# Towards a Conversational Measure of Trust

arXiv: https://arxiv.org/abs/2010.04885 · HTML: https://mlsanity.com/paper/2010.04885/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Oct 2020.

## Built on by (most cited first, 1 of 1)

- [AI-HRI Brings New Dimensions to Human-Aware Design for Human-Aware AI](https://mlsanity.com/paper/2210.11832/) (2022)

## Abstract (arXiv)

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.