my critique of Manjoo’s article specifically and the ongoing privacy hysteria broadly is not simply about definitions or philosophy. It’s about fundamental assumptions. The default state of the Internet is the endless propagation and collection of data: you have to do work to not collect data on one hand, or leave a data trail on the other. This is the exact opposite of how things work in the physical world: there data collection is an explicit positive action, and anonymity the default.

I believe the privacy debate needs to be reset around these three assumptions: Accept that privacy online entails trade-offs; the corollary is that an absolutist approach to privacy is a surefire way to get policy wrong. Keep in mind that the widespread creation and spread of data is inherent to computers and the Internet, and that these qualities have positive as well as negative implications; be wary of what good ideas and positive outcomes are extinguished in the pursuit to stomp out the negative ones. Focus policy on the physical and digital divide. Our behavior online is one thing: we both benefit from the spread of data and should in turn be more wary of those implications. Making what is offline online is quite another.

One thing I learned long ago is that people who prioritize design, UI, and UX in the software they prefer can empathize with and understand the choices made by people who prioritize other factors (e.g. raw feature count, or the ability to tinker with their software at the system level, or software being free-of-charge). But it doesn’t work the other way: most people who prioritize other things can’t fathom why anyone cares deeply about design/UI/UX because they don’t perceive it. Thus they chalk up iOS and native Mac-app enthusiasm to being hypnotized by marketing, Pied Piper style.

Those who see and value the artistic value in software and interface design have overwhelmingly wound up on iOS; those who don’t have wound up on Android. Of course there are exceptions. Of course there are iOS users and developers who are envious of Android’s more open nature. Of course there are Android users and developers who do see how crude the UIs are for that platform’s best-of-breed apps. But we’re left with two entirely different ecosystems with entirely different cultural values — nothing like (to re-use my example from yesterday) the Coke-vs.-Pepsi state of affairs in console gaming platforms.

So when ex-Telltale Games designer and writer Sean Vanaman announced last month that the first game from Campo Santo, his new video game development studio, was "being both backed by and made in collaboration with the stupendous, stupidly-successful Mac utility software-cum-design studio slash app/t-shirt/engineering company Panic Inc. from Portland, Oregon," it wasn't expected, but it wasn't exactly surprising, either. It was, instead, the logical conclusion of years-long friendships and suddenly aligning desires.

"There's a weird confluence of things that have crisscrossed," he said. "One is that we're lucky in that Panic is the kind of company that has never been defined by a limited mission statement, or 'We're the network tool guys' or anything like that. I mean, we made a really popular mp3 player. Then we kind of fell into network tools and utilities, but we've always done goofy stuff like our icon changer and these shirts and all that other stuff. "I kind of love that we can build stuff, and the best reaction that we can get when we do a curveball like this is, 'That's totally weird, but also that totally makes sense for Panic.'"

"To me," Sasser said, "when you have actually good people who are more interested in making awesome things than obsessing over the business side of things or trying to squeeze every ounce of everything from everybody, then that stuff just goes easy. It's just fun. The feeling that you're left with is just excitement.

here are five large language model applications that I find intriguing: Intelligent automation starting with browsers but this feels like a step towards phenotropics Text generation when this unlocks new UIs like Word turning into Photoshop or something Human-machine interfaces because you can parse intent instead of nouns When meaning can be interfaced with programmatically and at ludicrous scale Anything that exploits the inhuman breadth of knowledge embedded in the model, because new knowledge is often the collision of previously separated old knowledge, and this has not been possible before.

Even if chatbots were to fix their accuracy issues, Google would still have a business model problem to contend with. The company makes money when people click ads next to search results, and it’s awkward to fit ads into conversational replies. Imagine receiving a response and then immediately getting pitched to go somewhere else — it feels slimy, and unhelpful. Google thus has little incentive to move us beyond traditional search, at least not in a paradigm-shifting way, until it figures out how to make the money aspect work. In the meantime, it’ll stick with the less impressive Google Assistant.

