Title
Appropriate context-dependent artificial trust in human-machine teamwork
Author
Centeio Jorge, C. (TU Delft Interactive Intelligence) 
van Zoelen, E.M. (TU Delft Interactive Intelligence; TNO)
Verhagen, R.S. (TU Delft Interactive Intelligence)
Mehrotra, S. (TU Delft Interactive Intelligence)
Jonker, C.M. (TU Delft Interactive Intelligence; Universiteit Leiden)
Tielman, M.L. (TU Delft Interactive Intelligence)
Contributor
Dasgupta, Prithviraj (editor)
Llinas, James (editor)
Gillespie, Tony (editor)
Fouse, Scott (editor)
Lawless, William (editor)
Mittu, Ranjeev (editor)
Sofge, Donald (editor)
Date
2024
Abstract
As human-machine teams become a more common scenario, we need to ensure mutual trust between humans and machines. More important than having trust, we need all teammates to trust each other appropriately. This means that they should not overtrust or undertrust each other, avoiding risks and inefficiencies, respectively. We usually think of natural trust, that is, humans trusting machines, but we should also consider artificial trust, that is, artificial agents trusting humans. Appropriate artificial trust allows the agents to interpret human behavior and predict their behavior in a certain context. In this chapter, we explore how we can define this context in terms of task and team characteristics. We present a taxonomy that shows how trust is context-dependent. In fact, we propose that no trust model presented in the literature fits all contexts and argue that our taxonomy facilitates the choice of the trust model that better fits a certain context. The taxonomy helps to understand which internal characteristics of the teammate (krypta) are important to consider and how they will show in behavior cues (manifesta). This taxonomy can also be used to help human-machine teams’ researchers in the problem definition and process of experimental design as it allows a detailed characterization of the task and team configuration. Furthermore, we propose a formalization of the belief of trust as context-dependent trustworthiness, and show how beliefs of trust can be used to reach appropriate trust. Our work provides a starting point to implement mutual appropriate trust in human-machine teams.
Subject
Human-machine teams
HART
Artificial trust
Appropriate trust
Taxonomy
Context-dependent trust
To reference this document use:
http://resolver.tudelft.nl/uuid:02b64aba-ce12-4be1-bced-567906be8ab1
DOI
https://doi.org/10.1016/B978-0-443-15988-6.00007-8
Publisher
Academic Press
Embargo date
2024-08-23
ISBN
9780443159879
Source
Putting AI in the Critical Loop: Assured Trust and Autonomy in Human-Machine Teams
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
book chapter
Rights
© 2024 C. Centeio Jorge, E.M. van Zoelen, R.S. Verhagen, S. Mehrotra, C.M. Jonker, M.L. Tielman