Impact of agents' errors on performance, reliance and trust in human-agent collaboration

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Trust in automation is often strongly tied to an agent’s performance. However, our understanding of imperfect agents’ behaviours and its impact on trust is limited. In this paper, we study the relationship between performance, reliance and trust in a set of human-agent collaborative tasks. Participants collaborated with different automated agents that performed similarly but made errors in different ways; namely mistakes (error of prioritization), lapses (error of omission) and slips (lowered accuracy). We conducted a 4x2 within-subjects experiment (n=24) varying the agent behaviours (no error, slips, mistakes and lapses) and task difficulty (easy/hard) during a real-time collaborative game. Our results show that, at the same level of agent performance, agents’ errors are perceived differently and change the way participants interact with agents. For instance, slips and mistakes are more harmful to performance than lapses while slips are more harmful to reliance than mistakes.
Original languageEnglish
Pages (from-to)405-409
Number of pages5
JournalProceedings of the Human Factors and Ergonomics Society Annual Meeting
Issue number1
Early online date14 Jul 2020
Publication statusPublished - 9 Feb 2021
EventHuman Factors and Ergonomics Society Annual Meeting - Virtual Conference, Chicago, United States
Duration: 5 Oct 20209 Oct 2020
Conference number: 64


  • human factors
  • agents
  • AI
  • game
  • human-agent collaboration
  • HCI
  • performance
  • cognitive load
  • trust


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