three ways that the Pink Elephant Paradox can affect our thoughts and emotions. 1. Propagation of persistent negative emotions. Intrusive thoughts might include “repetitive thoughts, images or impulses.” Unfortunately, intrusive or unwanted thoughts are associated with depression, anxiety, post-traumatic stress, and obsessive compulsive disorders. However, individuals who are otherwise healthy can also develop intrusive thoughts that are comparable to a clinical obsession.  There is also evidence that rumination and intrusive thoughts are associated with negative thought patterns. Negative thought patterns were also found to be more common in those who did not practice mindfulness. Mindfulness requires an individual to become more aware of sights, sounds, thoughts and emotions, rather than trying to suppress them.  Without mindfulness, the opportunity to address difficult thoughts or feelings does not arise, and instead we attempt to suppress the emotions. This attempt at suppression, rather than acknowledgement, feeds into the Pink Elephant Paradox, causing the thoughts to become intrusive. 2. Increased distractibility. A study found that those who are plagued by negative thought intrusions, and individuals who have a propensity to worry, show increased distractibility when trying to focus on a specific task. Furthermore, the more an individual struggles with intrusive thoughts, the more distractible they tend to be.  The accessibility of social media, emails and other forms of communication or entertainment can distract even the most dedicated worker. However, if you are managing intrusive thoughts on top of technological distractions, staying focused poses an even greater challenge.  Being easily drawn away from the task in hand, by any form of distractor, disrupts focus and prompts the brain to try to multitask. Any form of disruption will stunt your professional creativity and development. It also means that each task could be taking you far longer than it should. Being easily distracted could be making it harder for you to establish and nurture professional and personal relationships, too. 3. Poor decision making. Intrusive thoughts can be so intense that it becomes difficult to focus on anything else. Although these thoughts or emotions can appear salient, they can be masking other, more important factors or considerations. With the intrusive thought taking centre stage, your decision making can become skewed. Rather than being able to make rational, carefully considered judgments, you may instead be swayed by persistent thoughts that lead you to make the wrong decision. How to manage The Pink Elephant Paradox There will be times when almost all of us experience the intrusion of thoughts that we have tried to suppress. Psychologists have shown that directly trying to suppress the thoughts is likely only to make them more persistent. Instead, there are other ways you can manage intrusive thoughts to remove their power and make them less noticeable. Use self-reflection to reduce the impact of intrusive thoughts. Self-reflection and mindfulness have been proven to protect individuals from the negative impact of intrusive thoughts. In particular, becoming more aware and accepting of negative thoughts or feelings can help to reduce the frequency of intrusive thoughts, as well as making them feel less distressing. Mindfulness shifts the focus from the intrusive thought to the present moment, helping to alleviate the fear or anxiety associated with the thought. By accepting a thought, and trying not to see it as negative, an individual’s perceived distress at the impulse or emotion can be minimised. Engage in constructive distractions. When an intrusive thought arises, finding a constructive distraction is healthier than ruminating on it. Refocusing your energy on a different task can help you to engage your brain in a different activity. Find something that requires almost all of your attention, such as reading, chatting to a friend, going for a run, painting or watching a film. By concentrating on something else, your mental energy is used elsewhere, leaving less room for intrusive thoughts. Find a positive thought substitution. If you find yourself ruminating on negative thoughts, try to replace them with a positive. On a blank piece of paper, draw two columns. When a negative thought persists, counterbalance it with the corresponding positive response. For example, if you think “I am a failure”, you might counteract the thought with “I made a mistake, but I am learning from it now”. If something is “too hard”, your positive substitution could be, “I will work hard to get better at this.” By turning negative ruminations into positive pledges, the intrusive thought loses the power it has over you. Thinking of positive solutions also helps you to make any appropriate adjustments or improvements. The Pink Elephant Paradox illustrates that trying to suppress a thought is likely to make it more intrusive. This can negatively affect your emotions, focus and decision-making abilities. Rather than suppress negative thoughts, it is healthier to acknowledge the emotion. Finding a constructive distraction that works for you, and reflecting on positive thought substitutions, can also help you to stop ruminating about intrusive, distressing, or unwanted thoughts. The post The Pink Elephant Paradox: how intrusive thoughts impact our emotions and decisions appeared first on Ness Labs.

Welcome to this edition of our interview series, where we connect with founders on a mission to help us achieve more without sacrificing our mental health. Craig Doig is the co-founder of Markee, a white-label collaboration tool that allows you to meet, chat, and share files with your team or whoever you would like all under your own logo, brand colors, and domain. In this interview, we talked about the importance of privacy and simplicity, the challenges of working with external partners, the debate of remote versus hybrid work, the future of online collaboration, the benefit of properly disconnecting from work, and more. Enjoy the read! Hi Craig, thank you so much for agreeing to this interview. Between Zoom, Slack, and other communication tools, people feel overwhelmed when collaborating with their team. Can you tell us a bit about what makes Markee different? It’s my pleasure, thanks so much for having me! We have been interested in the communication space for quite some time. Before Markee was a real startup company we were a group of creatives and developers remotely collaborating across six timezones. Between the core team, it’s likely we have used or tried over fifty tools. Nothing ever ticked all of our boxes. The most prominent reason was the lack of ownership. We never felt like we had a sense of ownership over any cloud-based tool. That became one of our core focuses: allowing our customers to experience a cloud tool that was fully brandable. That said, what makes us unique actually comes from a deeper but simple philosophical frame. We believe people deserve the right to enjoy and explore something as simple as a SaaS tool without feeling lost or tracked. That’s why simplicity and privacy are two of our core values. We want to remove as many negative barriers or complex dopamine triggers from work tools as possible. Everything is two clicks away fully encrypted. We are never storing personal data other than name and email. And if you ever leave, you can ask us to destroy everything. Those are great core values. What inspired you to build Markee? Originally, Markee was built as an event management and collaboration tool that could be used as a totally white labeled experience, something for people to differentiate themselves from the ubiquitous Zoom and Hopin events. We started building a rough prototype early with a few not-for-profits and local businesses who helped guide the design process. For example, we worked with a disabilities charity where the team was keen to stand out in the new digital fundraising space, and that encouraged us to add font options and access controls. After tons of feedback from these early partners, we decided to focus on the collaboration aspects of our tool, and thus the current version of Markee was born. And how does Markee work exactly? We see Markee as an all-in-one collaboration solution for remote and in-house teams, it allows you to host video meetings, chats, and share files with anyone. Our goal was to take the core features that people need every day at work and make them simpler. If you think of tools like Slack, you can only chat with your team members and you need to deal with confusing permission systems. This can make externally sharing spaces, chats, and video calls externally complicated or even impossible. Markee combines video and text chat rooms into one, and allows you to share it like you would a Notion or Google document. We think this makes things simple and accessible for even non-technical users both inside or out of your team. We are also browser based, so you don’t have to download anything or ask your customers to do so. For companies using Slack to communicate internally, Zoom to host meetings, and Dropbox to share documents, Markee is a completely new way to collaborate. Our goal is to make collaboration about meaningful discussions rather than being a notification machine that follows you everywhere. Now for a more high-level question. Business owners are still debating whether they should go fully remote, hybrid, some are considering asking everyone to come back to the office. What’s your view regarding this debate? We built Markee to enable remote and hybrid work, but if you look at most of our branding we tend to promote hybrid work. We believe human interaction and real life engagement is important for the development of ideas and growth, but certainly not a total necessity. Personally, I believe it should be optional to engage in person, and that businesses should promote “opt in” spaces or hubs where there is a concentration of employees. I think this helps the more extroverted on your team thrive without putting any pressure on teammates to come in, particularly if you have a culture that uses their communication tools in a healthy way that keeps everyone abreast of critical developments.  Markee is a relatively new product and you have been rapidly iterating and working on new features. Can you tell us about your approach to product development? We simply listen to our customers’ feedback. We very actively listen and engage with our customers and try to solve their core issue rather than just releasing a workaround or patch. We enjoy going back to them and gathering their feedback on the solution as well before we push anything live. This has allowed us to stay transparent with everyone and implement features that are always well received.  Listening to your customers is so important indeed. You have also put together a team of “Collaboration Experts” — what exactly do they do? When you sit down with one of our experts, the first thing they are going to do is create a vision of what clear and easy collaboration looks like for your team. Once they have a better idea of the desired outcome, they will evaluate your tech stack and provide you with recommendations on how you might optimize it, as it exists, to achieve those goals. If they think Markee makes sense, they will recommend and provide context for processes that could be winning plays in the long run. But they only do that if they genuinely think it would be a good fit. We have an empathetic sales team that believes in solving problems rather than providing solutions to problems that do not exist. We see this approach as an opportunity to transcend the traditional business model of selling at all costs. This is a very refreshing approach. You are also taking security very seriously. Can you tell us more? There are really two different threads here, there is user and data privacy and there is security from outside threats. First, every video chat is secure — our video calls are HIPAA-compliant and all our chats and file sharing are secure. To the second point, Markee doesn’t track any user behavior or personal data on the platform. Your files and private information remain yours, so you will never have to worry about vague terms and conditions or unreliable security. Upon request, we even destroy all copies of your files and information so you can tie up loose ends without liability concerns. That’s great to hear. I also wanted to ask you: what kind of people use Markee? We run the gamut when it comes to customer composition. For example, we have a charity that uses Markee to conduct therapy in a secure environment while also facilitating ongoing conversations with multiple members of the communities they support. Another awesome customer is a local software company using our tool for sales calls, then turning those calls into ongoing asynchronous conversations with their clients. What’s super cool is they also use our tool for internal collaboration which means it’s easy to connect their clients with other team members with a few clicks rather than meeting with them in another tool like Zoom. Almost all businesses need a secure platform that their clients can trust, and at the same time, they need an all-in-one workspace that holds all the files, information, and conversations for a project in an organized manner. That’s what we aim to offer with Markee. What about you… How do you personally use Markee? We really try to “eat our own dog food” by implementing it into our day-to-day routines. Everyone in our team’s ecosystem, friends, family, and close customers are using it and sharing feedback. Going through a typical week can give you an idea of all of the unique ways to use Markee. We do a standing meeting on Monday, Wednesday, and Friday with the team in our general room, which we use to greet each other via text chat in the morning and announce things during the week. During various department breakout meetings we hold our video meetings in the same team rooms where we keep the asynchronous conversations going and store our files and links. For the sales team and myself, we like to use the “Schedule Meeting” function to set up a meeting for each of our potential customers and automatically send it through Google calendar. My favorite part is the “Direct Messages” feature, where we create groups with custom names and do a lot of the intricate small team projects with all the power of a normal room. Other features I love are the user locations that you can see moving around the product, and of course the fact we can change the branding in real time. I already mentioned that Markee is browser based, but it’s also notification free. You have push notifications when you have it open in the browser, but not when you close the tab. This kind of thing is very important to us, setting work boundaries and making sure people are able to disconnect when they need to. We think more business tools should apply a similar philosophy. I completely agree. There’s still so much work to improve the way we collaborate online. Where would you like Markee to be in the next few years? We hope to continue to help others connect in a simple, healthy, and personal way. I think we have a bright and vibrant future with a growing community of users that just ...