“Google doesn’t inherently want you, at an inherent level, to just get the answer to every problem. Because that might reduce the need to go click around the web, which would then reduce the need for us to go to Google.”

Web3 has largely been technology looking for problems to solve while generative AI has been about almost too many solutions created by technology which is evolving on a seemingly daily basis. As a result, web3 has thus far been evangelists trying to convince us to re-solve old problems with their new technology

We fully acknowledge that it’s hard to be confident in any predictions at the pace the field is moving. Right now, though, it seems we’re much more likely to see applications full of creative images created strictly by programmers than applications with human-designed art built strictly by creators.

Whenever Facebook changes its interface, it has an impact on how millions of people communicate. In this sense, user interfaces are cultural artefacts.

the concept of file folders and directories, essential to previous generations’ understanding of computers, is gibberish to many modern students.

be inspired by the untapped potential of human capabilities. Don't just extrapolate yesterday's technology and then cram people into it.

if you go into the Shanghai City Guide, it’s easy to put together a list of must-visit restaurants or family-friendly activities. Plus, not only is it easy to create bookmarks of places you want to save, but you can also browse other public bookmarks curated by creators and influencers, and then sort the bookmarks by location or distance. This type of bookmark discovery is a completely different use case than how we use Google Maps or Yelp today. Our Western location-based platforms use a manual, search-based process that primarily works for high-intent discovery. In contrast, thanks to the algorithms and user behavior on Douyin, the app can push new places to a user that he or she would never have thought to search for. Short video effectively enables the continuous discovery of the best places around you, and it gets better with every swipe as the platform better understands you and your interests.

Humor us for a moment and picture your favorite neighborhood restaurant. Ours is a corner spot in Fort Greene, Brooklyn. It has overflowing natural light, handmade textile seat cushions, a caramel wood grain throughout, and colorful ornaments dangling from the ceilings. Can you picture yours? Do you feel the warmth and spirit of the place?A Silicon Valley optimizer might say, “Well, they don’t brew their coffee at exactly 200 degrees. And the seats look a little ratty. And the ceiling ornaments don’t serve any function.”But we think that’s exactly the point. That these little, hand-crafted touches give our environment its humanity and spirit. In their absence, we’re left with something universal but utterly sterile — a space that may “perfectly” serve our functional needs, but leave our emotional needs in the lurch.

Operating systems were bubbly and evanescent, like nature. Apps were customizable, in every shape and size. And interfaces drew on real-life metaphors to help you understand them, integrating them effortlessly into your life.But as our everyday software tools and media became global for the first time, the hand of the artist gave way to the whims of the algorithm. And our software became one-size-fits-all in a world full of so many different people. All our opinions, beliefs, and ideas got averaged out — producing the least common denominator: endless sequels that everyone enjoys but no one truly loves.When our software optimizes for numbers alone — no matter the number — it appears doomed to lack a certain spirit, and a certain humanity.

In the end, we decided that we didn’t want to optimize for numbers at all. We wanted to optimize for feelings.While this may seem idealistic at best or naive at worst, the truth is that we already know how to do this. The most profound craftsmanship in our world across art, design, and media has long revolved around feelings.

When Olmstead crafted Central Park, what do you think he was optimizing for? Which metric led to Barry Jenkins’ Moonlight? What data brought the iPhone into this world? The answer is not numerical. It’s all about the feelings, opinions, experiences, and ideas of the maker themself. The great Georgia O’Keefe put it this way: "I have things in my head that are not like what anyone has taught me... so I decided to start anew."

James Turrell took inspiration from astronomy and perceptual psychology. Coco Chanel was most influenced by nuns and religious symbols. David Adjaye drew from Yoruban sculpture, and Steve Jobs from Zen Buddhism and calligraphy.

And yet, in so much modern software today, you’re placed in a drab gray cubicle — anonymized and aggregated until you’re just a daily active user. For minimalism. For simplicity. For scale! But if our hope is to create software with feeling, it means inviting people in to craft it for themselves — to mold it to the contours of their unique lives and taste.

