A Longitudinal Study of Trust Calibration Methods with Individual Differences

Abstract

Trust has been considered a critical factor affecting the performance, experience and overall outcome of a collaborative team, whether the teammate is a human or a machine. Existing research has revealed that trust can be affected by many factors arising from the machine side, including the performance of a machine or system, the way information is presented and the context of interaction. However, the human aspects of the interaction, especially individual differences, have a strong impact on the inter-personal trust as well, although so far very little has been done to depict the full trust picture of human-machine interaction, i.e. to link individual differences to machine performance, which is partially due to the deficiency of objective means to longitudinally track trust change in human-machine interaction. As a consequence, this research proposal aims at examining human-machine trust, with a special focus on objective trust calibration and further to understand the implication of individual differences, e.g. personality traits or cultural differences for human’s trust in a machine and its development afterwards. Longitudinal investigation methods will be adopted as the interplay between personality, familiarity and machine performance in the long run is the key to achieve accurate depiction of a human’s trust profile and capture the interaction pattern.

Document Details

Document Type
DoD Grant Award
Publication Date
Aug 28, 2018
Source ID
FA23861814091

Entities

People

  • Fang Chen

Organizations

  • Air Force Office of Scientific Research
  • Commonwealth Scientific and Industrial Research Organisation
  • United States Air Force

Tags

Fields of Study

  • Computer science

Readers

  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Theoretical Analysis.