Advanced Studies in Human-Centred AI
A special issue of Behavioral Sciences (ISSN 2076-328X). This special issue belongs to the section "Cognition".
Deadline for manuscript submissions: closed (31 October 2025) | Viewed by 1164
Special Issue Editor
Special Issue Information
Dear Colleagues,
Human-centred AI puts human behaviour and experience at the heart of artificial intelligence research. For example, it is sometimes claimed that artificial neural networks (ANNs) now perform at human levels in a variety of tasks—to what extent is this claim substantiated by the evidence? Does that performance, human-level or otherwise, extend to replicating (or perhaps amplifying) well-documented biases in human decision-making? Can ANNs effectively and safely be used to support the work of highly trained professionals—for example, radiologists, therapists, legal advisors, or researchers? Can we effectively adapt the skills and techniques of behavioural research, previously applied to humans and other animals, to better understand the ‘psychology’ of complex black-box ANNs? To what extent can our understanding of how humans explain their decisions inform explainable AI? What makes an AI system seem trustworthy, and is that trust well placed? Can people spontaneously distinguish real photographs and videos from deepfakes—and, if not, can they be trained to do so? Can work on goal-setting and reinforcement learning in humans inform agentic behaviour and AI alignment? If the technical issues of AI alignment are indeed solvable, to what values should they be aligned? We welcome original papers on these and related topics in human-centred AI. The papers may be theoretical, empirical, or both. They may report new findings, or synthetically review the existing literature.
Prof. Dr. Andy J. Wills
Guest Editor
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Keywords
- human-centred AI
- neural networks
- AGI
- bias
- decision-making
- therapy
- healthcare
- experimental psychology
- explainable AI
- trust and trustworthiness
- deepfake detection
- AI alignment
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