Context-dependent preferences for a decision support system's level of automation

Abstract

Many organizations use decision support systems (DSS) to support DSS users in their daily work demands (e.g., high workload, insufficient information, ambiguous situations). A key question regarding their interaction is how the decision-control is divided between the DSS and the user, represented by the system's level of automation (LoA). To investigate the need for an adaptable DSS where users can manually adjust the LoA across situations, we used a vignette design to examine whether users prefer different LoA in different situations (i.e., six situational criteria, each manipulated by two specifications; e.g., low vs. high workload). In the twelve vignettes, the 116 participants should imagine working in an emergency control-center—a setting they were familiar with from previous experiments. Our results showed significant differences between the two corresponding vignettes, indicating that users prefer different LoA across situations. However, after controlling for the participants' overall preference for a situation-independent baseline LoA, the significant differences between all paired vignettes disappear. Our results have implications for whether situational or individual criteria are more important regarding LoA preferences, adaptable DSS, and for human-centered design based on user profiles. We discuss our findings in relation to the broader literature on trust and acceptance of DSS.

Keywords

• Level of automation
• Human–computer interaction
• Adaptable systems
• Artificial intelligence
• Participatory design
• Human-centered design