ArticleWellcome open research2026
The missing discipline in AI: a call for behavioural science.
Article in Wellcome open research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence systems increasingly shape how people think, feel, and act, particularly in high-impact domains such as healthcare, education, and social support. While significant attention has been paid to technical performance, bias, privacy, and security, the behavioural impacts of AI systems remain under-evaluated and under-governed. This Open Letter outlines why behavioural science should be treated as a core component of responsible AI practice. Even when technically accurate, AI systems can influence behaviour in ways that are harmful, misleading, or misaligned with people's interests. These effects are often predictable consequences of repeated human-AI interaction, yet they are rarely assessed systematically. We describe where behavioural risks arise in practice and outline what good practice looks like, drawing on established behavioural science methods. We then propose practical steps for funders, researchers, and developers to embed behavioural science expertise and behavioural evaluation across the AI lifecycle, including behavioural testing pipelines, longitudinal evaluation, and interdisciplinary governance. Addressing behavioural impacts is essential to ensuring that AI systems are not only effective, but safe, trustworthy, and appropriate for real-world use.
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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.