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Wim De Neys

@wimdeneys.bsky.social

Psychological scientist @ CNRS & University of Paris

37 Posts356 Follower106 Folgt
Wim De Neys@wimdeneys.bsky.social · 7mo ago

New work led by @jeremiebeucler.bsky.social who used LLMs to estimate stereotype strength in base-rate items. Great tool to create new material ;-)

Jérémie Beucler@jeremiebeucler.bsky.social · 7mo ago

Our paper with @zoepurcell.bsky.social , @luciecharlesneuro.bsky.social and @wimdeneys.bsky.social on using LLMs to estimate belief strength in reasoning is out in Behavior Research Methods. If you're interested in reasoning biases & LLMs as measurement tools, check it out: rdcu.be/eZXGK (free pdf)

title of the paper in behavior research methods
Jérémie Beucler@jeremiebeucler.bsky.social · 8mo ago

Our paper with @zoepurcell.bsky.social, @luciecharlesneuro.bsky.social, and @wimdeneys.bsky.social has been accepted at Behavior Research Methods! 🥳 Here is the updated preprint: osf.io/preprints/ps... Also, the baserater package is now on CRAN: cran.r-project.org/package=base... #psynomBRM

OSF

osf.io

Jérémie Beucler@jeremiebeucler.bsky.social · 10mo ago

1/10 🚨 New preprint: Using Large Language Models to Estimate Belief Strength in Reasoning 🚨 When asked: "There are 995 politicians and 5 nurses. Person 'L' is kind. Is Person 'L' more likely to be a politician or a nurse?", most people will answer "nurse", neglecting the base-rate info. A 🧵👇

Abstract Accurately quantifying belief strength in heuristics-and-biases tasks is crucial yet methodologically challenging. In this paper, we introduce an automated method leveraging large language models (LLMs) to systematically measure and manipulate belief strength. We specifically tested this method in the widely used “lawyer-engineer” base-rate neglect task, in which stereotypical descriptions (e.g., someone enjoying mathematical puzzles) conflict with normative base-rate information (e.g., engineers represent a very small percentage of the sample). Using this approach, we created an open-access database containing over 100,000 unique items systematically varying in stereotype-driven belief strength. Validation studies demonstrate that our LLM-derived belief strength measure correlates strongly with human typicality ratings and robustly predicts human choices in a base-rate neglect task. Additionally, our method revealed substantial and previously unnoticed variability in stereotype-driven belief strength in popular base-rate items from existing research, underlining the need to control for this in future studies. We further highlight methodological improvements achievable by refining the LLM prompt, as well as ways to enhance cross-cultural validity. The database presented here serves as a powerful resource for researchers, facilitating rigorous, replicable, and theoretically precise experimental designs, as well as enabling advancements in cognitive and computational modeling of reasoning. To support its use, we provide the R package baserater, which allows researchers to access the database to apply or adapt the method to their own research.
Communications Psychology@commspsychol.nature.com · 10mo ago

People and LLMs evaluate deliberative reasoning more favorably than intuitive thinking—even when both yield accurate results. This preference appears to be intuitive itself and has implications for how we assess others’ and AI advise. @wimdeneys.bsky.social www.nature.com/articles/s44...

Humans and LLMs rate deliberation as superior to intuition on complex reasoning tasks - Communications Psychology

People and LLMs evaluate deliberative reasoning more favorably than intuitive thinking—even when both yield accurate results. This preference appears to be intuitive itself and has implications for how we assess others’ and AI advise.

nature.com

Wim De Neys@wimdeneys.bsky.social · 10mo ago

Paper is now published: www.nature.com/articles/s44...

Humans and LLMs rate deliberation as superior to intuition on complex reasoning tasks - Communications Psychology

People and LLMs evaluate deliberative reasoning more favorably than intuitive thinking—even when both yield accurate results. This preference appears to be intuitive itself and has implications for how we assess others’ and AI advise.

nature.com

Wim De Neys@wimdeneys.bsky.social · last yr.

New preprint: “Folk Thinking, Fast and Slow: Intuitive Preference for Deliberation in Humans and Machines” Pop culture often praises intuition (“Blink”, Steve Jobs). But do we really trust it? Across 13 studies, we find a strong intuitive preference for deliberation. tinyurl.com/8r54dmyn (1/6)

Jorge Peña 🇵🇸@jorgeapenas.bsky.social · 11mo ago

📢 Apply to our (2-year) research fellowships at @iast.fr Join a multidisciplinary, interdisciplinary, transdisciplinary, and indisciplinary group of scholars in Toulouse, walkable/cyclable pink city of chocolatines in the South of France. Deadline: November 15, 2025. www.iast.fr/research-fel...

