Psychometrics Data Science

Artificial intelligence (AI)-powered technologies are becoming an integral part of youth's environments, impacting how they socialize and learn. Children (12 years of age and younger) often interact with AI through conversational agents (e.g., Siri and Alexa) that they speak with to receive information about the world. Conversational agents can mimic human social interactions, and it is important to develop socially intelligent agents appropriate for younger populations. Yet it is often unclear what data are curated to power many of these systems. This article applies a sociocultural developmental approach to examine child-centric intelligent conversational agents, including an overview of how children's development influences their social learning in the world and how that relates to AI. Examples are presented that reflect potential data types available for training AI models to generate children's conversational agents' speech. The ethical implications for building different datasets and training models using them are discussed as well as future directions for the use of social AI-driven technology for children.

David Meza, senior data scientist at NASA, and his team are building a talent mapping database to better identify talent for jobs.

David Meza, senior data scientist at NASA, and his team are building a talent mapping database to better identify talent for jobs.

Lifescope lets you search the internet of you using passive automatic life logging. Connect accounts for events, people, places, things, and digital content in one lifelogger. Built on BitScoop.

Learn how NASA uses Neo4j to develop a knowledge graph as part of its knowledge architecture to analyze lessons learned and save astronauts' lives.

An introduction on how to build a knowledge graph using employee and occupation skillsets. This presentation was given at the Nordic People Analytics Confere...

In recent years Knowledge Graphs have been used to solve one of the biggest problems not only in machine learning but also in computer…

Graph database startup Neo4j raised $320 million at an over $2 billion valuation, highlighting the value of graph databases.

Doing cool things with data!

I started a data blog on my quantified self journey. You can read the first post here. Let me know what you think, and if there’s anything in particular you’d be interested in reading in future posts. Thanks!

Online skill tree maker to design detailed, stunning skill trees. Prebuilt templates, customization options, and powerful collaboration capabilites.

Networks have emerged as a popular method for studying mental disorders. Psychopathology networks consist of aspects (e.g., symptoms) of mental disorders (nodes) and the connections between those aspects (edges). Unfortunately, the visual presentation of networks can occasionally be misleading. For instance, researchers may be tempted to conclude that nodes that appear close together are highly related, and that nodes that are far apart are less related. Yet this is not always the case. In networks plotted with force-directed algorithms, the most popular approach, the spatial arrangement of nodes is not easily interpretable. However, other plotting approaches can render node positioning interpretable. We provide a brief tutorial on several methods including multidimensional scaling, principal components plotting, and eigenmodel networks. We compare the strengths and weaknesses of each method, noting how to properly interpret each type of plotting approach.

Stanford scholars found that people’s interactions with a virtual person in augmented reality, or AR, influenced how they behaved in the physical world.

Engineers could use this breakthrough in graph theory to design wildly efficient quantum computer chips.

Mat Zucker shares eight components integral to creative professionals presenting and marketing themselves.

Analyzing arXiv articles with neo4j

Quantified self refers to the practice of using wearable devices and other modern technologies to collect data about one’s own life and health.

As self-trackers are pushing the movement forward, entrepreneurs are helping it scale...

Hi everybody! I’ve been enjoying developing and using an app for measuring+optimizing happiness+efficiency over the last ~9 years, but I’ve been having difficulty getting users to try it out and to give feedback. Would anybody here be interested in any of: Trying it out and offering feedback? Suggesting how to get more feedback? The application has a bunch of properties that I think are super interesting: Record what you do Super-convenient autocomplete: it only requires pressing a few bu...

Training your mind to find meaning in everyday life

Gaia-X represents the next generation of data infrastructure: an open, transparent and secure digital ecosystem, where data and services can be made available, collated and shared in an environment of trust.

I got up at 6:20 this morning

The self-tracking trend is about much more than physical wellbeing.

Reflections on this Year's Prostep IVIP Symposium This year’s Prostep IVIP Symposium was laden with topics around the usage of data ranging from AI over the digital thread and the digital twin. I am convinced there are two major technologies that will be the driving force for such data centric devel

The purpose of this website is to support anybody who wants to use empirical methods to explore personal questions. We call this practice “everyday science.” In the decade that we’ve been working with people doing self-tracking projects, we’ve come to appreciate the diversity of motivations, methods and tools people use to gain insight into a...

Quantified Self Quantified Self (QS) is the term that embodies self-knowledge through self-tracking. The list of things that we can measure about ourselves is endless: among others our heart rate, respiration, hours slept, or even the number of sneezes and coughs during a day. However, not all important things in life can be measured and not everything that