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University of Michigan School of Information


Connor Esterwood

Connor Esterwood kneeling and looking at a machine.


My research investigates the capacity of robots to repair and restore trust in the aftermath of trust violations. Robots are technological entities that combine artificial intelligence with physical materiality, leading humans to perceive them as social agents and collaborative teammates. Trust is a vital component of any successful collaboration, but it is fragile, dynamic, and at times easily broken. A literature review suggests that while there are methods to rebuild and restore trust, the effectiveness of trust repairs carried out by robots can vary greatly. My research aims to expand on existing theories of trust repair by investigating the underlying mechanisms that contribute to successful trust repair between humans and robots. Ultimately, the goal is to enhance the development of robots that can successfully rebuild trust with humans, thereby improving the overall interaction between humans and machines.

View Connor's CV

In the News 

Selected Press Coverage of Research 

Communications of the ACM 
Trust Is Hard to Restore After Robot Co-Worker Makes Mistakes 

Current Science Daily 
U. of Michigan study: Humans not tolerant of robot mistakes 

When robots screw up, how can they regain human trust?

World Economic Forum 
Here's why we struggle to trust robots after a few mistakes

University of Michigan News 
Robots who goof: Can we trust them again? 
Robot: I’m sorry. Human: I don’t care anymore!

Robotics and Automation News 
Three strikes and you’re out! Humans give up on robots after multiple mistakes 

The distrust of robots among AI users is growing

Selected Publications

Esterwood, C., & Robert Jr, L. P. (2023). The theory of mind and human–robot trust repairScientific Reports, 13(1), 9877.

Esterwood, C., & Robert Jr, L. P. (2023). Three Strikes and you are out!: The impacts of multiple human–robot trust violations and repairs on robot trustworthiness. Computers in Human Behavior, 142, 107658.

Esterwood, C., Essenmacher, K., Yang, H., Zeng, F., & Robert, L. P. (2022). A Personable Robot: Meta-analysis of Robot Personality and Human Acceptance. IEEE Robotics and Automation Letters, 7(3), 6918-6925.

Esterwood, C., & Robert, L. P. (2022). Having the Right Attitude: How Attitude Impacts Trust Repair in Human—Robot Interaction. Proceedings of the 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2022).

Esterwood, C., Essenmacher, K., Yang, H., Zeng, F., & Robert, L. (2021). A Meta-Analysis of Human Personality and Robot Acceptance in Human-Robot Interaction. The 2021 ACM CHI Virtual Conference on Human Factors in Computing Systems (CHI 2021).