Performance Trust in High-Stakes Heterogeneous Human-Machine Teams: Insights from Interviews with Team CoSTAR and Mars 2020

Boyoung Kim, Jordan Jannone, Zulma Lopez Rodriguez, Rachel Huerta, Elijah Sagaran, Nathalie Ochoa, Daria Shubina, Benjamin Morrell, Michael Milano, Marcel Kaufmann, Nhut T. Ho

Abstract: We examined how trust is conceptualized toward both humans and robots in heterogeneous human-machine teams. Based on interviews from Team CoSTAR (DARPA Subterranean Challenge) and the Mars 2020 mission, we employed a mixed-methods approach combining content analysis, thematic analysis, and text mining. Performance trust emerged as the dominant dimension across both teammate types, though distinct factors shaped how it was applied to humans versus robots. Moral trust was limited, particularly toward robots. This work contributes to understanding how trust is formed and differentiated in high-stakes contexts involving real machines and real human teammates operating in environments with real consequences.

External IDs:dblp:conf/ro-man/KimJRHSOSMMKH25