Large language models (LLMs) and the institutionalization of misinformation
Abstract
Large language models (LLMs), such as ChatGPT, flood the Internet with true and false information, crafted and delivered with techniques that psychological science suggests will encourage people to think that information is true. What's more, as people feed this misinformation back into the Internet, emerging LLMs will adopt it and feed it back in other models. Such a scenario means we could lose access to information that helps us tell what is real from unreal - to do 'reality monitoring.' If that happens, misinformation will be the new foundation we use to plan, to make decisions, and to vote. We will lose trust in our institutions and each other.
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These tools are designed to sound confident, and we are worrisomely prone to trust confident fluency, in AI and people.
“Yet these tools are designed to sound confident, and we are worrisomely prone to trust confident fluency, in AI and people (Garry et al. 2024);”
From Large language models and the problem of rhetorical debt (2025) · cites this paper as Garry et al. 2024
Cites
On seeing human: A three-factor theory of anthropomorphism
Epley, N., Waytz, A., & Cacioppo, J. T. (2007) · Psychological Review · doi:10.1037/0033-295x.114.4.864 · Cited by 4,069 · see citing works
Semantic integration of verbal information into a visual memory
Loftus, E. F., Miller, D. G., & Burns, H. J. (1978) · Journal of Experimental Psychology: Human Learning and Memory · doi:10.1037/0278-7393.4.1.19 · Cited by 1,511 · see citing works
The psychological drivers of misinformation belief and its resistance to correction
Ecker, U. K. H., Lewandowsky, S., Cook, J., Schmid, P., Fazio, L. K., Brashier, N., Kendeou, P., Vraga, E. K., & Amazeen, M. A. (2022) · Nature Reviews Psychology · doi:10.1038/s44159-021-00006-y · Cited by 1,372 · see citing works
Pennycook, G., & Rand, D. G. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2021.02.007 · Cited by 1,360 · see citing works
A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly
Yao, Y., Duan, J., Xu, K., Cai, Y., Sun, Z., & Zhang, Y. (2024) · High-Confidence Computing · doi:10.1016/j.hcc.2024.100211 · Cited by 1,083 · see citing works
Frequency and the conference of referential validity
Hasher, L., Goldstein, D., & Toppino, T. (1977) · Journal of Verbal Learning and Verbal Behavior · doi:10.1016/s0022-5371(77)80012-1 · Cited by 920 · see citing works
Deep Fakes: A Looming Challenge for Privacy, Democracy, and National Security
Chesney, R., & Citron, D. K. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3213954 · Cited by 880 · see citing works
Artificial intelligence and illusions of understanding in scientific research
Messeri, L., & Crockett, M. J. (2024) · Nature · doi:10.1038/s41586-024-07146-0 · Cited by 707 · see citing works
Misunderstanding the harms of online misinformation
Budak, C., Nyhan, B., Rothschild, D. M., Thorson, E., & Watts, D. J. (2024) · Nature · doi:10.1038/s41586-024-07417-w · Cited by 156 · see citing works
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Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges
Chhabra, A., Datta, S., Nahin, S. K., & Mohapatra, P. (2026) · IEEE Access · doi:10.1109/access.2026.3675554 · Cited by 28 · see citing works
“These agents have the potential to act in unpredictable ways, overcome human limitations, and expose users to a series of negative consequences, such as disinformation and hijacking [170, 171].”
Large language models and the problem of rhetorical debt
MacArthur, M. (2025) · AI & SOCIETY · doi:10.1007/s00146-025-02403-w · Cited by 8 · see citing works
“Yet these tools are designed to sound confident, and we are worrisomely prone to trust confident fluency, in AI and people (Garry et al. 2024); the “con” in “con man” stands, of course, for confidence (see Herman Melville’s 1857 novel The Confidence Man ).”
- Authors
- Garry, M., Chan, W. M., Foster, J., & Henkel, L. A.
- Affiliations
- University of Waikato (NZ)
- Macquarie University (AU)
- Fairfield University (US)
- Corresponding author
- Garry, Maryanne
- Venue
- Trends in Cognitive Sciences
- Publisher
- Elsevier BV
- Published
- 2024-12
- Volume
- 28
- Issue
- 12
- Pages
- 1078-1088
- ISSN
- 1364-6613 (ISSN-L)
- OpenAlex
- W4403296982
- Semantic Scholar
- cdf640b5ad7edcd7525a6c04642709f9a86cf421
- Cited by
- 33
- References
- 9
- Citations by year
- 2026: 12 · 2025: 17 · 2024: 4
- FWCI
- 3.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Trends in Cognitive Sciences (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Arts and Humanities › Philosophy › Epistemology, Ethics, and Metaphysics
- Keywords
- large language models, misinformation, reality monitoring, ChatGPT, institutional trust, decision-making
- MeSH terms
- Communication, Humans, Language, Models, Theoretical, Internet
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