Can you imagine a pink elephant? Is it big or small? Hot pink or pastel pink? Does it look happy, sad, tired, or excited? Give your pink elephant as much detail as you can. Now that you have got your pink elephant clear in your head, it is time to stop thinking about it. Think about any other topic for 30 seconds, and observe where your thoughts take you. How long did you last without the pink elephant creeping back into your mind? For most of us, that pink elephant will appear back in our thoughts within seconds. The same is true of unwanted and intrusive thoughts: the more you try to suppress them, the more they will bother you. This is called the Pink Elephant Paradox. Learning how to manage obsessive or intrusive thoughts can help you to avoid the associated pitfalls of negative emotions, distractibility, and poor decision-making. From white bear to pink elephant In 1987, the Journal of Personality and Social Psychology published a paper entitled ‘Paradoxical effects of thought suppression’. The study involved participants taking part in two experiments in which they verbalised their stream of consciousness for five minutes. As part of the first experiment, the participants were asked not to think about a white bear. In the second experiment, participants were asked to think about a white bear.  The researchers found that participants were more preoccupied with thinking about a white bear in the first experiment, despite being asked to not think of one. This suggests that trying to suppress a thought “has paradoxical effects as a self-control strategy,” and can lead to obsession or preoccupation despite an individual’s best efforts to ignore the thought. As writer Fyodor Dostoevsky famously put it in Winter Notes on Summer Impressions: “Try to pose for yourself this task: not to think of a polar bear, and you will see that the cursed thing will come to mind every minute.” Whether it’s a white bear, a pink elephant, or any other thought, this psychological process whereby our deliberate attempts to suppress certain thoughts make them more likely to surface has been named “ironic process theory” by scientists. For example, when your life hits a bump in the road, family or friends may recommend that you “just stop thinking about it”. However, their advice to suppress your thoughts could paradoxically serve only to strengthen your intrusive thoughts. The Pink Elephant Paradox can not only intensify intrusive thoughts, but it can also impact the way we think, feel and make decisions. You have probably experienced this phenomenon if you have ever felt more distracted or less productive at work because of a ruminating thought or unresolved issue. The impact of the Pink Elephant Paradox There are three ways that the Pink Elephant Paradox can affect our thoughts and emotions. 1. Propagation of persistent negative emotions. Intrusive thoughts might include “repetitive thoughts, images or impulses.” Unfortunately, intrusive or unwanted thoughts are associated with depression, anxiety, post-traumatic stress, and obsessive compulsive disorders. However, individuals who are otherwise healthy can also develop intrusive thoughts that are comparable to a clinical obsession.  There is also evidence that rumination and intrusive thoughts are associated with negative thought patterns. Negative thought patterns were also found to be more common in those who did not practice mindfulness. Mindfulness requires an individual to become more aware of sights, sounds, thoughts and emotions, rather than trying to suppress them.  Without mindfulness, the opportunity to address difficult thoughts or feelings does not arise, and instead we attempt to suppress the emotions. This attempt at suppression, rather than acknowledgement, feeds into the Pink Elephant Paradox, causing the thoughts to become intrusive. 2. Increased distractibility. A study found that those who are plagued by negative thought intrusions, and individuals who have a propensity to worry, show increased distractibility when trying to focus on a specific task. Furthermore, the more an individual struggles with intrusive thoughts, the more distractible they tend to be.  The accessibility of social media, emails and other forms of communication or entertainment can distract even the most dedicated worker. However, if you are managing intrusive thoughts on top of technological distractions, staying focused poses an even greater challenge.  Being easily drawn away from the task in hand, by any form of distractor, disrupts focus and prompts the brain to try to multitask. Any form of disruption will stunt your professional creativity and development. It also means that each task could be taking you far longer than it should. Being easily distracted could be making it harder for you to establish and nurture professional and personal relationships, too. 3. Poor decision making. Intrusive thoughts can be so intense that it becomes difficult to focus on anything else. Although these thoughts or emotions can appear salient, they can be masking other, more important factors or considerations. With the intrusive thought taking centre stage, your decision making can become skewed. Rather than being able to make rational, carefully considered judgments, you may instead be swayed by persistent thoughts that lead you to make the wrong decision. How to manage The Pink Elephant Paradox There will be times when almost all of us experience the intrusion of thoughts that we have tried to suppress. Psychologists have shown that directly trying to suppress the thoughts is likely only to make them more persistent. Instead, there are other ways you can manage intrusive thoughts to remove their power and make them less noticeable. Use self-reflection to reduce the impact of intrusive thoughts. Self-reflection and mindfulness have been proven to protect individuals from the negative impact of intrusive thoughts. In particular, becoming more aware and accepting of negative thoughts or feelings can help to reduce the frequency of intrusive thoughts, as well as making them feel less distressing. Mindfulness shifts the focus from the intrusive thought to the present moment, helping to alleviate the fear or anxiety associated with the thought. By accepting a thought, and trying not to see it as negative, an individual’s perceived distress at the impulse or emotion can be minimised. Engage in constructive distractions. When an intrusive thought arises, finding a constructive distraction is healthier than ruminating on it. Refocusing your energy on a different task can help you to engage your brain in a different activity. Find something that requires almost all of your attention, such as reading, chatting to a friend, going for a run, painting or watching a film. By concentrating on something else, your mental energy is used elsewhere, leaving less room for intrusive thoughts. Find a positive thought substitution. If you find yourself ruminating on negative thoughts, try to replace them with a positive. On a blank piece of paper, draw two columns. When a negative thought persists, counterbalance it with the corresponding positive response. For example, if you think “I am a failure”, you might counteract the thought with “I made a mistake, but I am learning from it now”. If something is “too hard”, your positive substitution could be, “I will work hard to get better at this.” By turning negative ruminations into positive pledges, the intrusive thought loses the power it has over you. Thinking of positive solutions also helps you to make any appropriate adjustments or improvements. The Pink Elephant Paradox illustrates that trying to suppress a thought is likely to make it more intrusive. This can negatively affect your emotions, focus and decision-making abilities. Rather than suppress negative thoughts, it is healthier to acknowledge the emotion. Finding a constructive distraction that works for you, and reflecting on positive thought substitutions, can also help you to stop ruminating about intrusive, distressing, or unwanted thoughts. The post The Pink Elephant Paradox: how intrusive thoughts impact our emotions and decisions appeared first on Ness Labs.

