Trusting Automation: Designing for Responsivity and Resilience

OBJECTIVE

This paper reviews recent articles related to human trust in automation to guide research and design for increasingly capable automation in complex work environments.

BACKGROUND

Two recent trends-the development of increasingly capable automation and the flattening of organizational hierarchies-suggest a reframing of trust in automation is needed.

METHOD

Many publications related to human trust and human-automation interaction were integrated in this narrative literature review.

RESULTS

Much research has focused on calibrating human trust to promote appropriate reliance on automation. This approach neglects relational aspects of increasingly capable automation and system-level outcomes, such as cooperation and resilience. To address these limitations, we adopt a relational framing of trust based on the decision situation, semiotics, interaction sequence, and strategy. This relational framework stresses that the goal is not to maximize trust, or to even calibrate trust, but to support a process of trusting through automation responsivity.

CONCLUSION

This framing clarifies why future work on trust in automation should consider not just individual characteristics and how automation influences people, but also how people can influence automation and how interdependent interactions affect trusting automation. In these new technological and organizational contexts that shift human operators to co-operators of automation, automation responsivity and the ability to resolve conflicting goals may be more relevant than reliability and reliance for advancing system design.

APPLICATION

A conceptual model comprising four concepts-situation, semiotics, strategy, and sequence-can guide future trust research and design for automation responsivity and more resilient human-automation systems.

Positive bias in the ‘Trust in Automated Systems Survey’? An examination of the Jian et al. (2000) scale

Measuring trust in technology is a mainstay in Human Factors research. While trust may not perfectly predict reliance on technology or compliance with alarm signals, it is routinely used as a design consideration and assessment goalpost. Several methods of measuring trust have been employed in the past decades, but one self-report measure stands out due to its popular use, the Trust in Automated Systems Survey (Jian, Bisantz, & Drury, 2000). We conducted a study to assess whether the survey could create biased responses, and found evidence the original scale is in fact skewed toward positive ratings. Assessing the literature revealed the survey has been used in unaltered form across at least 100 different reports and remains frequently administered – therefore, the potential impact of this bias may be widespread. Future directions, considerations, and caveats for our assessment, and for using this scale, are discussed.