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The Who's Who of AI

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

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Showing developments with attributable Policy & governance reactions.

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See how experts are reacting—not just what they shared.

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Policy & governance Research & technical analysis
1 live reaction map in this view Jump to the evidence ↓
Multiple readings Can AI Stand In for Human Survey-Takers? Not Really Policy & governance · 2 attributable reactions
Showing signals surfaced by J. Nathan Matias ×
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The developments commanding sustained expert attention

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

Established AI research Research 14d ago
⚡ 42 h early
Pew Research AI survey takers study

Can AI Stand In for Human Survey-Takers? Not Really

6 experts across 2 network communities independently surfaced this.

Why this matches Policy & governance reaction 1 attributable expert contribution · Dr. Elinor Carmi
“We just had a discussion on this in our editorial meeting of Internet Policy Review. It would be great to hear from other academic journal editors what are their policies around researchers using synthetic data. -> www.pewresearch.org/data-labs/20...” evidence ↗
6 experts 2 communities 1 sources clustered
Olivia Guest J. Nathan Matias Luke Stark Dr. Elinor Carmi Michael Zimmer Andrea Lathrop
How the network is reacting Experts are approaching this through 2 distinct lenses.
Multiple readings

Policy & governance

1 expert

Rules, institutions and accountability.

“We just had a discussion on this in our editorial meeting of Internet Policy Review. It would be great to hear from other academic journal editors what are their policies around researchers using synthetic data. -> www.pewresearch.org/data-labs/20...”

Research & technical analysis

1 expert

Evidence, methods and technical implications.

“In case you've been wondering about the viability of AI simulated surveys, Pew has offered in-depth reporting on their experiment with simulated survey participants. By Athena Chapekis, Arnold Lau, Samuel Bestvater, Sono Shah, Andrew Mercer, Aaron Smith www…”

Primary source pewresearch.org ↗
Established Culture, work & education Analysis 16d ago
Copyright law fixes AI bias paper

"How Copyright Law Can Fix Artificial Intelligence's Implicit Bias Prob" by Amanda Levendowski

3 experts across 2 network communities independently surfaced this.

Why this matches Policy & governance reaction 1 attributable expert contribution · Amanda Tepski
“If you wanna talk about AI training data, pls check out my early work addressing public domain data, licensing, and fair use (scholarship.law.georgetown.edu/facpub/2439/) and also why it’s possible for uses to be both fair and garbage (scholarship.law.georg…” evidence ↗
3 experts 2 communities 1 sources clustered
J. Nathan Matias Eileen Clancy 🧿 Amanda Tepski

“If you wanna talk about AI training data, pls check out my early work addressing public domain data, licensing, and fair use (scholarship.law.georgetown.edu/facpub/2439/) and also why it’s possible for uses to be both fair and garbage (scholarship.law.georg…”

Primary source scholarship.law.georgetown.edu ↗
Established Policy & governance Research 16d ago
copyright law public benefit paper

"Fairer Public Benefit in Copyright Law" by Amanda Levendowski Tepski

2 directory members surfaced this signal.

Why this matches Policy & governance reaction 1 attributable expert contribution · Amanda Tepski
“If you wanna talk about AI training data, pls check out my early work addressing public domain data, licensing, and fair use (scholarship.law.georgetown.edu/facpub/2439/) and also why it’s possible for uses to be both fair and garbage (scholarship.law.georg…” evidence ↗
2 experts 2 communities 1 sources clustered
J. Nathan Matias Amanda Tepski

“If you wanna talk about AI training data, pls check out my early work addressing public domain data, licensing, and fair use (scholarship.law.georgetown.edu/facpub/2439/) and also why it’s possible for uses to be both fair and garbage (scholarship.law.georg…”

Primary source scholarship.law.georgetown.edu ↗