English

Towards a Conversational Measure of Trust

Human-Computer Interaction 2020-10-13 v1

Abstract

The increasingly collaborative decision-making process between humans and agents demands a comprehensive, continuous, and unobtrusive measure of trust in agents. The gold standard format for measuring trust, a Likert-style survey, suffers from major limitations in dynamic human-agent interactions. We proposed a new approach to evaluate trust in a nondirective and relational conversation. The term nondirective refers to abstract word selections in open-ended prompts, which can probe respondents to freely describe their attitudes. The term relational refers to interactive conversations where respondents can clarify their responses in followup questions. We propose a systematic process for generating nondirective trust-based prompts by using text analysis from previously validated trust scales. This nondirective and relational approach provides a complementary trust measurement, which can unobtrusively elicit rich and dynamic information on situational trust throughout a human-agent interaction.

Keywords

Cite

@article{arxiv.2010.04885,
  title  = {Towards a Conversational Measure of Trust},
  author = {Mengyao Li and Areen Alsaid and Sofia I. Noejovich and Ernest V. Cross and John D. Lee},
  journal= {arXiv preprint arXiv:2010.04885},
  year   = {2020}
}