New Things Under the Sun is a living literature review; as the state of the academic literature evolves, so do we. Here are a few recent updates. Importing Knowledge in the Age of Mass Migration The article Importing Knowledge looks at what happens when scientists and inventors immigrate. As might be expected, after receiving migrant inventors, a receiving country tends to do better in the technology fields where the migrant inventors have comparative strength. But what’s perhaps less expected is that the impact on the field exceeds the extra output brought by these talented inventors and seems to spill over to domestic inventors. This article has now been updated to include a discussion of a new paper by Diodato, Morrison, and Petralia, which investigates the same question using a new dataset for the period 1870-1950. Diodato, Morrison, and Petralia (2021) looks across the United States over the period 1870-1950 to see what happens when different US cities receive more migrant scientists and inventors. In particular, they want to know what happens to the inventive activities of US-born inventors when foreign inventors move to town. With quite a lot of creative and tedious work, they are able to construct year-by-year, city-by-city, field-by-field, inventor-country-of-origin data for the USA over 1870-1950. They document several facts that are consistent with the above case studies. First, when a city receives more migrant inventors with expertise in a given technology field (as indicated by how the patents of these migrant-inventors are classified), this is associated with increased patenting by US-born residents of the same city. For their second fact, they restrict their attention to cities and years where US-born inventors have no patents in a given technology field. They then show that when a migrant inventor working in that field shows up, the city is more likely to have patents, in that field, by US-born inventors, in subsequent years. Third, analogous to Bahar, Choudhury, and Rapoport (2020) [note: discussed previously in the article], they show all this holds even when you use some statistical techniques to try and tease out just the migrants who moved to various cities for reasons uncorrelated with that city’s technological opportunity. This should strip out cases, for example, where a town gets a new college or national lab that attracts a lot of inventors, from all backgrounds, who work in a particular technology field. Why does this happen? “Importing Knowledge” argues that’s because the inventors bring more than just their own brainpower - they also bring new knowledge and ideas that spreads through local inventor networks. From the same piece, but later: Diodato, Morrison, and Petralia’s study of migration to different US cities in the first half of the twentieth century provide three additional strands of suggestive evidence. First, they show that most of the “oomph” of having migrant inventors comes from having only a small number of them. Stated more precisely, the increase in patents from US-born inventors, in a given technology, that arises when migrant inventors skilled in that technology move to the city is only slightly larger when many migrant inventors move in, as compared to fewer. Second and closely related, they show the impact of migrant scientists moving to your city fades over time. Both are consistent with the notion that it only takes that first “seed” to get a “garden of knowledge” going - though more seeds can help it grow faster. Finally, Diodata, Morrison, and Petralia provide some evidence that migrant inventors may help connect US born inventors with foreign knowledge, even if the migrant inventor doesn’t personally have that knowledge. To illustrate the idea, suppose Nikola is an inventor who emigrates from France to the USA and takes up residence in New York. Let’s suppose Nikola is an active inventor of technologies related to electricity. Meanwhile, suppose France is renowned for its food processing technologies, even though this is not an area in which Nikola is active. Diodato, Morrison, and Petralia show that having Nikola show up in New York increases the patenting of US-born New Yorkers both in the technologies in which he is directly involved (electricity in this example), as well as the technologies he is not directly involved in, but which are associated with his country of origin (food processing, in this example). The first effect is larger and more robust, but both are there. Read the whole thing for a lot more evidence on these points. Read the whole thing Fresh Perspectives in History The article Gender and What Gets Researched argues that one of the factors that affects researcher’s choice of research topic is what they find personally meaningful. This, in turn, can be affected by different people’s life experiences. One simplistic but well documented place you can see evidence of this is in the different research choices of men and women. “Gender and What Gets Researched” looked at some good evidence on differing research choices related to biomedical science, but a new 2022 paper by Risi and coauthors provides some evidence that this isn’t restricted to just that context. Risi et al. (2022) look at the influence of gender on research topics in history by analyzing a sample of 10,000+ articles from major US history journals over 1951-2014. They use natural language processing algorithms to extract from this sample 90 different “topics”, where topics are defined as sets of words that are usually found together. Once topics are assigned to different papers, it becomes possible to tally up the genders of the authors of each paper to see if topics differ in how much they are studied by men and women. As indicated in the table below, there are some considerable differences across topics. From Risi et al. (2022) Over 1951-2014, women substantially outnumber men in the study of not just the “women and gender” topic, but also “family”, “body history”, and even “consumption and consumerism.” As “Gender and What Gets Researched” points out, we have to be careful in how we analyze data like this; it could also be that differences in the topics favored by men and women does not stem from different preferences, but that various barriers prevent women from working on preferred topics. But “Gender and What Gets Researched” also argues that as the share of women in a field rises, the field more broadly begins to reflect their (initially distinctive) concerns. For example: The left figure below tracks the Jensen-Shannon distance between the topics covered by men and women in history articles. This is an index that measures the difference between two statistical distributions; in this case, the distribution of men and women among the 90 different topics that were identified by Risi and coauthors’ natural language processing algorithms. As this index falls, the difference between these distributions is narrowing; knowing someone’s gender is increasingly less useful for predicting what topics they work on. Meanwhile, at right below, we can see the rise of women in the field of history. As with patents, as more women enter the field, the dissimilarity of the topics studied appears to be dropping. From Risi et al. (2022) That said, while this is consistent with the idea that the ideas and perspectives of women have become mainstreamed, it is also possible that the Jensen-Shannon Distance fell merely because women came to study the same subjects as men, not because men began to do research in topics that used to be distinctive to women. However, Rishi et al. show the share of articles mentioning words like “women” or “gender” has grown substantially over the 1951-2014, whether the authors are men or women, and that these terms are less and less confined to a small niche subset. That suggests the gender-difference between topics is falling at least partially because men are taking up the topics that used to be distinctive to women. Read the whole thing for a lot more discussion. Read the whole thing The Adjacent Knowledge of Teammates Adjacent Knowledge is Useful looks at three different setting that let us say something about what kind of knowledge is most useful - knowledge that’s really close, really far, or somewhere in between. One of those setting was an experiment where life scientists attended a symposium where they were divided up into rooms and then talked about research with a random subset of people. Among other things, the experiment monitored which of these randomized conversations resulted in subsequent collaborations. The authors found collaborations were most likely to emerge among life scientists who worked on some overlapping topics, but not a lot. The updated article discusses a subsequent article that largely confirmed that finding, in a broader non-experimental study, again using natural language techniques to extract topics from text. A 2021 paper by Smith, Vacca, Krenz, and McCarty largely confirms Lane and coauthors work in a broader non-experimental context. Smith and coauthors look at what factors are correlated with researchers choosing to begin collaborating with each other during 2015-2018 for a sample of 3400 researchers at the University of Florida (all the faculty they could match to enough data to run their analysis). Specifically, they are interested in seeing whether faculty are more likely to begin collaborating if they work on more similar or dissimilar topics. Doing so requires a measure of how similar is the research expertise of different faculty at the University of Florida. They use a text analysis approach, based on the abstracts of the 14,000+ articles authored by faculty at the university in the three years prior to 2015. Specifically, they use an algorithm to create 5,000 different topics, each of which is defined by a cluster of words that are commonly used together (where more unusual words count for ...

Like the rest of New Things Under the Sun, this article will be updated as the state of the academic literature evolves; you can read the latest version here. Note: An audio version of New Things Under the Sun is now available on all major podcast platforms. Apple, Spotify, Google, Amazon, Stitcher Think of new technologies as proceeding through a set of stages: Basic scientific research that explores phenomena Applied research to better understand how to harness certain phenomena Technology development to capture and orchestrate phenomena for a purpose Marketing and diffusion of the new technology The real world can be more complicated with back-and-forth interplay between the stages, but this is a fine place to start.1 If you want to shape the direction of technology, you can intervene early in this process and try to push the kinds of technology you want onto the market, by subsidizing research.2 Or you can intervene at the end of the process and try to pull the kinds of technology you want into existence by shaping how markets will receive different kinds of technology. One specific context where we have some really nice evidence about the efficacy of pull policies is the automobile market. Making fuel more expensive or just flat out mandating carmakers meet certain emissions standards seems to pretty reliably nudge automakers into developing cleaner and more fuel efficient vehicles. We’ve got two complementary lines of evidence here: patents and measures of progress in fuel economy. In this post, first I’ll go over the evidence, and then I’ll talk a bit what I think we should take away from it. In my view, we have strong evidence that pull policies work well for incremental progress, but the case for their efficacy at promoting radical innovation is a lot shakier. Share Patents, Progress, and Pull Policies One pull policy is a tax on undesirable technologies, since, all else equal, that makes the taxed technology less profitable to develop and alternatives more profitable to develop. A carbon tax is the most famous example of this kind of policy. Aghion et al. (2016) are interested in how a carbon tax might change innovation in the auto sector, but given how rarely anyone actually tries to implement a carbon tax, they can’t directly study the question. Instead, they do the next best thing. From the perspective of a carmaker, one of the main effects of a carbon tax is to raise the price of fuel. So how do carmakers respond to higher fuel prices? To answer that question, they need a way to measure innovation. More specifically, they want to measure the kind of innovation a firm decides to do: do carmakers focus on clean technology (electric, hydrogen fuel cell, and hybrid vehicle) or conventional fossil fuel innovation? Patents are a useful dataset for this kind of problem, since they are correlated with inventive effort and can be easily categorized into different kinds of technology. One problem though is that patents vary tremendously in how valuable they are. Some are very important, but a lot are junk. So Aghion and coauthors focus on the subset of patents for which the patent-holder sought patent protection in three big markets: the USA, the European Union, and Japan. Since it’s costly to apply for a patent in each market, doing so in all these markets is a signal that the inventor thinks the patented invention is sufficiently valuable to be worth protecting in multiple large markets. So in this paper, you can think of them measuring innovation by counting the number of valuable patents for different kinds of automobile technology. In an ideal setting, if we really wanted to assess the impact of fuel prices on the innovation decisions of carmakers, we would want to randomly assign some carmakers to face higher fuel prices than others. Then we could compare the subsequent patenting behavior across groups facing different fuel prices. And if we wanted to establish this robustly, we would want to do this kind of experiment many times. We can’t do that. But Aghion and coauthors do something that gets you closer to this ideal. The price of fuel varies a lot from year-to-year, thanks to fluctuations in the price of oil (see left figure below), but it also varies a lot from country-to-country, because countries vary substantially in the size of their taxes on fuel (see right figure below). From Aghion et al. (2016) Moreover, carmakers typically sell to multiple countries, but have different footprints in different countries. Aghion and coauthors reason that carmakers are more sensitive to (tax-inclusive) fuel prices in the countries where they have a larger share of their total sales. For example, in the figure above it’s clear that the UK raised taxes pretty substantially over the 1990s, while taxes remained flat in the USA. In other words, if we have two carmakers, one with most of its sales in the USA and some in the UK, and another with most of its sales in the UK rather than the USA, then these carmakers are effectively facing different fuel prices. The carmaker selling primarily to the UK sees an increase in effective fuel prices, and we can compare their behavior to the one selling primarily in the USA. For every carmaker, Aghion and coauthors construct an “effective” fuel price that is specific to that carmaker, by weighting the fuel price in each country by the carmaker’s exposure to that country. They estimate this exposure from the share of patents the carmaker seeks protection for in that country over 1965-1985, because generally you don’t bother seeking patent protection in countries where you don’t plan to operate in the future. They then look to see how the patents of carmakers differ in the subsequent 20 years (1985-2005) as each carmaker faces a different effective fuel price. We can then compare the behavior of firms that were established in markets that went on to have higher fuel prices to the behavior of firms that were established in markets that went on to have lower fuel prices. (Note that they estimate the markets where a firm is established over 1965-1985, but look at the effect of fuel prices over 1985-2005; this prevents their results from being driven by innovative fuel efficient companies entering markets when they raise taxes, or from their measure of exposure to different markets from being whipped around by subsequent patenting activity) Aghion and coauthors find fuel prices exert a powerful impact on innovation. A 10% increase in the effective price of fuel (that a specific carmaker is exposed to) is associated with roughly 5% fewer patents of the conventional “fossil fuel” type, and a 10% increase in clean energy patents. Rozendaal and Vollebergh (2021) adapt this strategy to study the impact of emissions standards on auto innovation (in addition to fuel prices). Emissions standards are essentially a requirement that a carmaker’s average CO2 emissions per mile fall below some target by some date. It’s not actually quite that simple; but that’s the gist of the idea. Just as fuel prices differ across time and space, so to do regulatory standards. And just as a carmaker is more likely to care about the fuel prices in markets where it has a lot of sales, so too is a carmaker more likely to care about the emissions standards of markets where they have a lot of sales. Rozendaal and Vollebergh make one of those kinds of observations that is obvious in retrospect but which some previous papers apparently missed. In terms of its impact on the rate and direction of innovation, what matters is not whether a country has an emissions target, or even if this target is high or low. What matters is (1) how high or low is this target relative to today’s average emissions and (2) how long do carmakers have to meet the target? If the standard is high, but you’ve already cleared it, then even though it’s high it imposes no extra incentive to innovate. On the other hand, if the standard is high and you have not met it yet, but actually have a long way to go to meet it, then it matters whether you’ve got ten years or one year to get there. If you don’t account for this kind of thing, it might look like standards don’t have much of an impact on innovation. Rozendaal and Vollebergh construct a measure of standards that takes all this into account: it’s basically the difference between the average emissions of a country and the target, divided by the number of years left to meet the target. When the number is large, it means the average car in the country has a long way to go before it meets the target, and not a lot of time to get there. Here’s how their measure looks for the big three markets. From Rozendaal and Vollebergh (2021) As with Aghion and coauthors, Rozendaal and Vollebergh construct estimates of each carmaker’s exposure to these three major markets, as of the year 2000. Those heavily exposed to Japan, for example, faced stronger incentives to innovate in the 2000s, compared to those heavily exposed to US and EU markets. But after 2010, the situation has largely reversed. Again, Rozendaal and Vollebergh are going to look at valuable patenting of clean and dirty technology in response to these measures of emission standards stringency (in addition to fuel prices). And they find these pull policies work. A 10% increase in the stringency standards is associated with 2% more clean patents. Also importantly, Rozendaal and Vollebergh confirm Aghion and coauthor’s finding that fuel prices matter, albeit the strength of the relationship is weaker than Aghion and coauthors find. This might be because they are looking at a very different time frame, 2000-2016 compared to 1985-2005. What I like about these studies is that they have thousands of different inventive entities, and each of these entities is, at least in principle, facing a “pull policy”of a different strength (based on the mix of markets they operate in). This lets you estimate pretty precisely how effect...

