The Impact of a Strategy of Deception About the Identity of an Artificial Intelligence Teammate on Human Designers

Abstract

Advances in artificial intelligence (AI) offer new opportunities for human-AI collaboration in engineering design. Human trust in AI is a crucial factor in ensuring an effective human-AI collaboration, and several approaches to enhance human trust in AI have been suggested in prior studies. However, it remains an open question in engineering design whether a strategy of deception about the identity of an AI teammate can effectively calibrate human trust in AI and improve human-AI joint performance. This research assesses the impact of the strategy of deception on human designers through a human subjects study where half of participants are told that they work with an AI teammate (i.e., without deception), and the other half of participants are told that they work with another human participant but in fact they work with an AI teammate (i.e., with deception). The results demonstrate that, for this study, the strategy of deception improves high proficiency human designers’ perceived competency of their teammate. However, the strategy of deception does not raise the average number of team collaborations and does not improve the average performance of high proficiency human designers. For low proficiency human designers, the strategy of deception does not change their perceived competency and helpfulness of their teammate, and further reduces the average number of team collaborations while hurting their average performance at the beginning of the study. The potential reasons behind these results are discussed with an argument against using the strategy of deception in engineering design.