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AI apology: a critical review of apology in AI systems
Open accessAbstract
Apologies are a powerful tool used in human-human interactions to provide affective support, regulate social processes, and exchange information following a trust violation. The emerging field of AI apology investigates the use of apologies by artificially intelligent systems, with recent research suggesting how this tool may provide similar value in human-machine interactions. Until recently, contributions to this area were sparse, and these works have yet to be synthesised into a cohesive body of knowledge. This article provides the first synthesis and critical analysis of the state of AI apology research, focusing on studies published between 2020 and 2023. We derive a framework of attributes to describe five core elements of apology: outcome, interaction, offence, recipient, and offender. With this framework as the basis for our critique, we show how apologies can be used to recover from misalignment in human-AI interactions, and examine trends and inconsistencies within the field. Among the observations, we outline the importance of curating a human-aligned and cross-disciplinary perspective in this research, with consideration for improved system capabilities and long-term outcomes.
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“Consequently, users may accept a CA apology at an emotional level while still perceiving the system as unreliable for future interactions, rendering the decision to continue using the system contingent on unresolved uncertainty about its reliability (Gnewuch & Reinkemeier, 2025;Harland et al., 2025;Kim & Song, 2021).”
From Explainability in AI: Comparing Human-Like and System-Like Trust Repair Strategies (2026) · cites this paper as Harland et al., 2025
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Metadata
- Authors
- Harland, H., Dazeley, R., Senaratne, H., Vamplew, P., Cruz, F., & Nakisa, B.
- Affiliations
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Deakin University (AU)
- Federation University (AU)
- UNSW Sydney (AU)
- Corresponding author
- Harland, Hadassah
- ORCID
- Venue
- Artificial Intelligence Review
- Published
- 2025-10-06
- Volume
- 58
- Issue
- 12
- ISSN
- 0269-2821 (ISSN-L)
- 1573-7462
- OpenAlex
- W4414849137
- Cited by
- 19
- References
- 222
- Citations by year
- 2026: 15 · 2025: 4
- FWCI
- 21.05
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Artificial Intelligence Review (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- arXiv (Cornell University) (cc-by)
- Funders
- Deakin University
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Keywords
- apology, human-AI interaction, breach of trust, crime, emotional support, social regulation
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