Pierre-Yves Oudeyer

🔍 What happens when you give middle-schoolers unrestricted access to ChatGPT for science tasks? Findings from our new paper led by Rania Abdelghani w/ @koumurayama.bsky.social @celestekidd.bsky.social Hélène Sauzéon 🧵👇

🎯 Takeaways for educators: → AI literacy must train question-asking & answer evaluation, not just "how AI works" → Training metacognition should be a priority: benefits far beyond AI use → An "effortless" AI interaction should be a red flag, not a comfort signal

🔍 What happens when you give middle-schoolers unrestricted access to ChatGPT for science tasks? Findings from our new paper led by Rania Abdelghani w/ @koumurayama.bsky.social @celestekidd.bsky.social Hélène Sauzéon 🧵👇

3️⃣ They almost never asked follow-up questions — even after incomplete answers. Only 14 out of 63 students ever did.

🔍 What happens when you give middle-schoolers unrestricted access to ChatGPT for science tasks? Findings from our new paper led by Rania Abdelghani w/ @koumurayama.bsky.social @celestekidd.bsky.social Hélène Sauzéon 🧵👇

1️⃣ Students couldn't distinguish a good prompt from a bad one. A precise, context-rich question vs. a vague one? Chance-level discrimination.

🔍 What happens when you give middle-schoolers unrestricted access to ChatGPT for science tasks? Findings from our new paper led by Rania Abdelghani w/ @koumurayama.bsky.social @celestekidd.bsky.social Hélène Sauzéon 🧵👇

We studied 63 students (aged 14-15) in French schools. Task: read a science inquiry problem, query ChatGPT, evaluate its answers, then explain the concept in your own words. 📊 Average score: 10/20 — despite unlimited AI access and solvable problems (some scored near-perfect).

New blog post: The Phylogenetics of Artifacts — inferring the evolution of cultural objects, artificial life forms, and language models. From cat genetics to ancient myths to LLMs. 🧬 1/n

📖 Blog: developmentalsystems.org/phylolm 📄 ICLR 2025 paper: iclr.cc/virtual/2025... 💻 Code: github.com/Nicolas-Yax/... Hugging Face online demo: t.co/9wEdav3LZA

New blog post: The Phylogenetics of Artifacts — inferring the evolution of cultural objects, artificial life forms, and language models. From cat genetics to ancient myths to LLMs. 🧬 1/n

The blog walks the full intellectual journey — from cat genetics to Dawkins' memes, from myth phylogenetics to the evolutionary landscape of modern AI. Written to be accessible to anyone curious about evolution, culture, and intelligence. 🌱

New blog post: The Phylogenetics of Artifacts — inferring the evolution of cultural objects, artificial life forms, and language models. From cat genetics to ancient myths to LLMs. 🧬 1/n

Result: surprisingly accurate reconstruction of known model family trees. And a few insights on the ancestry of closed-source models 👀

New blog post: The Phylogenetics of Artifacts — inferring the evolution of cultural objects, artificial life forms, and language models. From cat genetics to ancient myths to LLMs. 🧬 1/n

A good evolutionary marker needs 3 properties: → compressed & universal representation → moderate rate of change → functional grounding DNA has all three. So do high-level myth features. And so does an LLM's core identity: its probability distribution over text.

New blog post: The Phylogenetics of Artifacts — inferring the evolution of cultural objects, artificial life forms, and language models. From cat genetics to ancient myths to LLMs. 🧬 1/n

The myth phylogenies match known human migration patterns — shown beautifully by the outstanding work of Julien d'Huy. Same logic, different substrate: not DNA, but narrative structure as evolutionary marker.

New blog post: The Phylogenetics of Artifacts — inferring the evolution of cultural objects, artificial life forms, and language models. From cat genetics to ancient myths to LLMs. 🧬 1/n

Humans' ability to invent their own games & goals is at the core of open-ended learning. Understanding and modeling computationally how they do it would be enlightening to understand better human cognition and build open-ended AI Great step in this direction in new paper by Guy Davidson et al.

Generative AI is a cultural transmission technology: it plays a growing role in generation, selection and transmission of ideas/opinions in human society 🧠🔄🌐 And yet we understand very little of this dynamics at this point 🤔❓ A step forward is our #ICLR2025 paper !👇

And thank you @gaiamolinaro.bsky.social for presenting the work ! + thanks Jérémy Perez for leading the project and thanks the whole team Corentin Leger @kovacgrgur.bsky.social @ccolas.bsky.social @clemmoulinfrier.bsky.social @maximederex.bsky.social

Forcing Diffuse Distributions out of Language Models "When LLMs are used for real-world tasks where diversity of outputs is crucial their inability to produce diffuse distributions over valid choices is a major hurdle" New method to address this challenge by Zhang et al.: arxiv.org/pdf/2404.10859