Who's Who of AI

Henry Farrell

236 trust commentator @himself.bsky.social · 37,100 followers
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Commentator with public evidence across AI research.

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Professor of democracy and international affairs. http://www.henryfarrell.net and newsletter at http://www.programmablemutter.com. Underground Empire: How America Weaponized the World Economy (Holt, Penguin). https://www.publishersweekly.com/9781250840554.
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Builds on stodgier academic work here - www.science.org/stoken/autho... - this, by Roberts et al, is also very interesting on language and LLMs albeit much more political www.nature.com/articles/s41...

State media control influences large language models | Nature nature.com
AI Weekly's analysis →
  • Chinese state-media content appears in typical LLM training sets at roughly 41 times the rate of Chinese-language Wikipedia.
  • Across 37 countries, models prompted in the local language produce more regime-favorable responses in countries with lower press freedom.
  • A pretraining experiment with just 6,400 state-scripted documents pushed an open-weight model to pro-government responses nearly 80 percent of the time.
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View on Bluesky · ♥ 9 ↻ 4 ↩ 1 · 10 from the directory shared this · 4d ago

Why we need the social sciences to understand AI www.nytimes.com/2026/09/06/o...

nytimes.com
View on Bluesky · ♥ 98 ↻ 36 ↩ 4 · 8 from the directory shared this · 21d ago

On the one hand, it may not ever be great at truly open ended forms of discovery, which aren't readily testable and aren't obviously amenable to some kind of reinforcement learning type feedback. So "geniuses in a lab" may never turn out to be generalizable. arxiv.org/abs/2607…

Can AI agents conduct open-ended AI research? Early evidence from two case studies arxiv.org
AI Weekly's analysis →
  • Frontier agents got six days and thousands of dollars of compute to tackle the central research question of two unpublished NeurIPS 2026 papers.
  • The agents completed all the engineering unaided but the papers' original authors unambiguously rejected the output as research.
  • The 24-author team names five recurring failure modes and releases the expert reviews, agent repositories, and logs for replication.
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View on Bluesky · ♥ 3 ↻ 0 ↩ 1 · 4 from the directory shared this · 57d ago

"At last we have created the Corporation That Eliminates Middle Managers from classic management text Don't Eliminate the Middle Managers!" www.programmablemutter.com/p/ai-isnt-ma...

programmablemutter.com
AI Weekly's analysis →
  • Cloudflare CEO Matthew Prince laid off more than 20% of his workforce while citing Peter Drucker's 1954 management framework to explain the cuts.
  • Prince labeled laid-off workers 'measurers' — a Drucker category he applied to middle management, finance, legal, and internal auditing.
  • Henry Farrell argues Prince inverted Drucker's intent: Drucker used measurement to develop managers, not to identify who to eliminate.
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View on Bluesky · ♥ 187 ↻ 63 ↩ 1 · 7 from the directory shared this · 124d ago
↻ Henry Farrell reposted
@birdsnfrogs.bsky.social

The essay, which I started working in full during the ICM, owes its framing to the important work of @himself.bsky.social, @alisongopnik.bsky.social, @cshalizi.bsky.social, and James Evans on LLMs as cultural technologies 2/ www.science.org/doi/full/10....

science.org View on Bluesky →

1. www.bloomberg.com/opinion/news... So Matt Levine had a newsletter yesterday where he suggested that AI labs could "publish papers about how important it is to slow down" to coordinate an effective cartel. I have a Modest Proposal that goes one better.

bloomberg.com
View on Bluesky · ♥ 74 ↻ 31 ↩ 1 · 2 from the directory shared this · 12d ago

This, by @melaniemitchell.bsky.social is a strong, subtle overview of where we are at yalereview.org/article/mela...

Melanie Mitchell: The Dangerous Unknowns at the Heart of LLMs yalereview.org
AI Weekly's analysis →
  • AI systems excel on some tasks while failing surprisingly on similar ones, a pattern Mitchell calls 'jagged intelligence.'
  • Ilya Sutskever, OpenAI cofounder, is quoted saying LLMs 'generalize dramatically worse than people' in a way that is 'very fundamental.'
  • Mitchell says AI researchers, herself included, are still struggling to design effective evaluation methods for LLMs' uneven capabilities.
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View on Bluesky · ♥ 17 ↻ 5 ↩ 3 · 5 from the directory shared this · 110d ago
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AI author-spamming veers unexpectedly into bonkers surrealism

View on Bluesky · ♥ 63 ↻ 6 ↩ 10 · 13d ago
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