Communicating trust-based beliefs and decisions in human-AI teams using visual summaries of explanations

Bachelor Thesis (2024)
Author(s)

S. Marossi (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

C. Centeio Jorge – Mentor (TU Delft - Interactive Intelligence)

Myrthe Lotte Tielman – Mentor (TU Delft - Interactive Intelligence)

Ujwal Gadiraju – Graduation committee member (TU Delft - Web Information Systems)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2024
Language
English
Graduation Date
27-06-2024
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Human-agent teams (HATs) are becoming more prevalent in our current world, necessitating mutual trust between humans and machines. This trust is split into artificial trust (agents trusting humans) and natural trust (humans trusting agents). Both types must be facilitated for effective teamwork. It is hypothesized that communicating artificial trust effectively helps develop natural trust and overall satisfaction. A visual summary of explanations is proposed to serve as an effective communication method. Summaries allow for in-depth information processing, and visual representations are quicker to interpret. This paper examines the impact of using a visual summary of explanations to communicate the agent’s trust beliefs on the human teammate’s natural trust and overall satisfaction within HATs. An experiment (n=40) was conducted to study this effect. Participants collaborated with an artificial agent during an urban search and rescue operation in a simulated 2D grid-world environment. Results show that the inclusion of a visual summary increases the human teammate’s trust in the agent alongside their overall satisfaction. The paper emphasizes the need for further research with longitudinal studies to measure the long-term effectiveness of communicating artificial trust.

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