ReviewBritish journal of psychology (London, England : 1953)2026
Comparability between AI and human cognition and its role in psychological research and AI ethics.
Review in British journal of psychology (London, England : 1953), 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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0 citing papers in PubMed.
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Abstract
With the advances in AI technology, comparison studies between humans and AI can not only enhance our understanding of information processing mechanisms underlying human cognition but also facilitate our understanding of AI systems' behaviour and interactions with humans. In particular, explainable AI (XAI) methods, including both computational and experimental methods, can be used to reveal the mechanisms underlying AI's behaviour and its interactions with humans. This information can be used (1) as computational models to study human behaviour, (2) for updating users' beliefs about AI during the interactions, and (3) for evaluation purposes to examine potential ethical issues associated with AI adoption. Different AI systems may require different XAI methods to accurately reveal their underlying mechanisms to facilitate the comparisons with humans. Thus, an important future research direction is to develop task-specific XAI methods through interdisciplinary approaches across psychology and AI to benefit both psychological research and the development of ethical AI.
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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.