ReviewNature human behaviour2024
How large language models can reshape collective intelligence.
Review in Nature human behaviour, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Payoff selectivity drives collective intelligence during dynamic resource tracking in humans.Nature communications · 2026Article
- A concordance between patent and trademark classes to link technologies to markets.Scientific data · 2026Article
- Moral stereotyping in large language models.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- A large-scale evaluation of commonsense knowledge in humans and large language models.PNAS nexus · 2026Article
- Toward a science of human-AI teaming for decision making: A complementarity framework.PNAS nexus · 2026Article
- Large language models show Dunning-Kruger-like effects in multilingual fact-checking.Scientific reports · 2026Article
- Large reasoning models are autonomous jailbreak agents.Nature communications · 2026Article
- From Isolation to Collaboration: Data Trading Mechanism in the Era of Large Language Model Democratization.Research (Washington, D.C.) · 2026Article
- Teamwork Cognitive Diagnostic Modeling.Psychometrika · 2025Article
- Investigating toxicity and Bias in stable diffusion text-to-image models.Scientific reports · 2025Article
- Generative artificial intelligence-mediated confirmation bias in health information seeking.Annals of the New York Academy of Sciences · 2025Review
- Human-AI collectives most accurately diagnose clinical vignettes.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Patient agency and large language models in worldwide encoding of equity.NPJ digital medicine · 2025Review
- AI-enhanced collective intelligence.Patterns (New York, N.Y.) · 2024Review
- Embracing the ubiquity of machines.Nature human behaviour · 2024Article
- SEMbeddings: how to evaluate model misfit before data collection using large-language models.Frontiers in psychology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
28 authors.
Funding
Abstract
Collective intelligence underpins the success of groups, organizations, markets and societies. Through distributed cognition and coordination, collectives can achieve outcomes that exceed the capabilities of individuals-even experts-resulting in improved accuracy and novel capabilities. Often, collective intelligence is supported by information technology, such as online prediction markets that elicit the 'wisdom of crowds', online forums that structure collective deliberation or digital platforms that crowdsource knowledge from the public. Large language models, however, are transforming how information is aggregated, accessed and transmitted online. Here we focus on the unique opportunities and challenges this transformation poses for collective intelligence. We bring together interdisciplinary perspectives from industry and academia to identify potential benefits, risks, policy-relevant considerations and open research questions, culminating in a call for a closer examination of how large language models affect humans' ability to collectively tackle complex problems.
Indexed as
Identifiers
39304760What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.