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Reposted by Basile Garcia

Stefano Palminteri @stepalminteri.bsky.social · 03/06/2026

New article out in @natcomms.nature.com : Context induces distortions in value representations across multiple elicitation methods and learning modalities, with Magda Soukupova (first author) and @bsgarcia.bsky.social www.nature.com/articles/s41...

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Reposted by Basile Garcia

Stefano Palminteri @stepalminteri.bsky.social · 15/01/2026

A revised version of our (@bsgarcia.bsky.social +Crystal Qian) paper “A Moral Turing Test to assess how subjective belief and objective source affect detection and agreement with LLM judgments” is now available on PsyArXiv osf.io/preprints/ps...

Screenshot of the abstract:
As large language models (LLMs) are increasingly integrated into decision-making systems—such as au-tonomous vehicles and medical devices—understanding how humans perceive and evaluate AI-generatedjudgements is crucial. To investigate this, we conducted a series of experiments in which participants evaluatedjustifications for moral and non-moral choices, generated either by humans or LLMs. Participants attempted toidentify the source of each justification (either human or LLM) and indicated their agreement with its content.We found that while detection accuracy was consistently above chance, it remained below 70%. In terms ofagreement, there was no overall preference for human-generated responses, even though machine-generatedjustifications were favored in particularly challenging moral scenarios. Notably, we observed a systematic anti-AIbias: participants were less likely to agree with judgments they believed were AI-generated, regardless of thetrue source. Linguistic cues, such as response length, typos, first-person pronouns, and cost-benefit languagemarkers (e.g., “lives,” “save”), influenced both detection and agreement. Participants tended to disagree withcost-benefit calculations, possibly due to an expectation that AI would favor such reasoning. These findingshighlight the influence of motivated belief and ingroup/outgroup bias in shaping human evaluation of AI-generatedcontent, particularly in morally sensitive contexts.

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Reposted by Basile Garcia

Stefano Palminteri @stepalminteri.bsky.social · 05/02/2026

Across seven incentivized experiments and a large reanalysis, we systematically manipulated the presence and type of post-choice feedback in repeated risky decisions to test whether feedback shapes behavior through learning mechanisms or through anticipatory changes in preferences.

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Reposted by Basile Garcia

Sophie Bavard @sophiebavard.bsky.social · 13/10/2025

🚨 New preprint! 🚨 Very happy to share our latest work on metacognition with M. Rouault, A. McWilliams, F. Chartier, @kndiaye.bsky.social and @smfleming.bsky.social where we identify contributors to self-performance estimates across memory and perception domains 👇 osf.io/preprints/ps...

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Reposted by Basile Garcia

Stefano Palminteri @stepalminteri.bsky.social · 09/10/2025

Thought experiments such as the Blockhead and Super-Super Spartans are often taken as “definitive” arguments against behavior-based inference of cognitive processes. In our review -with @thecharleywu.bsky.social- we argue they may not be as definitive as originally thought.

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Reposted by Basile Garcia

Caroline Pioger @carolinepioger.bsky.social · 07/08/2025

🎉 Excited to present a poster at #CCN2025 in Amsterdam! 📍 Aug 12, 1:30–4:30pm We show that experiential value neglect (Garcia et al., 2023) is robust to changes in how options and outcomes are represented. Also, people show reduced sensitivity to losses, especially in comparative decision-making.

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Reposted by Basile Garcia

Nicolas Yax @nicolasyax.bsky.social · 24/04/2025

🔥Our paper PhyloLM got accepted at ICLR 2025 !🔥 In this work we show how easy it can be to infer relationship between LLMs by constructing trees and to predict their performances and behavior at a very low cost with @stepalminteri.bsky.social and @pyoudeyer.bsky.social ! Here is a brief recap ⬇️

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Reposted by Basile Garcia

NPR @npr.org · 24/04/2025

Harvard scientist Kseniia Petrova has been in ICE custody for about two months. Her colleague and friend Leon Peshkin says her case is causing some scientists to reconsider working in the U.S.

npr.org

Colleague of Harvard scientist held by ICE warns that foreign scientists are scared

Harvard scientist Kseniia Petrova has been in ICE custody for about two months. Her colleague and friend Leon Peshkin says her case is causing some scientists to reconsider working in the U.S.

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Reposted by Basile Garcia

Stefano Palminteri @stepalminteri.bsky.social · 23/04/2025

Below the thread about a thoroughly updated version of our human-machine / moral psychology paper where we show the complex nature of anti-/ pro-AI biases in evaluating and detecting machine vs. artificial judgements. Study lead by @bsgarcia.bsky.social in collaboration with Crystal Qian

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Basile Garcia @bsgarcia.bsky.social · 23/04/2025

How does thinking something is AI-generated influence agreement—and vice versa?🧠 In our latest preprint (@stepalminteri.bsky.social, Crystal Qian), ~230 people judged justifications from GPT-3.5 and humans across moral dilemmas. osf.io/preprints/ps... 👇

How Objective Source and Subjective Belief Shape the Detectability
and Acceptability of LLMs' Moral Judgments
Basile Garcia (1) Crystal Qian (2) Stefano Palminteri (3)
(1) University ofGeneva, Geneva, Switzerland
(2) Google, DeepMind, New York City, NY USA
(3) d'études cognitives, École normale supérieure, PSL Research University;
paris, 75005, France-
(4) Laboratoire de Neurosciences Cognitives Computationnelles, Institut National de la Santé et
de la Recherche Médicale', paris, 75005, France.

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Stefano Palminteri @stepalminteri.bsky.social · 16/04/2025

Our first fMRI in a while where we investigate the neural bases or multi-step Reinforcement Learning and found a clear functional dissociation between the parietal and the peri-hippocampal cortex. More info by Fabien, below

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fabiencerrotti.bsky.social @fabiencerrotti.bsky.social · 16/04/2025

🚨 New preprint on bioRxiv! We investigated how the brain supports forward planning & structure learning during multi-step decision-making using fMRI 🧠 With A. Salvador, S. Hamroun, @mael-lebreton.bsky.social & @stepalminteri.bsky.social 📄 Preprint: submit.biorxiv.org/submission/p...

submit.biorxiv.org

bioRxiv Manuscript Processing System

Manuscript Processing System for bioRxiv.

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