Project and publication examining what we teach AI systems and what those choices say about us.
In plain terms: This project shares anonymous handwritten notes about people to examine what humans teach artificial intelligence systems. You can read the publication to reflect on the personal choices and ethics behind modern technology.
Why I recommend it: Useful for language and framing when you explain AI risk to non-technical people.
Read / subscribe freeThis is the only entry from What We Tell AI in the hub so far.
Other resources that share this publication's topics.
Public resources and event highlights from an organization researching, building and governing technology around human flourishing. Covers AI, youth wellbeing and technology policy; the listing refers to free public material, not guaranteed free access to every event or program.
Medium CEO Tony Stubblebine's announcement of TK, a private agentic notebook app from Medium for drafting writing and developing ideas, describing the company's position that writing still matters as AI tools spread.
A KDnuggets guide by Vinod Chugani that goes round by round through current data science hiring processes, including AI-assisted coding rounds and generative AI evaluation questions, and lists ways candidates can prepare.
A Resume Now survey report on workplace values, stating that 70% of surveyed workers say leaders bend rules for favorites, with findings on fairness, favoritism and alignment between stated and practiced company values. Resume Now sells résumé-building services.
A Built In survey of job seekers on how AI tools shape which employers they find and consider. Among respondents who use AI for employer research, 66% say they applied to a company they had not considered and 53% say they decided not to apply somewhere because of what AI showed them. Built In sells employer branding services.
Artificial Analysis reports Muse Ember benchmark scores and task-cost estimates, including an Intelligence Index score of 36 and $0.14 per task in its evaluation. These are evaluator-specific results, not a verified Meta launch announcement or evidence of free model access.
