Name: Emanuel Rojas

Master’s Thesis Proposal Meeting

Date: Monday, May 20, 2024

Time: 10:00 am- 11:00am (virtual on Microsoft Teams).

link to the teams meeting: click here

Advisor: Mengyao Li, Ph.D. (Georgia Tech)

Thesis Committee Members:

Mengyao Li, Ph.D. (Georgia Tech)

Richard Catrambone, Ph.D. (Georgia Tech)

Rick Thomas, Ph.D. (Georgia Tech)

Title: Trust Contagion: Repairing Trust in Human-Human-AI Teaming

Abstract: Human teams are integrating autonomous agents as team members to increase efficiency in human-agent teams (HAT). Autonomous agents are systems, usually powered through AI, with some degree of autonomy that can communicate and collaborate with humans to achieve team mutual goals. Autonomous agents, just like humans, can make errors during the task. These errors can decrease people’s trust and potentially lead to failed cooperation. For this reason, repairing trust is essential for people to calibrate their trust and properly rely on the autonomous agent for team cooperation and performance. Past literature mainly emphasized dyadic human-autonomy teams for trust repair, yet real-life contexts often involve multiple humans and automation. In multi-human teams, individuals can consciously or subconsciously influence others’ teammates trust and behaviors when cooperating with autonomous agents, known as trust contagion. The proposed study aims to investigate whether the effects of trust contagion can be a medium of repairing trust towards the agent. The study is a 2 (agent reliability: high vs. low, within-subjects factor) x 2 (confederate trusting: high and neutral, between-subjects factor) mixed-subject design. A team of three—participant, confederate, and autonomous agent—will engage in a ten-round trust-based cooperative game. Trust will be measured through subjective ratings, behavioral responses in the game, and in-game conversations. We hypothesized trust in a virtual agent is contagious by another human, positive trust contagion from a human teammate can repair trust in the agent, and interpersonal trust between humans mediates participant’s trust in the agent. Planned analyses involve an optimal linear mixed model to measure trust contagion. For the second hypothesis, a paired t-test will assess trust repair within conditions and an independent t-test will compare changed trust values between rounds 5 and 10 across conditions. For the third hypothesis, a mediational model will investigate whether participants' interpersonal trust towards the confederate mediates their trust in the virtual agent. Implications if trust repair through trust contagion is possible, then it suggests multi-human teams as the optimal configuration to sustain trust towards automation.