Gratitude is an efficient way to increase the appreciation we have for the things that we could otherwise take for granted. Practising gratitude might make us feel more thankful for the circumstances we find ourselves in, such as where we live, the work we do, the people we have in our lives, and the gifts we receive.  However, things are not that simple. Although practising gratitude is generally seen as a positive practice, forcing gratitude could lead to what is known as gratitude traps. These traps could have a detrimental impact on your wellbeing, especially if artificially induced positivity causes you to deny yourself from experiencing a full spectrum of emotions. The pitfalls of gratitude Practising gratitude consists in finding ways to appreciate experiences that are valuable or meaningful to you. This might include feeling thankful for a job opportunity that arises, appreciating someone else cooking a meal for you, or the relief of commuting to work without hitting rush hour. Many psychologists agree that practising gratitude can foster positive feelings which will boost our sense of wellbeing. But recent research has revealed that looking on the bright side can also have its pitfalls. If you feel that you should be thankful by default, you may be at risk of others exploiting your grateful nature. Psychologist Alex Mathew Wood and colleagues have written about the dark side of gratitude. They have raised concerns that the benefits of positive, personal gratitude can be outweighed by the exploitative behaviour of others. For example, if you feel that you should be grateful to your boss for giving you a job and allowing you to support yourself financially, this emotional reasoning may prevent you from even contemplating that their controlling nature is concerning. While you focus on trying to be thankful, you may become blind to the ways in which they harm you. Dr Ruida Zhu and colleagues reported that gratitude could also lead to what is called moral violation: those who are grateful to someone may be more “willing to violate the norms of honesty and justice”. In the above example, being grateful to your boss could increase your willingness to lie for them if it might protect them or the business from harm. Furthermore, Dr Inna Ksenofontov and Dr Julia Becker found that when low-power group members are grateful to high-power group members, the power hierarchy becomes solidified. If someone in a high-power group behaves badly but then offers thanks to someone with less power, this expression of gratitude pacifies those with less power. The least powerful are then less likely to protest their poor treatment. In this case, the expression of gratitude leads to the justification of bad behaviour for those who hold the power. The three types of gratitude traps Gratitude traps come in many forms and shapes, but there are three big categories of common ways they can occur.  1. Inauthentic gratitude. Inauthentic gratitude describes the display or feeling of gratitude for something that you do not truly feel grateful for. If you feel that you should be grateful for a gift that was thoughtlessly chosen, you risk belittling your own sense of self-worth. Subjectively accepting that you are worthy of someone’s time and effort will improve your sense of wellbeing more than forcing feelings of gratitude will.  2. Shame-based gratitude. This type of gratitude trap occurs when we feel that we ought to be grateful for something. For example, you may tell yourself that you should feel grateful that you have a job and therefore a steady income. However, if you are facing workplace bullying or feel chronically stressed, focusing on the positives does not leave room for interventions to improve the situation or your personal wellbeing. 3. Comparative gratitude. By comparing ourselves to others, we attempt to force gratitude. By internalising statements such as “it could be worse”, or “at least I still have a roof over my head” we forget about the satisfaction we have in life and instead focus on feeling gratitude for not being in an even less desirable situation. Comparative gratitude is an attempt to make us feel better about ourselves, but it does not help us to see the positives in our lives. How to avoid gratitude traps Gratitude has many benefits, but you want to avoid falling prey to its potential pitfalls. If you use gratitude to boost your wellbeing, it is important to take steps to avoid gratitude traps that could have a detrimental impact.  First, embrace a variety of emotions. Throughout life, it is natural to experience a full range of emotions, from happiness to grief and even to despair. If we try to look only for the positive in every situation, we may be forcing ourselves to swallow our true feelings. Leaving such emotions unresolved can negatively impact our mental health.  Dr Jainish Patel and Dr Prittesh Patel recommend exploring one’s true feelings to help regulate emotions for greater emotional stability. They reported that “expressing one’s true emotions is crucial to physical health, mental health, and general well being, while a reliance on concealment gives rise to a barrier to good health.”  Then, Clinical psychologist Dr Ellen Kenner recommends finding the root of our “unearned guilt”. This is the guilt that you feel when someone else tries to induce it in you, rather than guilt for something you have done and want to make amends for. Dr Kenner explains that self-reflection and questioning the motivation behind your gratitude can help to reveal unearned guilt.  You should also question the source of your gratitude. As we have seen earlier, gratitude can increase the risk of exploitation or moral violations. If you are attempting to feel grateful for something, question your motivation for doing so. If you do not truly feel grateful for the gesture, gift or experience, or your gratitude is based on obligation, guilt or shame, then your gratitude may be misplaced. Recognising when your gratitude is misplaced is already a powerful first step in managing gratitude traps. However, if gratitude traps are prominent within your life, you may benefit from cognitive restructuring. Research suggests that those who emotionally involve themselves in the honest expression of their feelings will reap long term physical and mental benefits, and those who enlist the help of a counsellor or therapist in exploring emotional or distressing events will benefit the most. Practising gratitude has become a popular way to develop a deeper appreciation of your life. However, gratitude traps can negatively impact your mental health. If you feel grateful, or think you should feel grateful for something, it is important to critically investigate whether the gratitude is well-founded. The wide range of human emotions should be embraced, and frustration, anger, and upset should not be stifled in the pursuit of thankfulness. If your gratitude is inauthentic or based on comparison or shame, then it is wise to seek guidance from an expert in cognitive restructuring. The post Gratitude traps: why we should be critical of gratefulness appeared first on Ness Labs.

