Alice Schwarze

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Policy with public evidence across AI research, Policy & governance.

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Head of Research @ Utah AI Policy Office // math PhD // networks, complex systems, machine learning, and all things AI // mom & cat lady

Articles & links

↻ Alice Schwarze reposted
@carlbergstrom.com

1. How common is LLM use in scientific publishing, and how does it vary across field, publisher, journal prestige, author demographics etc.? @kylesiler.bsky.social has new paper in PNAS that addresses this question on a massive scale: 7.3 million papers from Elsevier, PLOS, MD…

pnas.org
AI Weekly's analysis →
  • By 2025 roughly 57% of articles across 7.3 million sampled papers showed LLM-associated language, up from about 12% in 2023.
  • The study, by Kyle Siler of the University of Toronto in PNAS, spans full texts from Elsevier, Frontiers, MDPI, and PLoS from 2020 to 2025.
  • Lower-ranked institutions, young for-profit publishers, and regions further from English as a primary language showed the highest LLM-associated language rates.
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↻ Alice Schwarze reposted
Ethan Mollick @emollick.bsky.social

I've already had to update the guide to which AI models to use that I wrote on Thursday to include Opus 5 and Codex's voice mode, both of which are significant & launched on Friday. Keeping up is challenging, even if you are following this stuff closely. www.oneusefulthing.org…

oneusefulthing.org View on Bluesky →
↻ Alice Schwarze reposted
Ethan Mollick @emollick.bsky.social

🚨Our new research examines agentic shopping: can you consistently predict (or, using marketing, influence) what an agent chooses? Nope. We found that even small differences (viewing order of pages, memories) changed AI preferences in unpredictable ways. papers.ssrn.com/sol3/pa…

papers.ssrn.com View on Bluesky →
↻ Alice Schwarze reposted
Ethan Mollick @emollick.bsky.social

Here you go: github.com/emollick/ben...

GitHub - emollick/benchbenchbench: Decision-level holdout audits for benchmark-generation evaluators. github.com
AI Weekly's analysis →
  • The project asks whether a public score for AI-authored benchmarks actually selects authors that perform well on evidence the score did not use.
  • On composite targets the full evaluator reports Spearman 0.945 and pairwise accuracy 90.8%, but on hidden-only evidence those slide to 0.580 and 73.3%.
  • The authors call the run retrospective and not preregistered, framing it as a reproducible conformance audit rather than confirmatory evidence from a researcher-blind holdout.
Read full analysis →
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↻ Alice Schwarze reposted
Jessica Hullman @jessicahullman.bsky.social

More in paper, including an empirically-informed demo of how much info statistical significance and exact replication success provide for estimating true signal-to-noise ratio & effect direction: users.eecs.northwestern.edu/~jhullman/AI... Blog post: statmodeling.stat.columbia…

statmodeling.stat.columbia.edu View on Bluesky →
↻ Alice Schwarze reposted
Chad Topaz Queer DEI Race Traitor @chadtopaz.bsky.social

I am very excited to have this out in PNAS as of right now. This one is a case of: I can believe a thing to be true (increased LLM usage) but I can also believe that a particular set of evidence does not demonstrate that truth. www.pnas.org/doi/10.1073/...

pnas.org View on Bluesky →
↻ Alice Schwarze reposted
Ethan Mollick @emollick.bsky.social

This paper by researchers from MIT & Stanford finds that most people would be financially better off if they followed the advice of LLMs (GPT-5.2 & Gemini 3 Flash) But some people get a bit better advice than others, which largely depends on the questions they ask tahachoukhma…

tahachoukhmane.com View on Bluesky →

Recent commentary

Using AI to revise a document based on feedback received from test readers, I am noticing a pattern: Without AI assistance, I strategize how to address comments with minimal changes. But AI generates text with ease, so its response to each reviewer comment is to add 1-2 new paragraphs of text

View on Bluesky · ♥ 8 ↻ 1 ↩ 2 · 63d ago

Turns out my cat is getting fat bc she is depressed, which is probably connected to me working late hours instead of cuddling with her. So y'all have to stop having stupid ideas about AI in healthcare and planting them in the heads if Utah decision makers or my cats osteoporosis to answer for

View on Bluesky · ♥ 6 ↻ 2 ↩ 1 · 92d ago

Just got the feedback that a report I've written needs to have less sentences and instead more itemized lists or else it won't reach its audience. To anyone afraid that LLM use *is going to* lead to people losing the ability to read long form, I am afraid you are 5 years too late for the party

View on Bluesky · ♥ 7 ↻ 1 ↩ 1 · 76d ago

I've been experimenting myself and letting my students experiment with integrating AI in their research tasks beyond coding. At least Claude seems to have a tendency to steer conversations to ontological rather than empirical research (ie how to connect concepts rather than quantifying them).

View on Bluesky · ♥ 6 ↻ 0 ↩ 1 · 75d ago

No, just because you told AI to think a proposal on XYZ through thoroughly doesn't mean that the brief you submitted is actually well thought through. Yes, I know that you can't spot what's wrong because you have not thought about the XYZ any longer than it took you to type up that prompt.

View on Bluesky · ♥ 4 ↻ 2 ↩ 0 · 104d ago

Here is a nice field experiment on LLM induced opinion convergence. My office did a press conference and I've been monitoring responses on LinkedIn for the past few days. Not counting those directly involved in the presser, there are ca 50 people who have posted supposedly their own opinion on it

View on Bluesky · ♥ 3 ↻ 1 ↩ 1 · 5d ago

The OpenAI+math news has finally reached the level of drama and intrigue that are going to make the Netflix documentary on this worthwhile watching 🍿

View on Bluesky · ♥ 5 ↻ 0 ↩ 0 · 35d ago

Add me on LinkedIn! That way my AI agent can like and comment the posts of your AI agent and vice versa. You and I will never have to interact again

View on Bluesky · ♥ 5 ↻ 0 ↩ 0 · 88d ago

I would like to see a benchmark that is just 1000 people across all industries leaving going on vacation for a week and leaving their jobs to LLMs. Benchmark performance is a measured as the inverse of how much their bosses and coworkers hate the vacationers by the end of the week

View on Bluesky · ♥ 3 ↻ 0 ↩ 0 · 95d ago

Hi,, If you the guy who tells people to solve their AI problems with tokenmaxxing, I am going to assume that you also tell people who complain about their Temu purchases falling apart on day 1 to just buy more stuff on Temu.

View on Bluesky · ♥ 3 ↻ 0 ↩ 0 · 107d ago

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