You see — if software is to have soul, it must feel more like the world around it. Which is the biggest clue of all that feeling is what’s missing from today’s software. Because the value of the tools, objects, and artworks that we as humans have surrounded ourselves with for thousands of years goes so far beyond their functionality. In many ways, their primary value might often come from how they make us feel by triggering a memory, helping us carry on a tradition, stimulating our senses, or just creating a moment of peace.This is not to say that metrics should not play a role in what we do. The age of metrics has undeniably led us to some pretty remarkable things! And numbers are a useful measuring stick to keep ourselves honest.But if the religion of technology preaches anything, it celebrates progress and evolution. And so we ask, what comes next? What do we optimize for beyond numbers? How do we bring more of the world around us back into the software in front of us?

So using that hook of “simplicity”, the best advice for “doing agile” is: Read the manifesto Figure out what makes you happy. And do that.

In fact, more people are technologists than ever before, insofar as a “technologist” can be defined as someone inventing, implementing or repurposing technology. In particular, the personal computer has allowed anyone to live in the unbounded wilderness of the internet as they please. Anyone can build highly specific corners of cyberspace and quickly invent digital tools, changing their own and others’ technological realities. “Technologist” is a common identity that many different people occupy, and anyone can occupy. Yet the public perceptions of a “technologist” still constitute a very narrow image.

A technologist makes reason out of the messiness of the world, leverages their understanding to envision a different reality, and builds a pathway to make their vision happen. All three of these endeavors—to try to understand the world, to imagine something different, and to build something that fulfills that vision—are deeply human.

Humans are continually distilling and organizing reality into representations and models—to varying degrees of accuracy and implicitness—that we can understand and navigate. Our intelligence involves making models of all aspects of our realities: models of the climate, models of each other’s minds, models of fluid dynamics.

We are an unprecedentedly self-augmenting species, with a fundamental drive to organize, imagine, construct and exercise our will in the world. And we can measure our technological success on the basis of how much they increase our humanity. What we need is a vision for that humanity, and to enact this vision. What do we, humans, want to become?

As a general public, we can collectively hold technologists to a higher ethical standard, as their work has important human consequences for us all. We must begin to think of them as doing deeply human work, intervening in our present realities and forging our futures. Choosing how best to model the world, impressing their will on it, and us. We must insist that they understand their role as augmenting and modifying humanity, and are responsible for the implications. Collective societal expectations are powerful; if we don’t, they won’t.

By improving home charging for urban apartment dwellers and prioritizing vehicles with smaller batteries, rather than road-trip-enabling charging stations and big batteries, we could maximize the miles we can affordably electrify. In an era of battery scarcity, we could have two 150-mile E.V.s for the battery capacity in every 300-mile E.V. Or, using the same 300-mile E.V. battery, you could have six plug-in hybrids with 50 miles of electric range for daily driving and a gasoline engine for those rarer road trips or many, many more e-bikes.

Rather than holding E.V. adoption hostage to our ability to make batteries match internal combustion in every way, government policy should focus on the cases where E.V.s have advantages that internal combustion will never match: waking up every morning with a full “tank” sufficient for daily commuting and errands.

Every aspect of interacting with the various institutions that monitored and managed my kids—ACS, the foster care agency, Medicaid clinics—produced new data streams. Diagnoses, whether an appointment was rescheduled, notes on the kids’ appearance and behavior, and my perceived compliance with the clinician’s directives were gathered and circulated through a series of state and municipal data warehouses. And this data was being used as input by machine learning models automating service allocation or claiming to predict the likelihood of child abuse.

The dominant narrative about child welfare is that it is a benevolent system that cares for the most vulnerable. The way data is correlated and named reflects this assumption. But this process of meaning making is highly subjective and contingent. Similar to the term “artificial intelligence,” the altruistic veneer of “child welfare system” is highly effective marketing rather than a description of a concrete set of functions with a mission gone awry.