Welcome to this edition of our Tools for Thought series, where we interview founders on a mission to help make the most of our minds. Jennifer Smith is the founder of Scribe, a tool to help knowledge workers share their specialized know-how. Her goal is to make it as easy as possible for teams to increase their collective intelligence. In this interview, we talked about enabling everyday experts to scale their knowledge, the power of peer-to-peer learning, the biggest productivity sink for knowledge workers, how knowledge-sharing results in big efficiency gains, how staying agile is crucial in our rapidly changing world, and much more. Enjoy the read! Hi Jennifer, thank you so much for agreeing to this interview. One of your mottos is that “everyone is an expert” — what do you mean by that? I truly believe everyone is an expert. Everyone knows how to do something special, something that adds value in some way.  Work is now more specialized than ever before. There are more software tools at this moment than at any point in history; digital workflows are the most complex they’ve ever been, and no one person can ever know everything. Rather, you’ve now got a phenomenon where, with specialization, everyone is now an expert in something more specific. Whether that’s how to generate a report in QuickBooks, or configure a Shopify account, or track prospects in Salesforce — everyone has some kind of special know-how. With Scribe, we think about how to make it really easy for anyone to share what they know how to do. We always say: “You’ve done the hard part already. You know how to do something special, valuable, and unique. We’re just here to make it easy and automatic for you to share what you know how to do.” Scribe will just watch you work and automatically generate step-by-step tutorials that you can share with others to show them what you know how to do. Our hope is that this enables “everyday experts” to scale their knowledge — and to get recognized for the cool things they already know how to do! Knowledge workers spend thousands of hours documenting their work and sharing what they know with others. What makes Scribe different from other approaches to sharing a process or workflow? You’re a knowledge worker and you have some specialized know-how. If you want to share that with someone else right now — a colleague, a customer, or your community — you only have two options: either take precious time away from doing actual work to write down what you know how to do, maybe in a Google Doc, or an email, or copy-pasting screenshots, or explain it to someone else who does the first option for you. Both are really manual and time-intensive, and the information you create can become outdated pretty quickly. With Scribe, all you have to do is hit the “start” button, and do the work you would normally do.  Let’s say you want to explain to someone how to generate an invoice in your CRM. You would hit start, and just generate the invoice. When you’re done, you hit “stop.” Scribe will immediately and automatically generate a step-by-step, written tutorial with screenshots showing exactly how to generate an invoice. You can share that Scribe with someone who can now replicate that process themselves; or save it for later whenever someone has a similar question in the future. You’ve magically created documentation without actually doing any additional work. You didn’t have to take time away from doing productive output to explain to someone else how to do something. We really focused on how to make it as simple, easy, and fast as possible. We look at the time it takes someone from the moment they first land on our website to when they’ve created and shared their first Scribe, and it’s under four minutes. We’re focused on how to help people get time back in their day, so we didn’t want to design a product that had a learning curve. We all have too many tools where we have to invest time to learn how to use them. With Scribe, we’re constantly trying to push the time-to-value to be nearly instantaneous. Four minutes from signing up to creating their first Scribe is impressive. Was there an “aha” moment that inspired you to build Scribe? I have been obsessed with processes and efficiency for pretty much my whole life. I’m always trying to see if there’s a better, faster way to do something. I spent seven years as a consultant at McKinsey & Company, mostly in the Org & Operations practices, which meant eight hours a day in ops centers documenting processes. I quickly learned the name of the game was to find the best agent, sit next to them, and just ask them what they did differently. And they would tell me! “Oh, I was trained to do it this way but I found these thirty shortcuts.” And we would dutifully write that up in powerpoint and sell that back to our clients. But I always thought to myself — if these people had just had a platform to share what they had figured out how to do, they could have a really big impact on their ops center. They didn’t need me and my team saying it for them. This always kind of nagged at me, but I figured it was a problem for someone else to solve some day. Fast forward a decade and I’m working at Greylock Partners on Sand Hill Road. I talked to 1200 CXOs of Fortune 500 companies to understand what they wanted and where they saw gaps. And to my surprise, I realized that the state-of-the-art hadn’t really evolved. If you wanted to improve your operations, you still had some version of a 28-year-old Jennifer with her Lenovo ThinkPad running around manually documenting processes to find best practices. Sure, maybe it’s someone in the company and they’re using a wiki instead, but the task is just the same: highly manual and not scalable. And that was crazy to me. So much technological advancement in the world, and we still had not solved something that is so core, so fundamental, to how millions of people work every day. So you decided to solve that problem. How does Scribe work exactly? The concept behind Scribe is simple: what if software could watch you do a task, and automatically generate a step-by-step guide on how to do that task? It’s almost like the documentation is just digital exhaust — a by-product of you doing your normal course of work.  As I said, when you go to do a task, you hit “start” and just do the task. When you are done, you click “stop.” And Scribe will immediately and automatically generate a step-by-step, written guide with screenshots showing exactly how to do that task. You have a bunch of advanced options for how to edit the Scribe, but the point is, you don’t really need to — all the info someone would need to replicate that task is automatically contained in that Scribe. And then you have several options for how to share that Scribe — whether it’s one-click sharing a persistent link, downloading a PDF, or embedding the Scribe in any of hundreds of your favorite tools. The average Scribe takes 54 seconds to create.  It’s designed to have nearly no learning curve at all. Anyone can just get started and create their first Scribe in a matter of seconds. We really focused on how we can take the friction down to nearly zero, for nearly anyone, regardless of digital literacy. This seems like an amazing way to encourage peer-to-peer learning. What are some of the benefits teams have experienced? When you think of learning in companies traditionally, people often think of formal training programs —  maybe one you attended when you first onboarded or as part of ongoing professional development. But most of what you need to know to actually be productive every day is learned on the job, mainly by observing your peers and asking them questions about how things are done. This happens very informally today. You shadow a colleague when you first start, you pop your head over the proverbial cubicle to ask a question, or you call a teammate to ask them to walk you through how to do something. This is often the most effective kind of learning, but it is not very scalable. With Scribe, you can capture what your best people know how to do — once — and share it with anyone, in perpetuity. If a colleague has learned a new tool, or found a better way to do something, they can Scribe it and share it with their team; it scales their knowledge and up-levels their team, but in a way that takes no additional time for them. In this way, you’re able to tap into the best knowledge within your organization and surface it to anyone who needs it, at any time — with big productivity and efficiency gains that cost little to no time to generate. Staying agile is crucial in our rapidly changing world. How does Scribe help teams quickly adapt to change? Research from McKinsey estimates knowledge workers spend about 20% of their time searching for information they need to do their job. This is a huge productivity sink. Layer on to this the Great Resignation, more people changing jobs, companies switching to a remote environment, and you’ve got a lot of wasted time — not to mention frustration — trying to find out how work gets done. With Scribe, you now have all of the process knowledge for how work gets done captured in a central repository.  Now, rather than having to track down the right person who has the info you need, ask them to explain it to you, and wait for them to write it up or call you back — you can simply find what you need in a matter of seconds. New practices, or best practices, can spread much more quickly within a team. That makes sense. What kind of people use Scribe? Anyone who has to explain “how-to” — to a colleague, a customer, a friend, or a community.  So, in short, a lot of different kinds of people. Pretty commonly, this looks like customer-facing teams, be they sales, support, or customer success, who want to show customers how to use a product or complete a process; technology teams who are rolling out a new tool to colleagues; or operations te...

Welcome to this edition of our interview series, where we meet with founders on a mission to help live more fulfilling personal and professional lives. Zach Hamed and Matthew Achariam are the co-founders of Clay, a beautiful and private home for all your relationships which is populated using your calendar and social history. As you know, at Ness Labs, we care a lot about nurturing authentic relationships and building thoughtful learning communities, so it was fascinating to learn about Clay’s approach to helping us remember who you’ve met and what matters to them. In this interview, we talked about how we rely on relationships to make sense and meaning of the world, the power of serendipity, the problem with social media feeds, how the team at Clay designed a holistic and cohesive solution for thoughtful relationship management, and much more. Enjoy the read! P.S. Zach and Matthew are kindly offering two months of free membership to Clay to Ness Labs readers. Just use this link to unlock this special offer. Hi Matt and Zach, thank you so much for agreeing to this interview. Despite being more connected than ever, we still struggle to nurture our relationships with others. Why do you think that’s the case? Thanks for having us! We’re longtime readers and fans of Ness Labs, so we’re really excited to be here. It’s a great question. We talk about this exact tension constantly at Clay. How do we take these incredibly important things — relationships — and give them the real care and attention they deserve? Because we know that relationships are important. And they’ve only gotten more important in the past few years as everyone has been spread out and often isolated.  Still, people feel like they’re falling behind with their friendships, professional relationships, both online and offline — and there’s data to back that up. The average professional meets 3500 people over the course of their professional career, and that’s only increasing. Our friends and coworkers are changing careers more often than older generations. And so we have more relationships in more contexts — with a lot of relational turnover. So it’s not surprising that people spend 63% less time with coworkers in 2012 than they did in the mid-1970s, and 49% of professionals say it’s hard to keep in touch with their network. The tools and systems we use to connect with others have increased from in-person meetings, phone calls, and text messages to an arsenal of social platforms and apps where everyone we know has equivalent standing based on a ‘follow’. The end result is that now you’re wading through engagement pictures of someone that you aren’t sure how you met — right next to updates from really important relationships. Those changes have only been exacerbated by the pandemic. People met 20% fewer people at work over the past two years, and the time spent on personal relationships has also dropped significantly since people have been unable to meet in social settings.  Based on personal experiences and data-driven research studies, it’s becoming increasingly apparent that we’re devoting less time to more relationships, and we’re feeling worse about it. Our networks are larger and more spread out than they’ve been. So, people feel spread thinly because they are! Yet, paradoxically, relationships are more important than they’ve ever been, too. As the world of possible jobs, entertainment, ideas, etc. gets larger, our relationships act as guides and curators to what we should pursue and how we should process our life.   We rely on relationships to make sense and meaning of the world, to find opportunities for work and recreation, to examine ideas. Even though relationships are more important than ever, we are using tools which are not specifically designed to nurture relationships in the current ecosystem where relationships live. And so we built Clay to be a modern tool that can help people feel thoughtful with the people in their life, without feeling overwhelmed or stressed. I think that’s a struggle everyone can relate to. What about you… What struggles did you face in maintaining your relationships before you built Clay? We built Clay out of a deeply personal need. We’re both immigrants or first-generation, and our relationships were the most important things we had growing up. Our jobs, our internships, our biggest opportunities in high school, college, and beyond — they all came from people. Relationships formed the center of our lives, but we realized they didn’t really have a home. They were all over the place: scattered in notes, apps, text messages, social media, email, different jobs, or company accounts. We tried everything. We started with a spreadsheet, with columns for names and locations and tags. We signed up for countless tools. And they each had their benefits. But over time they were acquired, or shut down, or went dormant. Matt and I, at various points, built solutions for ourselves, separately, out of pure frustration. We just wanted a home for our people. Evernote and Apple Notes were our solutions at the time, but we also coded our own version with a local database and a simple frontend. Lots of people try building their own solution for this problem, only to find out that (1) it’s a *lot* of work, and (2) your homegrown solution grows stale almost instantly when you start adding info to it manually. People move locations, APIs become deprecated, and over time things become messier and messier until you no longer check it. So after years of thinking “there has to be a better way!”, we talked to hundreds of professionals across myriad industries, and we realized that this is a fairly universal problem with a million different solutions. It’s a very personal problem to a lot of people. For some, it could be a physical notepad where they write down quick notes or birthdays, very similar to an old-school Rolodex. For others, it’s digital notes apps. Some use a spreadsheet and a few use actual CRMs like Salesforce. Everybody sort of gravitated towards the solutions that resonated with them or the tools that they use in their professional life and sort of tried to shoehorn other types of relationships into them.  And so we said, let’s carefully design a product that pays attention to the nuances of relationships and helps people be more thoughtful with the many different types of people they interact with, personally and professionally. And that’s how Clay was born. I've had "make a personal CRM" on my list since the April, but never did and and boom! I'm scrolling Twitter and learn about @ClayHQ ! Life changing — cyrina (@cyrinathomas) July 16, 2021 Scratching your own itch is often a great way to get started, and it looks like you’re not the only ones feeling that itch. There has been a surge in personal CRM tools recently. What makes Clay different from other solutions? We’ve built Clay around a system of values and principles for deepening relationships that we designed from countless hours of research, interviews, and experimentation. Because we established those values and the method first, and then built out the features that naturally flowed from them, Clay actually helps you be more thoughtful. It feels holistic and cohesive.  In addition to the system that our members pick up by using Clay, there are a few more reasons why they love using the software. First, after you connect your email, calendar, Twitter, LinkedIn, and iMessage, Clay does a ton of work automatically for you. There’s no data entry or manual upload that other software tools make you go through.  If you ever need help, or need us to import something for you, we’re just an email away. We do 1:1 onboarding calls to answer any questions, from how to set up Clay to power user pro-tips and best practices. And we ship new features and improvements multiple times a week, to the point where we’ve pushed a feature in the afternoon for an onboarding call we had in the morning.  Clay is also beautifully designed. The small interactions that save time and make things easier matter, and we intentionally design every last detail. Our members tell us Clay is the most stunning tool they use daily and that we’re incredibly responsive when they have questions or feature requests. We care. And that’s increasingly rare in tech and software nowadays. Our goal is to help you think about that person that you may have forgotten. To remember that birthday. To reconnect if it’s been a few months. Our entire team is singularly focused on that, and the product is tailor-made to make that easier. And we have a sustainable business model so we can focus on improving that over time. lastly, i personally have really enjoyed refactoring my own work style over the past year to 100% work from home. i added @ClayHQ and @sunsamaHQ to my daily routine. these apps genuinely brought organization and structure to my work and personal life without a huge effort. — spencer (@skerbz) December 9, 2021 We tend to appreciate thoughtfulness even more when we don’t expect it. How does Clay help cultivate serendipity in its users’ relationships? We’re big believers in serendipity — unexpectedly running into someone you needed or a chance encounter with someone new that blossoms into a lifelong bond. Clay is designed to amplify that by resurfacing people, notes, and updates. It’s baked into every part of the product. Social media feeds, like LinkedIn, Facebook, and Twitter, are presented in order of what those companies think will engage best — what will cause you to like or comment. But that content is often from influencers or people you barely know, not people you actually care about.  So when designing our Explore view, we decided to focus on content that most people want to pay attention to, but isn’t easy to find for everyone you’ve ever met.  If you’ve ever been reading a blogpost or magazine article and come across the name of someone you know, you know ho...

