Comment on Novozhilova et al. More Capable, Less Benevolent: Trust Perceptions of AI Systems across Societal Contexts. Mach. Learn. Knowl. Extr. 2024, 6, 342

Comment on Novozhilova et al. More Capable, Less Benevolent: Trust Perceptions of AI Systems across Societal Contexts. Mach. Learn. Knowl. Extr. 2024, 6, 342–366

Published:2024-07-22 Issue:3 Volume:6 Page:1667-1669
ISSN:2504-4990
Container-title:Machine Learning and Knowledge Extraction
language:en
Short-container-title:MAKE

Author:

Damaševičius Robertas¹^ORCID

Affiliation:

1. Centre of Real Time Computer Systems, Kaunas University of Technology, 51424 Kaunas, Lithuania

Abstract

The referenced article [...]

Publisher

MDPI AG

Link

https://www.mdpi.com/2504-4990/6/3/81/pdf

Reference12 articles.

1. More Capable, Less Benevolent: Trust Perceptions of AI Systems across Societal Contexts;Novozhilova;Mach. Learn. Knowl. Extr.,2024

2. Trust in AI and Its Role in the Acceptance of AI Technologies;Choung;Int. J. Hum.-Comput. Interact.,2022

3. Using agent features to influence user trust, decision making and task outcome during human-agent collaboration;Herse;Int. J. Hum.-Comput. Interact.,2023

4. Towards responsible AI: A design space exploration of human-centered artificial intelligence user interfaces to investigate fairness;Nakao;Int. J. Hum.-Comput. Interact.,2022

5. Danks, D. (2019, January 27–28). The Value of Trustworthy AI. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, Honolulu, HI, USA.

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1. Reply to Damaševičius, R. Comment on “Novozhilova et al. More Capable, Less Benevolent: Trust Perceptions of AI Systems across Societal Contexts. Mach. Learn. Knowl. Extr. 2024, 6, 342–366”;Machine Learning and Knowledge Extraction;2024-07-22