Artificial agents’ explainability to support trust: considerations on timing and context

Strategies for improving the explainability of artificial agents are a key approach to support the understandability of artificial agents’ decision-making processes and their trustworthiness. However, since explanations are not inclined to standardization, finding solutions that fit the algorithmic-...

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Bibliographic Details
Published in:AI & society 2023-04, Vol.38 (2), p.947-960
Main Authors: Papagni, Guglielmo, de Pagter, Jesse, Zafari, Setareh, Filzmoser, Michael, Koeszegi, Sabine T.
Format: Article
Language:English
Subjects:
Agents (artificial intelligence)
Artificial Intelligence
Computer Science
Control
Decision making
Engineering Economics
Logistics
Marketing
Mechatronics
Methodology of the Social Sciences
Network Research
Organization
Performing Arts
Restoration strategies
Robotics
Standardization
Trustworthiness
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Summary:Strategies for improving the explainability of artificial agents are a key approach to support the understandability of artificial agents’ decision-making processes and their trustworthiness. However, since explanations are not inclined to standardization, finding solutions that fit the algorithmic-based decision-making processes of artificial agents poses a compelling challenge. This paper addresses the concept of trust in relation to complementary aspects that play a role in interpersonal and human–agent relationships, such as users’ confidence and their perception of artificial agents’ reliability. Particularly, this paper focuses on non-expert users’ perspectives, since users with little technical knowledge are likely to benefit the most from “post-hoc”, everyday explanations. Drawing upon the explainable AI and social sciences literature, this paper investigates how artificial agent’s explainability and trust are interrelated at different stages of an interaction. Specifically, the possibility of implementing explainability as a trust building, trust maintenance and restoration strategy is investigated. To this extent, the paper identifies and discusses the intrinsic limits and fundamental features of explanations, such as structural qualities and communication strategies. Accordingly, this paper contributes to the debate by providing recommendations on how to maximize the effectiveness of explanations for supporting non-expert users’ understanding and trust.
ISSN:0951-5666
1435-5655
DOI:10.1007/s00146-022-01462-7