Do you tend to focus on negative details? Mental filtering is a cognitive distortion that leads us to magnify the negative details of a situation, while filtering out the positives. Also known as selective abstraction, this bias for dwelling on your shortcomings could lead you to focus on one piece of negative feedback, while disregarding or disbelieving the ten other positive comments received.  The problem with mental filtering The psychiatrist Aaron T. Beck frequently referred to mental filtering during his work in cognitive therapy in the 1960s, when he found a link between focusing on negative details and both depression and anxiety, and recent research has backed up Beck’s findings. Dr Carl Weems and colleagues at the University of New Orleans described mental filtering as “focusing only on the negative aspects of an event, such as I ruined the whole recital because of that one mistake.” This blinkered thinking was found to be strongly associated with anxiety and depression. Mental filtering also shares a close relationship with self-esteem. The more distorted our reasoning becomes, the less confidence we have in ourselves.  The following are common examples of negative filtering: Upon submitting a project for approval, the overwhelmingly positive feedback is quickly overshadowed by one piece of constructive criticism. This can lead you to believe that you are doing a poor job, even though this is not what you were told. A colleague fails to greet you when you walk past each other in the street. Rather than consider that they simply may not have seen you, you assume that they dislike you, or that you have done something to offend them. A friend does not wish you a happy birthday. You reason that they no longer value your friendship, rather than considering that their card may be delayed in the post. This can leave you feeling unnecessarily angry or upset. As you can see, mental filtering can have a detrimental impact on your self-confidence and personal growth. If the one piece of advice your boss gave you after a presentation led you to feel that you were no good at public speaking, then you may internalise that any future attempts will be a disaster. This vicious cycle can lead to intensification of anxiety and worsening of your mood. Furthermore, it will do little to improve how you feel about your next attempt at public speaking. Aaron T. Beck conducted interviews with patients who were moderately to severely depressed. He found that many of these patients had a distortion of reality and “a bias against themselves.” This led to “negative expectancies as to the probable success of anything they undertake, and a massive amount of self-criticism.” Some people use this self-criticism and negative self-talk to avoid disappointment when things do not go as well as they might like. However, this negative mindset can further compound low mood, and expecting failure may also stunt your personal growth. How to manage mental filtering To manage this cognitive distortion, you must consciously start to manage negative thought patterns so you can begin to see your efforts and achievements in a more positive light. First, recognise when mental filtering occurs. A key step to managing a cognitive distortion is to acknowledge its presence. Reflect on how you respond to life events, professional feedback, and social situations. If your glass tends to be half-empty, explore your feelings further by journaling, creating a log of voice notes, or using a habit tracker. Then, conduct a cost-benefit analysis. In psychology, a cost-benefit analysis is a technique used as part of cognitive behavioural therapy. It can be used to support you in challenging the patterns of thinking that have led you to focus on the negative elements of a situation. On a piece of paper, create two columns for costs and benefits. Think about whether mental filtering benefits you, as well as what it costs you. Write each point down in a column and assign it a value of importance from 1 to 10. It is likely that filtering costs you far more than it benefits you. The next step in the analysis is to think about alternative thought or behaviour patterns you could employ to see situations more positively. Finally, ask for objective opinions. Asking your friends or colleagues for an objective opinion on your performance or achievements is a good way to gauge your ability or progress. If you have become entrenched in negative self-talk, listen carefully to what others objectively report. Write down all of the positive opinions your friend or colleague shares, and focus on each one individually. Start forming positive habits and mindsets, and allow yourself to believe in your own ability, rather than focusing on the negatives. Remember that if you are prone to mental filtering and negative self-talk, you are more likely to focus on the negatives and ignore any positives of a situation. Challenging unhelpful thought patterns and becoming more objective can help to avoid the automatic descent into unwarranted negativity. Journaling and keeping an open mind when receiving feedback can help you recognise the positives. By avoiding mental filtering, you will be better equipped to mitigate the anxiety and low mood associated with any difficult challenges you may encounter in life. The post Mental filtering: when we focus on negative details appeared first on Ness Labs.

Self-love is seen by many as a futile, even narcissistic pursuit. With influencers urging you to love yourself without much substance to their advice, the concept of self-love may seem like an empty one. However, there is lots of scientific evidence suggesting that self-love can have a positive impact on your mental health, self-esteem, and overall life satisfaction. Modern society creates so much pressure on people — whether it’s pressure to achieve status, wealth, or beauty — that it can sometimes feel easier to focus on our failures and ignore the areas where we have grown. This strive for perfection can make us forget to take care of our basic needs, such as psychological safety, companionship, and personal creativity. Self-love is not selfish. Self-love is about acknowledging the need to take care of our needs, not our wants, and to work towards self-betterment instead of sacrificing our needs to prioritize the happiness of others. The self-positivity bias Nowadays, the definition of self-love has moved away from its traditional negative connotations such as narcissism and selfishness. It is seen as a positive psychology practice which can help people better manage their emotions and their mental health. As Jeffrey Borenstein, President of the Brain & Behavior Research Foundation, puts it: “Self-love is a state of appreciation for oneself that grows from actions that support our physical, psychological and spiritual growth. Self-love means having a high regard for your own well-being and happiness. Self-love means taking care of your own needs and not sacrificing your well-being to please others.” The scientific term for self-love is self-positivity bias, which is defined as the way people rate themselves as possessing more positive personality traits and displaying more positive behaviors than the average population. Cultivating this self-positivity bias has many evidence-based benefits. Eric Fields and Gina R. Kuperberg, both researchers from the Department of Psychology at Tufts University, explain that: “Positively biased self-views are argued to be a key component of healthy psychological functioning, influencing self-esteem, motivation, and determination. Indeed, a lack of a self-positivity bias (or even a self-negativity bias) may contribute to mood and anxiety disorder.” Here are some of the evidence-based benefits of self-love, or self-positivity bias: Better mental health More self-acceptance Higher self-esteem More motivation Stronger determination Increased self-awareness Less anxiety Better sleep The great news is that, even though it may be more difficult for some people compared to others, anyone can learn how to practice self-love. Five ways to practice self-love Fundamentally, self-love is mostly about managing our inner critic so we can develop a more nuanced view of our failures, and appreciate all our effort and personal growth in a kind, loving, and respectful way towards ourselves. Avoid negative self-talk. In her book, Dr. Kristin Neff asks: “What type of language do you use with yourself when you notice a flaw or make a mistake? Do you insult yourself or do you take a more kind and understanding tone? If you are highly self-critical, how does that make you feel inside?” Paying attention to how you internally talk to yourself is the most important step in learning how to cultivate self-love. Create personal rituals. The main difference between habits and rituals is how aware and intentional you are. Rituals are meaningful practices with a deep sense of purpose. Take time out of your busy day for self-care rituals, whether it’s giving love to your body by exercising, or giving love to your mind by meditating. Set healthy boundaries. It can be hard to love yourself when people around you are not respecting your time or acknowledging your value, whether at work or in your daily life. Getting out of the yes autopilot and learning to say no to protect your time and energy is a powerful way to practice self-love. Be compassionate towards yourself. Self-compassion is very similar to being compassionate towards other people. It consists in noticing that you are suffering and offering yourself understanding and kindness. As Dr. Kristin Neff puts it: “​​You may try to change in ways that allow you to be more healthy and happy, but this is done because you care about yourself, not because you are worthless or unacceptable as you are.” Make space for self-reflection. Sometimes, things don’t go to plan. Instead of blaming yourself, fail like a scientist so you can learn from these failures and use them as an opportunity for personal growth. Self-reflection can take the form of a journaling practice, a weekly review, or a regular meeting with a trusted friend to reflect on your recent experiences and challenges. As you can see, just a few changes can nurture more self-love. These changes can be as simple as appreciating our hard work and efforts without being overly or harshly critical, adopting healthy rituals, and setting healthy boundaries. Self-love can lead to better mental health, higher self-esteem, more motivation, and many other evidence-based benefits. It doesn’t need to be cheesy. Give it a try, and don’t forget about the power of self-reflection. Failure is not the end of the world, it’s an opportunity for learning and personal growth. The post The science of self-love: the evidence-based benefits of loving yourself appeared first on Ness Labs.

