The DOI matches its Crossref record; 45 of the 46 references it cites were found in a registry or an index.
Explanation and trust: what to tell the user in security and AI?
Open accessAbstract
There is a common problem in artificial intelligence (AI) and information security. In AI, an expert system needs to be able to justify and explain a decision to the user. In information security, experts need to be able to explain to the public why a system is secure. In both cases, an important goal of explanation is to acquire or maintain the users’ trust. In this paper, I investigate the relation between explanation and trust in the context of computing science. This analysis draws on literature study and concept analysis, using elements from system theory as well as actor-network theory. I apply the conceptual framework to both AI and information security, and show the benefit of the framework for both fields by means of examples. The main focus is on expert systems (AI) and electronic voting systems (security). Finally, I discuss consequences of the analysis for ethics in terms of (un)informed consent and dissent, and the associated division of responsibilities.
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“Without a careful study on these psychological issues before implementing in practice, 6G could cause catastrophic consequences and even deconstruct existing trust in ICTs [81].”
From What should 6G be? (2020) · cites this paper as [81]
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“However, quality assurance requires thorough attention to guarantee safe and reliable behaviour and increase the accountability and responsibility of the involved AI systems [38, 47, 13, 23].”
From The pipeline for the continuous development of artificial intelligence models—Current state of research and practice (2023) · cites this paper as [38]
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“AI characteristics such as the inherent non-determinism lead to a certain degree of uncertainty [46, 47, 38].”
From The pipeline for the continuous development of artificial intelligence models—Current state of research and practice (2023) · cites this paper as [38]
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Citations
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Cited by
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Human trust in artificial intelligence: Review of empirical research
Glikson, E., & Woolley, A. W. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0057 · Cited by 2,921
Dang, S., Amin, O., Shihada, B., & Alouini, M.-S. (2020) · Nature Electronics · doi:10.1038/s41928-019-0355-6 · Cited by 1,790
"I always assumed that I wasn't really that close to [her]"
Eslami, M., Rickman, A., Vaccaro, K., Aleyasen, A., Vuong, A., Karahalios, K. G., Hamilton, K., & Sandvig, C. (2015) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702556 · Cited by 781
Langer, M., Oster, D., Speith, T., Hermanns, H., Kästner, L., Schmidt, E., Sesing, A., & Baum, K. (2021) · Artificial Intelligence · doi:10.1016/j.artint.2021.103473 · Cited by 652
How Much Information?: Effects of Transparency on Trust in an Algorithmic Interface
Kizilcec, R. F. (2016) · Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858402 · Cited by 615
Metadata
- Authors
- Pieters, W.
- Affiliations
- University of Twente (NL)
- Corresponding author
- Pieters, Wolter
- ORCID
- Pieters, Wolter
- Venue
- Ethics and Information Technology
- Published
- 2010-11-03
- Volume
- 13
- Issue
- 1
- Pages
- 53-64
- ISSN
- 1388-1957 (ISSN-L)
- 1572-8439
- OpenAlex
- W2133761762
- Cited by
- 153
- References
- 46
- Citations by year
- 2026: 11 · 2025: 20 · 2024: 17 · 2023: 15 · 2022: 28 · 2021: 19 · 2020: 13 · 2019: 6 · 2018: 4 · 2017: 6 · 2016: 2 · 2015: 4 · 2014: 4 · 2013: 3
- FWCI
- 1.35
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Ethics and Information Technology (publishedVersion, cc-by-nc)
- University of Twente Research Information (publishedVersion)
- University of Twente Research Information (submittedVersion, other-oa)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Stichting voor de Technische Wetenschappen
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Computer Networks and Communications › Access Control and Trust
- Keywords
- explanation, trust, artificial intelligence, information security, expert systems, electronic voting, justification of decisions, actor-network theory, systems theory, informed consent, dissent, division of responsibilities, AI ethics
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