Expert attention map

The Who's Who of AI

What credible people across AI noticed, why it matters, and where the field is converging or disagreeing.

2,364 searchable experts 2,966 tracked across all sources
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Posts are grouped by conversation and tone. Select a lens to filter the stream; these are never permanent labels on people.

Showing signals surfaced by Data & Society ×

What is moving across the network now

One card per development. Sources are clustered; reaction bundles describe these posts, never the people behind them.

New Agents & robotics Signal 11h ago

The Limits of Human Oversight in the Age of AI Agents - Data & Society

2 directory members surfaced this signal.

2 experts 1 community 1 sources clustered

“On August 20, at 1 p.m. ET, the authors will join @mmitchell.bsky.social, chief ethics scientist @hf.co; and Madeleine Claire Elish, head of eval, responsible development, & innovation at Google Deepmind; to discuss their research. Learn more and RSVP! data…”

New Agents & robotics Signal 11h ago

The Oversight Fallacy: Why AI Agents Require More than Humans-in-the-Loop - Data & Society

1 directory member surfaced this signal.

1 expert 1 community 1 sources clustered

“📣 New! As AI agents are increasing used for daily tasks, their relative autonomy challenges traditional means of human oversight. Samir Passi & Ranjit Singh show why oversight can't rest on individual users alone, w specific recommendations for builders and…”

Developing Culture, work & education Signal 1d ago
⚡ 385 h early

Ai white collar jobs

2 experts are actively discussing the implications.

2 experts 2 communities 1 sources clustered

“Once AI companies have taught their models to perform a certain job, their need for more training data in that area could sharply decline. In this way, data-training start-ups are like the freelancers they employ: making $$ today, in danger of being dropped…”

“it's not like Mercor is the first to do this, but interesting that AI companies hiring experts is (finally) getting attention :: www.nytimes.com/2026/07/10/b...”

2 experts discussed this · 5 posts
Jeffrey P. Bigham: end of an era. the lesson one should not take from this is that human annotation/labeling is over, but the players have changed. scale, surge, companies that work at larger scale, have taken over.
Jeffrey P. Bigham: it's always been a little bit odd how little amazon invested in making mturk good, yet they kept it around. the lore was something about how they were keeping it in case it became useful.
Long Lasting Mascot: Indeed. My first project in grad school involved getting turkers to annotate data for us. The results were not good, but I was never sure if it was our instructions or their abilities.
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Developing Culture, work & education Signal 1d ago

Ai screens schools weingarten

1 directory member surfaced this signal.

1 expert 1 community 1 sources clustered

““If we don’t find a way to call this out from an education perspective, I fear that we will lose a generation of kids,” says @rweingarten.bsky.social. “The work of teaching and learning in the earliest grades should be done without AI.” www.nytimes.com/2026…”

Developing AI field signal Analysis 2d ago
⚡ 219 h early
AI gender gap parenting intersection essay

The A.I. Gender Gap Meets the Parenting Gender Gap

3 directory members surfaced this signal.

3 experts 1 community 1 sources clustered

“A lesson from the history of household tech, from the vacuum cleaner to the AI family assistant: Labor-saving technology tends to create domestic systems that are far more efficient over all, but not necessarily easier for the people doing the labor. www.ne…”

““Recently, she tried to train Claude to help with meal planning for her family of three, but gave up after a couple of months. “It would leave crucial ingredients out, it would get the proportions totally wrong, it would suggest the same five things over an…”

Developing Responsible AI Development 2d ago
⚡ 174 h early

AI is more likely than humans to form biases when hiring

2 directory members surfaced this signal.

2 experts 1 community 1 sources clustered
How the network is reacting 2 experts are emphasizing concern & critique.
Shared emphasis

Concern & critique

2 experts

Risks, limits and unintended consequences.

“New research suggests that LLMs can develop their own biases from experience, separate from their training data. This can lead them to stereotype job applicants even more than humans do. www.technologyreview.com/2026/07/20/1...”

Established AI field signal Signal 5d ago

J.B. Branch: Brace yourself for the AI public relations blitz

1 directory member surfaced this signal.

1 expert 1 community 1 sources clustered

““No fellowship, academy or glossy public opinion campaign can repair what years of extraction and broken promises have eroded,” @jbbranch.bsky.social writes. “[T]rust, once squandered, is far harder to build than the next model update.” www.chicagotribune.c…”

Established AI field signal Analysis 6d ago
municipal government AI models essay

What If Municipal Governments Built Their Own AI Models? - Data & Society

1 directory member surfaced this signal.

1 expert 1 community 1 sources clustered

“To make govt services more accessible & accountable, @baricks.bsky.social, @boston.gov’s aleja jimenez jaramillo & @megyoung0.bsky.social call on state & local govts to explore collectively-governed “in-house” alternatives to commercial language translation…”