Psychological and behavioural responses in human-agent vs. human-human interactions: a systematic review and meta-analysis
Not on the map. Why?
Abstract (arXiv)
Interactive intelligent agents are being integrated across society. Despite achieving human-like capabilities, humans' responses to these agents remain poorly understood, with research fragmented across disciplines. We conducted a first systematic synthesis comparing a range of psychological and behavioural responses in matched human-agent vs. human-human dyadic interactions. A total of 162 eligible studies (146 contributed to the meta-analysis; 468 effect sizes) were included in the systematic review and meta-analysis, which integrated frequentist and Bayesian approaches. Our results indicate that individuals exhibited less prosocial behaviour and moral engagement when interacting with agents vs. humans. They attributed less agency and responsibility to agents, perceiving them as less competent, likeable, and socially present. In contrast, individuals' social alignment (i.e., alignment or adaptation of internal states and behaviours with partners), trust in partners, personal agency, task performance, and interaction experiences were generally comparable when interacting with agents vs. humans. We observed high effect-size heterogeneity for many subjective responses (i.e., social perceptions of partners, subjective trust, and interaction experiences), suggesting context-dependency of partner effects. By examining the characteristics of studies, participants, partners, interaction scenarios, and response measures, we also identified several moderators shaping partner effects. Overall, functional behaviours and interactive experiences with agents can resemble those with humans, whereas fundamental social attributions and moral/prosocial concerns lag in human-agent interactions. Agents are thus afforded instrumental value on par with humans but lack comparable intrinsic value, providing practical implications for agent design and regulation.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 16 of its 127 references that are in the map. First posted on arXiv 25 Sep 2025.
Builds on
16 of 127 references.
References · 16
- 2020Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Databasecited by 96
- 2024Large language models surpass human experts in predicting neuroscience resultscited by 69
- 2025Why human-AI relationships need socioaffective alignmentcited by 47
- 2025An Approach to Technical AGI Safety and Securitycited by 45
- 2023ALYMPICS: LLM Agents Meet Game Theory -- Exploring Strategic Decision-Making with AI Agentscited by 33
- 2024From Explainable to Interactive AI: A Literature Review on Current Trends in Human-AI Interactioncited by 26
- 2022UX Research on Conversational Human-AI Interaction: A Literature Review of the ACM Digital Librarycited by 20
- 2025As Confidence Aligns: Exploring the Effect of AI Confidence on Human Self-confidence in Human-AI Decision Makingcited by 19
- 2023Does GPT-4 surpass human performance in linguistic pragmatics?cited by 16
- 2025The AI Agent Indexcited by 15
- 2024Multi-Agent, Human-Agent and Beyond: A Survey on Cooperation in Social Dilemmascited by 12
- 2021Software-Based Dialogue Systems: Survey, Taxonomy and Challengescited by 11
4 more
Built on by
Citing papers per year: 2026: 2.
2 papers.