Calibrating workers' trust in intelligent automated systems.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 39568648.
- Also identified by DOI 10.1016/j.patter.2024.101045 and PMC identifier 11573890.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
With the exponential rise in the prevalence of automation, trust in such technology has become more critical than ever before. Trust is confidence in a particular entity, especially in regard to the consequences they can have for the trustor, and calibrated trust is the extent to which the judgments of trust are accurate. The focus of this paper is to reevaluate the general understanding of calibrating trust in automation, update this understanding, and apply it to worker's trust in automation in the workplace. Seminal models of trust in automation were designed for automation that was already common in workforces, where the machine's "intelligence" (i.e., capacity for decision making, cognition, and/or understanding) was limited. Now, burgeoning automation with more human-like intelligence is intended to be more interactive with workers, serving in roles such as decision aid, assistant, or collaborative coworker. Thus, we revise "calibrated trust in automation" to include more intelligent automated systems.