Practical

There is a finding from a 2024 study published at the ACM CHI Conference that deserves more attention than it has received. Researchers analyzed nearly nine thousand COVID-19 data visualization posts on Twitter,

How category errors in AI research lead to regulatory failure The most consequential errors in AI discourse are not the obvious ones. They are the ones that survive peer review, get cited in

The coverage of Claude Mythos followed a familiar pattern. Initial alarm about offensive capability followed by security community response followed by company mitigation and marketing, followed by a rapid news cycle. Then attention

Governing AI in Schools: the Developmental Stakes The debate about screens in schools is being conducted almost entirely from outcomes. Test scores, engagement metrics, effect sizes, procurement accountability: these matter, but they are

Anthropic's recent paper "The Hot Mess of AI: How Does Misalignment Scale with Model Intelligence and Task Complexity?" makes an important empirical observation: frontier models show increasing output variance