Direct link to the actual paper: arxiv.org/pdf/2604.04721
D. Hicks
Researcher with public evidence across AI research, Policy & governance.
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I saw a bunch of people dragging this study based on the recruitment emails back in the spring. But it seems to have resulted in empirical evidence for exactly the critiques those people wanted to make! arxiv.org/abs/2606.08251
- 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.
I know a bunch of the CSUs are worried about enrollments, but uhhh leaning into the technology gen Z actively hates doesn't seem like the bestest recruitment strategy? www.sfgate.com/bayarea/arti...
There are plenty of other reasons to not use Google products, but they don't use customer data to train models: knowledge.workspace.google.com/admin/genera...
Recent commentary
I see we've decided to move on to conspiracy theories and/or confusing LLM training with social media algorithms
You don't have to use AI or even like it. But try to avoid confidently making clearly false statements like "AI can't do web search." They've had web search tools for like two years now.
Today we're mad that Substack has made a partnership with Pangram, an AI detector that (a) has an extremely low false positive rate, (b) isn't based on "AI tells," and (c) does not itself use generative AI
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