Welcome to this edition of our Tools for Thought series, where we interview founders on a mission to help us become more productive and more creative without sacrificing our mental health. Rishank Pandey is the co-founder of Workduck, a self-organizing work hub for modern product teams. Workduck helps you automate your tasks and augment your work so you can focus on what really matters: building great products. In this interview, we talked about the networked nature of product work, the difference between discovery work and delivery work, how to unlock serendipity in the product development process, accessing tacit team knowledge, the principles of building a modern agile workplace, and much more. Enjoy the read! Hi Rishank, thank you so much for agreeing to this interview. Let’s face it: building a product can be incredibly stressful — can you describe some of the challenges commonly faced by product teams?  Thanks a lot for the opportunity! That’s a deceptively simple but great question. The core problem is information overload. On average, a software team uses 106 different SaaS tools, a problem that some call “SaaS sprawl” — and that has been exacerbated by remote work. This results in tons of work metadata that’s spread haphazardly across sheets, emails, people’s brains, issue tickets, chat threads — all of this is hard to find and nearly impossible to keep in sync. Product work is highly networked and has lots of interconnected moving parts. What doesn’t help further is that there are currently almost no tools to help augment product-building workflows. For example, let’s say a product manager wants to keep their launch checklist updated, following some key insights derived from user research or feedback which itself is scattered across Slack threads, customer support tickets, and forums. Traditional automation tools built for sequential processes don’t cut it for such iterative and dynamic processes which are getting more intertwined by the day. So, a large part of a product person’s day is spent searching for information, attending additional meetings for context sharing, logging information into multiple tools, and the list goes on. These folks spend almost one third of their time looking for or recreating information that already exists! As you can see, product work largely consists of “discovery work” and “delivery work” — while delivery work has historically been the center of attention, tools that support discovery work and help to link the two together is where there is a huge void today. At Workduck, we think that writing is the way to most clearly bridge this gap. After all, every action that you perform can actually be expressed as a Note! And Words are the most persistent data structures! Continuously re-reading what you have written and editing it for better accuracy for as long as that piece is relevant to your team — even if it’s in months or years — is powerful, but sadly no platform promotes such behavior. Shared knowledge bases quickly become stale or irrelevant if they are not updated and connected to new ideas. This leads to the company depending on a few stakeholders to document all the relevant information the team needs. A good proxy to understand the scale of this problem is to look at the rise of ResearchOps and ProductOps roles who maintain this central source of truth for product teams. That’s fascinating. How is Workduck addressing those challenges? If I ask you to picture a productive person, what image springs into your mind? Probably someone who is waking up very early, a hacker who is gulping down vitamin shakes for breakfast and hustling all week long? The overarching problem that needs to be addressed to solve these broken product workflows is to work on changing this perception. At Workduck, we feel that the new productivity metric is not just time. Instead, empowered product teams — the ones who would strongly hate the term “feature factory” — rely on another productivity metric: “time to insight”, which entails smartly augmenting your present work and automating your common repetitive tasks across tools that traditionally have not talked to each other. The cornerstone to achieving this is unlocking serendipity in your work by consolidating all your knowledge that’s scattered and fragmented, and putting it to work for you. This quote by the ex-CEO of Hewlett-Packard, Lew Platt, is a good summary of what our vision is: “If HP knew what HP knows, we would be three times more productive.” Love this HP quote. More specifically, what are some of Workduck’s most unique features? Our guiding light is slightly contrarian. We feel your work should be independent of the tools you use as part of your “backend”, and we want to be the “middleware” that promotes this. After all, we are in the business of selling speed and digital fulfillment. Think of us as an embedded assistant in your workflow, something that’s at the back so you can be in your deep state of work — or “flow” — while we automate away all the complexities in the background. The less time you spend on our platform while we help augment your work, the more successful we get as a platform. So what does this translate to in terms of user journey? First, Workduck is keyboard optimized. We’ve designed it to help you work at the speed of thought. You press a key and the work gets done. That’s it. Then, we surface relevant insights. Haven’t we all secretly wanted the power of Google Photos but for our personal and professional knowledge? With Workduck, we get a step closer to that. For instance, you can get insights and additional context right when you’re in a stream of consciousness looking at an artifact that other members of your team might have shared a while ago. Finally, Workduck is bringing code like reusability to your workflows. We link artifacts together, sync data across tools together, and allow you to share these just like you share your notes. You can also experience the power of backlinks across your tools and daily workflows. It’s that simple. Personally, what’s your favorite feature? That would be quick capture, by a mile. You can essentially call a keyboard shortcut to smartly “capture” a piece of content from anywhere you are, whether it’s Gmail, Slack, Figma, Twitter, etc. and either turn it into a backlink, perform an action (like sending it to a particular tool, seeing related ideas and insights, adding context) or integrate it into a pre-built contextual workflow. This feature comes in very handy everyday when I’m in research mode. In the grander scheme of things, modern product work is largely defined by how fast you can get to qualitative insights or what might be more commonly referred to as “continuous discovery” work, and that’s where our quick capture feature shines. You are building Workduck for the “modern agile workplace”, what does that mean?  To be agile means being able to ship fast and learn iteratively. It’s a topic that’s been part of public discourse since ages.  But if one had to sum up the essence of an “agile workplace” across the different frameworks, debates and discussions, it is one that promotes constant experimentations and the need to periodically learn, unlearn and relearn everything. In principle, doing this has never been easier than today. But, ironically, it has become much harder to put into practice. That’s primarily because it’s very easy to zoom so much into iterative processes that you start to perceive events as linear in nature, losing out on its intertwined essence. Our brains, our interests, our potential and the project we work on have never been single-threaded nor confined to one unique stream of actions. Everything is networked. A modern agile workplace is one that promotes cross-functional collaboration in such a networked environment. A lot has been written and is being written on what this would entail process-wise. But sometimes it’s not so much about the very explicit things as much as the subtle, implicit things ingrained in every team in an org that creates the main difference.  Similarly, the solutions to making a team agile should not be defined by fixed processes, but rather as a series of checklists on how to make every function or role feel equally empowered within a team and make knowledge transfer among these as seamless as possible. Concise and updated documentation, being open to rapid experimentation, and knowing the difference between data-driven and data-dependent decisions are some of the key defining characteristics you’ll find in a modern agile workplace. The culmination of that is shipping delightful products truly fast. Talking about quickly shipping delightful products, Workduck is a big proponent of the low-code and no-code movement — why do you believe this is the future? This question reminds me of this one time Steve Jobs was asked about Visual Basic and the future of low-code applications in the Apple Developer Conference in 1997 and he responded saying: “The way you increase programmer productivity is not by increasing the lines of code per programmer per day — that doesn’t work. The way you increase programmer productivity is by eliminating the lines of code you have to write. The line of code that is the fastest to write, that never breaks, that doesn’t need maintenance is the line of code you never had to write. The goal is to eliminate 80% of the code that you have to write for your app.” So the discussions and buzz around low-code and no-code are not new. But recently there have been two macro-trends coming together that make us excited about low-code and no-code tools, and especially their applications in product workflows. Traditionally, no-code and low-code tools used to exist in silos to code-based and more intensive product development tools. This meant that as the actual use cases for them became more complex — which is to be expected as teams and their processes grow — the too...

When faced with a difficult decision, copying the actions of others can feel reassuring. We are social animals, and following the crowd can lead us to believe that we are benefitting from the wisdom of others. This may be especially true if we emulate the behaviour of those we consider to be authority figures. This informal fallacy of making choices that fit with those of our peers is known as social proof. While social proof can help us to make everyday decisions, it is vital to learn how to use it wisely rather than blindly following the crowd into what could turn out to be a bad choice. Seeking safety in numbers First coined by Robert Cialdini in 1984, social proof is also known as informational social influence. In his book Influence: Science and Practice, he discusses social proof as one of the influential psychological principles that persuade us to behave in certain ways. In ambiguous situations, decision making is made difficult by uncertainty regarding the potential outcomes, which may result in decision anxiety. Social proof therefore becomes a powerful influencer of decision making if we feel that others are better qualified to decide than we are. Researchers Elliot Aronson, Timothy Wilson and Robin Akert explain: “We conform because we believe that others’ interpretation of an ambiguous situation is more accurate than ours and will help us choose an appropriate course of action.” Safety in numbers, or reliance on the authority of others, can give us the courage to commit to a decision that we might otherwise struggle with. Social media influencers, for example, have an impressive impact on the buying decisions of their followers. Their perceived authority and belief in a product can persuade people who might otherwise have felt indifferent otherwise to make a purchase. The power of positive endorsement This impact has been corroborated in a study published in the Journal of Consumer Psychology. David Wooten and Americus Reed found that when consumers felt ambiguous about a product, positive endorsement from others was likely to sway their conclusion to align with others’ opinions. That’s why retailers use social proof to further encourage spending. Positive public reviews and ratings persuade us that a company or their product is trustworthy. Endorsements from specialists such as doctors or dentists also encourage consumers to choose a recommended product rather than one with no professional testimonial, even if the products are otherwise comparable. It’s interesting to note that we don’t tend to seek safety in any kind of numbers. When we see ourselves as similar to those around us, we are more likely to view their behaviour as correct, and therefore adopt it as our own. For instance, in a study of canned laughter, participants were found to “laugh longer and harder when they perceive the people laughing to be similar to themselves.” The dangers of relying on social proof Although there are many benefits of using social proof in decision making, especially as a quick rule of thumb for unimportant decisions, there are also dangers to be aware of. Herd mentality can prevent us from practising critical thinking and exploring new, innovative ideas. Even if an opinion is held by a large group of people, this does not necessarily make it correct. In argumentation theory, argumentum ad populum, Latin for “appeal to the people,” is the fallacious belief that when the majority approves of something, then it must be real or better. Following the crowd can lead people to make poor decisions that they would not have made without the encouragement obtained from social proof. For example, in Arizona, stealing of rare wood from the Arizona Petrified Forest only worsened when officials put up notices highlighting the high prevalence of theft. Rather than deterring theft, the notices seemed to act as social proof that stealing the rare wood could be justified, because many other people had already committed the act. In addition, social proof can cause you not only to act, but also to fail to act. Robert Cialdini reported in his book that upon witnessing the attack of a woman, a crowd of over thirty people failed to intervene to assist the victim. This inaction was thought to be the result of mass uncertainty. Because no-one had the confidence to intervene, everyone failed to act. How to wisely use social proof Many of us will have been persuaded by social proof, whether in making moral, social, professional, or purchasing decisions. When used carefully, you can unlock the benefits of social proof in everyday decision making, without succumbing to its pitfalls. Be mindful of influencers. Successful influencers are incredibly persuasive. When you see a product or argument being advertised, be aware of the underlying mechanism of influence at play rather than allowing yourself to blindly follow their lead. Reflect on whether you truly respect their opinion, or if you are being persuaded by powerful marketing. Interrogate your own beliefs. It can feel easier and quicker to adopt the beliefs of others, rather than interrogating your own opinion on a subject. Requesting advice or an opinion of a friend or colleague can be helpful, but the decision you later come to must also align with your personal values. Know when a decision matters. Decision anxiety can cause you to adopt someone else’s opinion to avoid making a decision for yourself. This can be helpful in avoiding becoming bogged down in minutiae. Choosing the same water bottle as a celebrity endorser will likely save you time, with minimal consequences if the bottle does not meet your expectations. However, moral decisions, choices that will affect your income or career, or expensive purchasing dilemmas should be made with more than just reliance on social proof.  If a decision really matters, you should ensure that you give it careful consideration. Social proof may help, but it should not be the deciding factor. Social proof can be a beneficial way to make decisions when you feel ambiguous about a choice or its outcome. Drawing wisdom from external sources can make a choice seem less risky or give us more conviction in our own actions. However, social proof can lead us to act in ways that do not align with our beliefs, and that morally may not be defensible. Learning when and how to use social proof to make decisions will allow you to benefit from the wisdom of others, without encountering the associated pitfalls. The post Social proof: is there always safety in numbers? appeared first on Ness Labs.

