research-article

From manifesta to krypta: The relevance of categories for trusting others

Authors:

Michele Piunti,

Matteo Venanzi,

Cristiano CastelfranchiAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology (TIST), Volume 4, Issue 2

Article No.: 27, Pages 1 - 24

https://doi.org/10.1145/2438653.2438662

Published: 03 April 2013 Publication History

Abstract

In this article we consider the special abilities needed by agents for assessing trust based on inference and reasoning. We analyze the case in which it is possible to infer trust towards unknown counterparts by reasoning on abstract classes or categories of agents shaped in a concrete application domain. We present a scenario of interacting agents providing a computational model implementing different strategies to assess trust. Assuming a medical domain, categories, including both competencies and dispositions of possible trustees, are exploited to infer trust towards possibly unknown counterparts. The proposed approach for the cognitive assessment of trust relies on agents' abilities to analyze heterogeneous information sources along different dimensions. Trust is inferred based on specific observable properties (manifesta), namely explicitly readable signals indicating internal features (krypta) regulating agents' behavior and effectiveness on specific tasks. Simulative experiments evaluate the performance of trusting agents adopting different strategies to delegate tasks to possibly unknown trustees, while experimental results show the relevance of this kind of cognitive ability in the case of open multiagent systems.

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Cited By

Kollerup NWester JSkov Mvan Berkel N(2024)How Can I Signal You To Trust Me: Investigating AI Trust Signalling in Clinical Self-AssessmentsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661612(525-540)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661612
Centeio Jorge CJonker CTielman M(2024)Interdependence and trust analysis (ITA): a framework for human–machine team designBehaviour & Information Technology10.1080/0144929X.2024.2431631(1-21)Online publication date: 25-Nov-2024
https://doi.org/10.1080/0144929X.2024.2431631
Jorge CJonker CTielman M(2023)How Should an AI Trust its Human Teammates? Exploring Possible Cues of Artificial TrustACM Transactions on Interactive Intelligent Systems10.1145/363547514:1(1-26)Online publication date: 6-Dec-2023
https://dl.acm.org/doi/10.1145/3635475
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Index Terms

From manifesta to krypta: The relevance of categories for trusting others
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
  2. Symbolic and algebraic manipulation
    1. Symbolic and algebraic algorithms
      1. Theorem proving algorithms

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Published In

cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 4, Issue 2

Special section on agent communication, trust in multiagent systems, intelligent tutoring and coaching systems

March 2013

339 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/2438653

Issue’s Table of Contents

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 April 2013

Accepted: 01 April 2011

Revised: 01 March 2011

Received: 01 August 2010

Published in TIST Volume 4, Issue 2

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Cited By

Kollerup NWester JSkov Mvan Berkel N(2024)How Can I Signal You To Trust Me: Investigating AI Trust Signalling in Clinical Self-AssessmentsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661612(525-540)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3643834.3661612
Centeio Jorge CJonker CTielman M(2024)Interdependence and trust analysis (ITA): a framework for human–machine team designBehaviour & Information Technology10.1080/0144929X.2024.2431631(1-21)Online publication date: 25-Nov-2024
https://doi.org/10.1080/0144929X.2024.2431631
Jorge CJonker CTielman M(2023)How Should an AI Trust its Human Teammates? Exploring Possible Cues of Artificial TrustACM Transactions on Interactive Intelligent Systems10.1145/363547514:1(1-26)Online publication date: 6-Dec-2023
https://dl.acm.org/doi/10.1145/3635475
Ulfert AGeorganta ECenteio Jorge CMehrotra STielman M(2023)Shaping a multidisciplinary understanding of team trust in human-AI teams: a theoretical frameworkEuropean Journal of Work and Organizational Psychology10.1080/1359432X.2023.220017233:2(158-171)Online publication date: 20-Apr-2023
https://doi.org/10.1080/1359432X.2023.2200172
Centeio Jorge CTielman MJonker CSakamoto DWeiss AHiatt LShiomi M(2022)Artificial Trust as a Tool in Human-AI TeamsProceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction10.5555/3523760.3523956(1155-1157)Online publication date: 7-Mar-2022
https://dl.acm.org/doi/10.5555/3523760.3523956
Templeton JTran T(2022)Cluster‐based improvement rates for trust establishment models in single or distributed multi‐agent systemsComputational Intelligence10.1111/coin.1254638:5(1884-1919)Online publication date: 29-Aug-2022
https://doi.org/10.1111/coin.12546
Jorge CTielman MJonker C(2022)Artificial Trust as a Tool in Human-AI Teams2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI)10.1109/HRI53351.2022.9889652(1155-1157)Online publication date: 7-Mar-2022
https://doi.org/10.1109/HRI53351.2022.9889652
Falcone RSapienza A(2020)Recommendations In The Virtual Societies: Some Considerations2020 IEEE International Conference on Human-Machine Systems (ICHMS)10.1109/ICHMS49158.2020.9209507(1-4)Online publication date: Sep-2020
https://doi.org/10.1109/ICHMS49158.2020.9209507
Dragos VDezert JRein K(2019)Assessment of Trust in Opportunistic Reporting using Belief Functions2019 22th International Conference on Information Fusion (FUSION)10.23919/FUSION43075.2019.9011281(1-8)Online publication date: Jul-2019
https://doi.org/10.23919/FUSION43075.2019.9011281
Falcone RSapienza A(2017)Using Sources Trustworthiness in Weather Scenarios: The Special Role of the AuthorityAI*IA 2017 Advances in Artificial Intelligence10.1007/978-3-319-70169-1_1(3-16)Online publication date: 7-Nov-2017
https://doi.org/10.1007/978-3-319-70169-1_1
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