Impact of agent reliability and predictability on trust in real time human-agent collaboration

Research output: Contribution to conferencePaper

Abstract

Trust is a prerequisite for effective human-agent collaboration. While past work has studied how trust relates to an agent's reliability, it has been mainly carried out in turn based scenarios, rather than during real-time ones. Previous research identified the performance of an agent as a key factor influencing trust. In this work, we posit that an agent's predictability also plays an important role in the trust relationship, which may be observed based on users' interactions. We designed a 2x2 within-groups experiment with two baseline conditions: (1) no agent (users' individual performance), and (2) near-flawless agent (upper bound). Participants took part in an interactive aiming task where they had to collaborate with different agents that varied in terms of their predictability, and were controlled in terms of their performance. Our results show that agents whose behaviours are easier to predict have a more positive impact on task performance, reliance and trust while reducing cognitive workload. In addition, we modelled the human-agent trust relationship and demonstrated that it is possible to reliably predict users' trust ratings using real-time interaction data. This work seeks to pave the way for the development of trust-aware agents capable of adapting and responding more appropriately to users.
Original languageEnglish
Number of pages9
DOIs
Publication statusAccepted/In press - 3 Aug 2020
EventInternational Conference on Human-Agent Interaction - Online Event, Sydney, Australia
Duration: 10 Nov 202013 Nov 2020
Conference number: 8
http://hai-conference.net/hai2020/

Conference

ConferenceInternational Conference on Human-Agent Interaction
Abbreviated titleHAI 2020
CountryAustralia
CitySydney
Period10/11/2013/11/20
Internet address

Keywords

  • human-virtual agent interaction
  • HAI experimental methods
  • gaming and serious games

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