Like the rest of New Things Under the Sun, this article will be updated as the state of the academic literature evolves; you can read the latest version here. Note: An audio version of New Things Under the Sun is now available on all major podcast platforms. Apple, Spotify, Google, Amazon, Stitcher There’s this idea that technology is characterized by path dependency: once you start going down one technology trajectory, you kind of get locked in and it’s hard to switch to another, possibly better trajectory. That can happen for lots of reasons, but one possibility is that it’s something about the nature of knowledge itself. The more you know, the more you can learn: knowledge begets more knowledge. So whichever technology trajectory we start on becomes the one we know the most about, and therefore the one it makes most sense to stick with. One line of evidence about this comes from dynamics of patenting. You know what’s a pretty good predictor of patent activity in the future? Patent activity in the recent past. In this post, I want to see what we can learn from a literature that directly or indirectly looks at this dynamic. But while I think this line of evidence is useful, I want to be up front that it also has significant limitations. Most importantly, in this literature we almost never get anything like an experiment. Instead, we’re reading the tea leaves in observational data. Share Patent Stocks Specifically, we’re going to look at the conceptual category of a “patent stock” (also frequently called a “knowledge stock”). To illustrate just what a patent stock is, let’s start with a practical implementation of the notion in a paper. Aghion et al. (2016) is a paper interested in three kinds of technological progress among automobiles: clean tech (think electric cars, hydrogen fuel cells, and hybrid vehicles), fossil fuel technology (think internal combustion engine), and “grey” tech (think more fuel efficient fossil fuel technology). The paper measures innovation in these different technologies by counting valuable patents.1 There are about 2,500 companies and 1,000 individuals who hold one of these patents, and Aghion and coauthors construct three patent stocks for each of these inventive entities, one for each of these three flavors of technological progress. (Constructing patent stocks is hardly the only thing this paper does, but it’s what I’m focusing on today) Constructing a patent stock basically means adding up all the patents that an inventive entity has taken out in the past, giving more weight to the more recent patents. To be very explicit, suppose Ford Motor Company had a clean technology patent stock of 1,000 last year and obtains 250 new patents for clean technology this year. Then, to construct the patent stock for current year, we take last years’ patent stock, multiply it by 80%, and then add to that the number of new patents. So this year’s patent stock is 0.8 x 1000 + 250 = 1050. Suppose we get 150 patents next year. Then the patent stock next year is 0.8 x 1050 + 150 = 990. The exact value of 80% isn’t that important and people use different numbers, though always less than or equal to 100%. The key idea is it’s telling us, in a single number, something about the prior patent activity of the Ford Motor Company. Note that last year’s patents are worth less than this year’s patents (in this case, 80% as much). And since we apply the 80% discount each year, patents from two years ago are worth even less (80% x 80% = 64%). For the data that Aghion et al. (2016) have, for clean technology, a 10% increase in last year’s clean tech patent stock is associated with a 3% increase in this year’s new clean tech patents (for that firm). For fossil fuel technology, the link is even better: if a firm has a 10% higher patent stock in fossil fuels last year, that’s associated with 5% more new fossil fuel patents this year. This is quite a robust (though not universal) finding. Rozendaal and Vollebergh (2021) look at the same context (clean and dirty innovation in automobiles), but with a more recent slice of data (2000-2016, instead of Aghion and coauthors’ 1986-2005). In their sample, they find an even stronger link: roughly speaking, a 10% increase in last year’s patent stock is associated with a 10% increase in patenting this year. Noailly and Smeets (2015) do something similar for innovation in renewable energy and fossil fuel energy (not automobiles). They also find that firms sought many more clean or fossil fuel patents when last year’s patent stock (of the appropriate type) was higher. You can also go beyond firms and look at whole countries. Looking specifically at US patents, a famous 2002 paper by David Popp uses a slightly different approach to create patent stocks for 11 different technologies related to energy. He finds that a 10% increase in last year’s patent stock for a particular technology was associated with 7% more patents for that technology this year. And Porter and Stern (2000) compute patent stocks for 17 different OECD countries (looking at patents they seek in the USA, to hold consistent the definition of a patent). Again, a 10% increase in a country’s patent stock last year is associated with 8-11% more patents this year. This isn’t a universal finding. Lazkano, Nøstbakken, and Pelli (2017) look at innovation in renewable energy, conventional energy, and storage (battery) technology. Unlike the work discussed above, they typically find the opposite result: a higher patent stock for energy storage technology last year is associated with less energy storage patenting today. Similarly for renewable energy. That said, this paper is the outlier (I’ll return to it briefly later). For now, let’s proceed with the understanding that a positive link between yesterday’s patent stock and today’s patenting is a pretty robust correlation. But before jumping from a correlation to a conclusion, we need to think a bit harder about what’s really going on here. Why is there this correlation? (And if you feel like saying “patents don’t measure innovation!” I hear you, but bear with me for a bit) What’s Going on Under the Hood? One potential explanation is quite interesting. Suppose: Patent stocks measure how much knowledge we have about a technology When we have more knowledge, it’s easier to discover new things The new knowledge we discover gets added to our existing knowledge If this is what’s “really” going on, then it explains why we have a positive link between last year’s patent stock and this year’s patenting. Knowledge begets more knowledge! And this is especially true of more recent knowledge, for which we have not already wrung out all the possible implications (hence the higher weight on recent patents). If we really believe this story, we can even use the estimated statistical models to make neat little forecasts of how technologies will develop. For every year, we can use last year’s patent stock to predict how many new patents will be discovered. We then use that to predict what next year’s patent stock will be. Rinse and repeat. There’s also a policy implication. If we can temporarily accelerate the accumulation of knowledge in a field, it can pay huge dividends. That’s because the benefits will compound, since they’ll enable more knowledge creation next year, which will enable more knowledge creation in the following year and so on. Moreover, this model implies path dependence is a powerful force in technology. If one technology gets a minor head start, it might keep it’s lead for a very long time. In fact, if the relationship is strong enough (a 10% increase in the patent stock increases patenting by 10% or more), then all else equal a technology that is a bit behind can never catch up! But before we get too far ahead of ourselves, we need to strongly consider some other potentially important explanations. Let’s jettison the conceptual category “patent stock” for a minute. So far all we have really shown is that patenting in the recent past is correlated with patenting today. To think through why that might be the case, we need to think through what kinds of factors determine the number of patents in a given year (for a firm, technology, or country). Since I’m an economist, I’m going to divide the potential factors into two categories: supply and demand. Supply factors are anything that affects the cost of getting patents (where cost is broadly construed). Demand factors are anything that affects the value of getting a patent. If it patents get cheaper or more valuable, then we should expect inventors to seek more patents. And if the things that made them cheaper or more valuable persist over time, then patenting in the recent past predicts patenting today. Yes, it’s true that knowledge is one kind of things that makes it cheaper to discover new things and get patents. But many other non-knowledge factors might also be important. On the supply side, that might include things like more scientists/inventors; more physical capital (computers, laboratories, etc); improved access to financing; more patent lawyers; and so on. On the demand side that might include demand from consumers; new regulations favoring certain kinds of technology; or even just oddball idiosyncratic stuff like demand from a new CEO who thinks the firm should be patenting more of its existing inventions. If we get any of these factors, we’ll get more patenting today and tomorrow (if the factor sticks around), which will deliver the correlation that patenting today predicts patenting tomorrow. But unlike the interesting “knowledge begets knowledge” theory, this doesn’t necessarily have the same policy implications, nor does it necessarily mean we have strong path dependency in technologies. If these other factors are driving the correlation, then if we increase patenting by hiring more scientists, subsidizing R&D, passing some new regulation, or whatever, the boost in patenting will...