Jacy Reese Anthis

@jacyanthis.bsky.social

Researching machine learning and human-AI interaction, particularly the rise of digital minds. Student researcher at Google DeepMind, visiting scholar at Stanford, co-founder of Sentience Institute, and PhD candidate at U of Chicago. jacyanthis.com

When a chatbot uses anthropomorphic companion language like "I'm worried about you" or "You are great, dear", people actually see it as less likable, humanlike, and trustworthy, according to our new simulation study @GoogleResearch with people from the US, UK, India, and Nigeria.

Vertical bar charts comparing companionship-behavior effect estimates for likability, humanlikeness, affective trust, and cognitive trust in Studies 1 and 2. Each estimate is negative (i.e., below the horizontal zero line), and each outcome has a significant negative estimate in at least one study.

Which LLMs tend to facilitate delusion-linked behaviors in realistic multi-turn conversations? We tested 14 models with DelusionEval and found that every evaluated LLM exhibited some of these behaviors, with large differences across categories and model families. 🧵

Can humans be biased against AI? Does an LLM like Claude or a robot "clanker" matter less just because it is artificial: made of chips and wires instead of flesh and blood? With 5 preregistered studies, our new paper rigorously validates a psychometric scale for "substratism" 📝

Bild

After the #CHI2026 opening plenary, catch Janet Pauketat presenting "Mental Models of Autonomy and Sentience Shape Reactions to AI" in session Relationships with AI: 11:15-12:45 Disentangling the two oft-conflated faculties can help us make sense of human-AI interaction: dl.acm.org/doi/10.1145/...

Mental Models of Autonomy and Sentience Shape Reactions to AI | Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems

dl.acm.org

Thrilled to be starting at Google DeepMind as a student researcher! I'll be building a multi-agent system to scale AI safety research and ensure pluralistic alignment with humanity. I think this is a crucial piece of safe AGI development for cooperation and inclusion across many human and AI agents.

Blonde man on a yellow Google Bike in front of a large physical Google "G" letter and a canopy-like building

Disturbing anecdotal reports of "AI psychosis" and negative psychological effects have been emerging in the news. But what actually happens during these lengthy delusional "spirals"? In our preprint, we analyze chat logs from 19 users who experienced severe psychological harm🧵👇

How well do "agent" benchmarks like SWE-bench map onto reality? METR hired repo maintainers and found only ~half of PRs that pass the benchmark would be rejected by the repo maintainers. For now, these benchmarks are still a very weak signal of real-world capability. metr.org/notes/2026-0...

Many SWE-bench-Passing PRs Would Not Be Merged into Main

We find that roughly half of test-passing SWE-bench Verified PRs written by recent AI agents would not be merged into main by repo maintainers. A naive interpretation of benchmark scores may lead one ...

metr.org

🧵on my new paper "Synthetic personas distort the structure of human belief systems" w Roberto Cerina I'm v excited about... 🚨 Do synthetic samples look like human samples? We compare 28 LLMs to the 2024 General Social Survey (GSS) to find out + develop host of diagnostics...

“Pope Leo XIV has urged priests to not to use artificial intelligence to write their homilies or to seek ‘likes’ on social media platforms like TikTok.” “‘To give a true homily is to share faith,’ and artificial intelligence ‘will never be able to share faith,’ the pope added.”

Pope Leo tells priests not to use AI to write homilies or seek likes on TikTok

"To give a true homily is to share faith," and artificial intelligence "will never be able to share faith," the pope said.

ncronline.org

Any journalist who covered LLMs as stochastic parrots/spicy autocomplete who didn't also point out that text compression was considered to be "AI-complete" by many people working in AI decades before LLMs existed was misleading their readers. We're still dealing with the consequence of that mistake.