[PUBLISHED] A Theoretical Model to Explain Mixed Effects of Trust Repair Strategies in Autonomous Systems

Our recent paper has been accepted for publication.

Pak, R., & Rovira, E. (2023). A Theoretical Model to Explain Mixed Effects of Trust Repair Strategies in Human-Machine Interaction. Theoretical Issues in Ergonomics Science.

An uncorrected preprint is available here.

Abstract: The topic of an autonomous system initiating trust repair has generated intense interest from researchers and has led to a stream of empirical works studying the impact of different trust repair strategies.  Unfortunately, there does not seem to be a clear pattern of results or systematicity in the experimental manipulations. This is likely due to a lack of a coherent model or theoretical framework of trust repair.  We present a possible theoretical model that may explain and predict how different trust repair strategies may work with different autonomous systems, in different situations, and with different people.  We have adapted and applied a well-established social cognition theory that has successfully explained and predicted complex attitudinal and behavioural phenomena.  The model suggests that significant variance in trust repair results may be partly due to individual differences (e.g., motivation, cognitive abilities), which have not been extensively examined in the literature, and confounded or uncontrolled study parameters (e.g., timing of trust measurement, repair frequency, workload).  We hope that this theoretical model stimulates discussion toward a more theory-driven trust repair research agenda to understand basic underlying mechanisms.