Research Fellowships

Each year, IAST invites applications for post-doctoral Research Fellowships, which offer candidates an opportunity to devote themselves full-time to their research at the start of their careers. Fello...

iast.fr

Wim De Neys@wimdeneys.bsky.social · 12mo ago

Moses, fast and slow ! @jeremiebeucler.bsky.social interesting evidence for sound intuiting (and reflection). My take home: Don't use semantic illusions as a pure test of cognitive reflection.

Jérémie Beucler@jeremiebeucler.bsky.social · 12mo ago

1/8 New (and first) paper accepted at JEP:LMC 🎉 Ever fallen for this type of questions: "How many animals of each kind did Moses take on the Ark?" Most say "Two," forgetting it was Noah, and not Moses, who took the animals on the Ark. But what’s really going on here? 🧵

When asked “How many animals of each kind did Moses take on the Ark?”, most people answer “Two”, failing to notice that it was Noah, and not Moses, who took the animals in the Ark. “Fast-and-slow” dual process accounts of such semantic illusions posit that incorrect responders are not sensitive to their error and that overcoming the illusion requires deliberate correction of an intuitive erroneous answer. We present three experiments that force us to revise this dual process view. We used a two-response paradigm in which participants had to give their first, initial answer under cognitive load and time pressure. Next, participants could take all the time they wanted to deliberate and select a final answer. This enabled us to identify the intuitively generated response that preceded the final response given after deliberation. Results show that participants do not necessarily need to deliberate to avoid the illusion and that incorrect respondents consistently display error sensitivity (as reflected in decreased confidence), even when deliberation is minimized. Both reasoning performance and error sensitivity in the initial, intuitive stage tended to be driven by the semantic relatedness between the anomalous word (e.g., “Moses”) and the undistorted word (e.g., “Noah”). We show how this leads to a revised model where the response to semantic illusions depends on the interplay of both incorrect and correct intuitions.
Wim De Neys@wimdeneys.bsky.social · last yr.

"Defining deliberation for dual-process models of reasoning" is now published. Free online access to the published Nat Rev Psy version: rdcu.be/erM5T

Defining deliberation for dual-process models of reasoning

Nature Reviews Psychology - Dual-process models propose that reasoning involves intuition and deliberation, but the conceptualization of deliberation remains unclear. In this Perspective, De Neys...

rdcu.be

Wim De Neys@wimdeneys.bsky.social · last yr.

New forthcoming perspective paper in Nature Reviews Psychology: “Defining System 2 deliberation for dual-process models” preprint: osf.io/preprints/ps... (1/5)

Wim De Neys@wimdeneys.bsky.social · last yr.

New preprint: “Folk Thinking, Fast and Slow: Intuitive Preference for Deliberation in Humans and Machines” Pop culture often praises intuition (“Blink”, Steve Jobs). But do we really trust it? Across 13 studies, we find a strong intuitive preference for deliberation. tinyurl.com/8r54dmyn (1/6)

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Esther Boissin@boissinesther.bsky.social · 2y ago

Want to challenge your biases and boost your logical reasoning? 🚀 Check out this fantastic website by my amazing colleagues @wimdeneys.bsky.social and @ninafraniatte.bsky.social. Dive into engaging videos that make logical reasoning accessible to everyone. Available in English and French.

Nina Franiatte@ninafraniatte.bsky.social · 2y ago

🧠 Cogitum: Train your logical reasoning! As part of our research, @wimdeneys.bsky.social and I developed video-based training to boost sound reasoning 🎥 And we need your help to test it! Try it anonymously (& share it!) in French or English here: cogitum-site.powerappsportals.com/homePage

Wim De Neys@wimdeneys.bsky.social · 2y ago

New paper with Katerina Voudouri and Michal Bialek showing that when people face risky decisions, they can intuitively determine which choices have better expected value and avoid loss aversion without careful deliberation. www.sciencedirect.com/science/arti...

Fast & slow decisions under risk: Intuition rather than deliberation drives advantageous choices

Would you take a gamble with a 10% chance to gain $100 and a 90% chance to lose $10? Even though this gamble has a positive expected value, most peopl…

sciencedirect.com

Wim De Neys@wimdeneys.bsky.social · 2y ago

"Adieu Bias!": New paper with Nina Franiatte et al. in which we replicated previous intuitive debiasing findings in la douce France. Thanks openAI for the awesome title suggestion ;-)

Nina Franiatte@ninafraniatte.bsky.social · 2y ago

❗New open access paper out with @boissinesther.bsky.social, Alexandra Delmas & @wimdeneys.bsky.social in Psychologica Belgica! 🔗 psychologicabelgica.com/articles/10.... ⬇️ In this paper, we explored whether we could replicate previous debiasing findings among native French speakers. (1/4)