COMPARING JUDGMENT AND TEMPORAL EVOLUTION OF TRUST BETWEEN ARTIFICIAL INTELLIGENCE SUPPORTED DECISION-MAKING AND HUMAN SUPPORTED DECISION-MAKING

Decision support systems underpin the Department of Defense’s Command and Control apparatus, feeding into decision-making processes at all levels. The extant research surrounding Artificial Intelligence’s (AI’s) use in decision support systems establishes trust as a critical driver of such systems’ performance and adoption. However, little research has explored the impacts of temporal factors and the existence of intermediate decisions on a decision-maker’s level of trust in such systems or how the impacts differ when the decision is supported by another human versus an AI. Extant literature assumes trust in AI is different than other objects of trust. This thesis explores this assumption by asking whether the emergence of trust depends more on the object or source of trust. A previous experiment examined the impacts of time and intermediate judgements on trust when the decision support was provided by an AI-system only. This thesis extends that experiment by also manipulating the source of the decision-support, to be human, not just AI. By including the base case of human-to-human trust, this research enables comparative analysis regarding the relative impact of intermediate judgments and time on trust in decision-support systems.Distribution Statement A. Approved for public release: Distribution is unlimited.Outstanding ThesisMajor, United States Marine CorpsMajor, United States Marine Corp