5:21ET on a Friday. www.anthropic.com/news/fable-m...
Who's Who of AI
Brian C. Keegan, Ph.D.
Why they matter
Researcher with public evidence across Policy & governance, AI research, Culture, work & education.
- AI signals
- 2 past 30d
- Sources
- 2 distinct domains
- Discussões
- 6 past 30d
- Latest signal
- 4d ago
{Social, Data, Network, Information} Scientist, @cuboulder.info
Visiting Scientist, @harvardpopcenter.bsky.social AY25-26
High-tempo collaboration, information commons, public interest data science
https://www.brianckeegan.com/
Signal: brianckeegan.26
What they're sharing
Statement on the US government directive to suspend access to Fable 5 and Mythos 5 anthropic.com
AI Fiction Is Easy to Detect Because It's Stupid and Bad, Research Finds 404media.co
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The Safety Reckoning Inside OpenAI wired.com
Contemporary AI lacks the imagination to diverge or negate in science arxiv.org
GitHub - Zoher15/PluRule: PluRule: A multilingual, multimodal benchmark for detecting rule violations when moderating pluralistic communities on social media. github.com
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Return of the solo author: The changing division of labor in science in the age of generative AI arxiv.org
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The Reciprocal Impact of Science and Software: A Cross-Corpus Analysis of How Research Shapes Software and Software Enables Research arxiv.org
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Discriminatory Compliance: How LLMs Answer Queries from Protected Groups arxiv.org
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arxiv.org
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Discriminatory Compliance: How LLMs Answer Queries from Protected Groups arxiv.org
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Examining AI-generated historical narratives and their reception through the example of history POVs on TikTok arxiv.org
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arxiv.org
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Articles & links
Brian C. Keegan, Ph.D. reposted
NEW: Fiction written by AI is easy to detect because it struggles with complex story structure, according to a new study. Researchers found that AI fiction has tells that go beyond the overuse of em-dashes and other obvious AI tropes and have more to do with the formulaic natu…
No one could've seen this coming www.wired.com/story/openai...
Brian C. Keegan, Ph.D. reposted
Honglin Bao, Siyang Wu, Xiao Liu, Sida Li, Shiyun Cao, James A. Evans: Contemporary AI lacks the imagination to diverge or negate in science https://arxiv.org/abs/2606.08251 https://arxiv.org/pdf/2606.08251 https://arxiv.org/html/2606.08251
AI Weekly's analysis
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- No model class tested — reasoning or non-reasoning — spontaneously proposed null hypotheses, a move scientists make more freely.
- Non-reasoning LLMs converge into a 'hivemind' of similar ideas; LLMs struggle most in pluralistic fields like the social sciences.
- The study drew 25,139 rating sets from 6,749 scientists across biology, medicine, chemistry, and the social sciences.
Read full analysis →
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Brian C. Keegan, Ph.D. reposted
ACL 2026 was fun! We presented our benchmark, which reveals that frontier models struggle to moderate pluralistic communities on Reddit. A fun bonus: creating all the colorful plots for the paper! 🎨 Our paper, code, and benchmark are all available here: github.com/osome-iu/Plu...
Brian C. Keegan, Ph.D. reposted
Return of the solo author: The changing division of labor in science in the age of generative A https://arxiv.org/abs/2607.10780
Brian C. Keegan, Ph.D. reposted
The Reciprocal Impact of Science and Software: A Cross-Corpus Analysis of How Research Shapes Software and Software Enables Research https://arxiv.org/abs/2606.28120
Brian C. Keegan, Ph.D. reposted
Dinesh Ayyappan, Carlos Castillo: Discriminatory Compliance: How LLMs Answer Queries from Protected Groups https://arxiv.org/abs/2606.21296 https://arxiv.org/pdf/2606.21296 https://arxiv.org/html/2606.21296
Brian C. Keegan, Ph.D. reposted
Dinesh Ayyappan, Carlos Castillo: Discriminatory Compliance: How LLMs Answer Queries from Protected Groups https://arxiv.org/abs/2606.21296 https://arxiv.org/pdf/2606.21296 https://arxiv.org/html/2606.21296
Brian C. Keegan, Ph.D. reposted
Dinesh Ayyappan, Carlos Castillo: Discriminatory Compliance: How LLMs Answer Queries from Protected Groups https://arxiv.org/abs/2606.21296 https://arxiv.org/pdf/2606.21296 https://arxiv.org/html/2606.21296
Brian C. Keegan, Ph.D. reposted
Nina Brolich, Anna Neovesky: Examining AI-generated historical narratives and their reception through the example of history POVs on TikTok https://arxiv.org/abs/2606.23300 https://arxiv.org/pdf/2606.23300 https://arxiv.org/html/2606.23300
Brian C. Keegan, Ph.D. reposted
Nina Brolich, Anna Neovesky: Examining AI-generated historical narratives and their reception through the example of history POVs on TikTok https://arxiv.org/abs/2606.23300 https://arxiv.org/pdf/2606.23300 https://arxiv.org/html/2606.23300
Their own posts
Recent commentary
I am so excited to finally get access to @anthropic.com Fable 5 so I can center this div.
Their network
In Brian C. Keegan, Ph.D.'s orbit
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