Child welfare is actually family policing. What AFST presents as the objective determinations of a de-biased system operating above the lowly prejudices of human caseworkers are just technical translations of long-standing convictions about Black pathology. Further, the process of data extraction and analysis produce truths that justify the broader child welfare apparatus of which it is a part.

As the scholar Dorothy Roberts explains in her 2022 book Torn Apart, an astonishing 53 percent of all Black families in the United States have been investigated by family policing agencies.

The kids were contractually the property of New York State and I was just an instrument through which they could supervise their property. In fact, foster parents are the only category of parents legally obligated to open the door to a police officer or a child protective services agent without a warrant. When a foster parent “opens their home” to go through the set of legal processes to become certified to take a foster child, their entire household is subject to policing and surveillance.

Not a single one was surprised about the false allegations. What they were uniformly shocked about was that the kids hadn’t been snatched up. While what happened to us might seem shocking to middle-class readers, for family policing it is the weather. (Black theorist Christina Sharpe describes antiblackness as climate.)

In reality, artificial intelligence encompasses a range of techniques that largely remain useful for a range of uncinematic back-office logistics like processing data from users to better target them with ads, content and product recommendations.

the technologies would at times cause harm, as their humanlike capabilities mean they have the same potential for failure as humans. Among the examples cited: a mistranslation by Facebook’s AI system that rendered “good morning” in Arabic as “hurt them” in English and “attack them” in Hebrew, leading Israeli police to arrest the Palestinian man who posted the greeting, before realizing their error.

Recent local, federal and international regulations and regulatory proposals have sought to address the potential of AI systems to discriminate, manipulate or otherwise cause harm in ways that assume a system is highly competent. They have largely left out the possibility of harm from such AI systems’ simply not working, which is more likely, she says.

The impact is particularly noticeable among Generation Z and millennials, the first generations to come of age with the possibility of knowing where their peers are at all times. It has changed how friends communicate with one another and blurred lines of privacy. Friends now, sometimes unwittingly yet obsessively, check one another’s locations and bypass whole conversations — about where somebody is, what they are doing or how their days are going — when socializing. All of that information can be gleaned from Find My.

Although Find My is not marketed as a social experience, sharing locations has become a test of sorts, much like being included on a close friends list on Instagram or on a private story on Snapchat can signal closer friendships.

With Find My, “you aren’t actively choosing to do something as you reach a certain location because you’re constantly sharing your location,” said Michael Saker, a senior lecturer in digital sociology at City, University of London. As a result, “there’s an intimacy that’s intertwined with that act,” he added. “There’s a verification of being friends.”

In other words, when Kylie Jenner posts a petition demanding that Meta “Make Instagram Instagram again”, the honest answer is that changing Instagram is the most Instagram-like behavior possible.

The first trend is the shift towards ever more immersive mediums. Facebook, for example, started with text but exploded with the addition of photos. Instagram started with photos and expanded into video. Gaming was the first to make this progression, and is well into the 3D era. The next step is full immersion — virtual reality — and while the format has yet to penetrate the mainstream this progression in mediums is perhaps the most obvious reason to be bullish about the possibility.

The second trend is the increase in artificial intelligence. I’m using the term colloquially to refer to the overall trend of computers getting smarter and more useful, even if those smarts are a function of simple algorithms, machine learning, or, perhaps someday, something approaching general intelligence.

The third trend is the change in interaction models from user-directed to computer-controlled. The first version of Facebook relied on users clicking on links to visit different profiles; the News Feed changed the interaction model to scrolling. Stories reduced that to tapping, and Reels/TikTok is about swiping. YouTube has gone further than anyone here: Autoplay simply plays the next video without any interaction required at all.

Nevertheless, the interface pushes back with its prescribed methodologies, workflows, and limitations. Interface and artist are an antagonistic pair. Perhaps the best description of the polemic between the two is one of productive cannibalism. Just as the interface evolves under the pressure of innovation to accommodate new pragmatic uses, the artists’ will continue to deconstruct and push its aesthetic and behavioral properties to their limits.