Explainability increases trust resilience in intelligent agents
Bibliographic Data
| ID | 9619346 |
|---|---|
| Authors | Min Xu (0000-0002-8940-1614, School of Economics and Management Fuzhou University Fuzhou China), Yiwen Wang (0000-0002-6879-8974, School of Business Administration Zhejiang Gongshang University Hangzhou China, corresponding author) |
| Year | 2024 |
| Volume | 117 |
| Issue | 2 |
| Pages | 528-547 |
| Publication date | 2024-10-21 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | British Journal of Psychology (JOURNAL) |
| Journal identifiers | ISSN: 0007-1269 • E-ISSN: 2044-8295 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/bjop.12740 |
| PMID | 39431949 |
| OpenAlex | W4403603341 |
| Language | EN |
| Citations received | 3 |
| References cited | 49 |
Even though artificial intelligence (AI)‐based systems typically outperform human decision‐makers, they are not immune to errors, leading users to lose trust in them and be less likely to use them again—a phenomenon known as algorithm aversion. The purpose of the present research was to investigate whether explainable AI (XAI) could function as a viable strategy to counter algorithm aversion. We conducted two experiments to examine how XAI influences users' willingness to continue using AI‐based systems when these systems exhibit errors. The results showed that, following the observation of algorithms erring, the inclination of users to delegate decisions to or follow advice from intelligent agents significantly decreased compared to the period before the errors were revealed. However, the explainability effectively mitigated this decline, with users in the XAI condition being more likely to continue utilizing intelligent agents for subsequent tasks after seeing algorithms erring than those in the non‐XAI condition. We further found that the explainability could reduce users' decision regret, and the decrease in decision regret mediated the relationship between the explainability and re‐use behaviour. These findings underscore the adaptive function of XAI in alleviating negative user experiences and maintaining user trust in the context of imperfect AI
Context (archaeology) · Delegate · Economics · Function (biology) · Imperfect · Machine learning · Microeconomics · Preference · Regret · Artificial Intelligence · Computer Science · Decision-Making and Behavioral Economics · Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI · Psychology · Social Psychology
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Regret
| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |