Expert responsibility in AI development
Open accessAbstract
The purpose of this paper is to discuss the responsibility of AI experts for guiding the development of AI in a desirable direction. More specifically, the aim is to answer the following research question: To what extent are AI experts responsible in a forward-looking way for effects of AI technology that go beyond the immediate concerns of the programmer or designer? AI experts, in this paper conceptualised as experts regarding the technological aspects of AI, have knowledge and control of AI technology that non-experts do not have. Drawing on responsibility theory, theories of the policy process, and critical algorithm studies, we discuss to what extent this capacity, and the positions that these experts have to influence the AI development, make AI experts responsible in a forward-looking sense for consequences of the use of AI technology. We conclude that, as a professional collective, AI experts, to some extent, are responsible in a forward-looking sense for consequences of use of AI technology that they could foresee, but with the risk of increased influence of AI experts at the expense of other actors. It is crucial that a diversity of actors is included in democratic processes on the future development of AI, but for this to be meaningful, AI experts need to take responsibility for how the AI technology they develop affects public deliberation.
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AI algorithms are often trained on unrepresentative data, leading to potential discrimination and disadvantages for certain patient groups.
“AI algorithms are often trained on unrepresentative data, leading to potential discrimination and disadvantages for certain patient groups.”
From Proposing a Principle-Based Approach for Teaching AI Ethics in Medical Education (2024) · cites this paper as [4]
Bias on the part of developers can result in inequitable treatment.
“Bias on the part of developers can also result in inequitable treatment [4].”
From Proposing a Principle-Based Approach for Teaching AI Ethics in Medical Education (2024) · cites this paper as [4]
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Sorted by citations
Proposing a Principle-Based Approach for Teaching AI Ethics in Medical Education
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- Authors
- Hedlund, M., & Persson, E.
- Affiliations
- Lund University (SE)
- Corresponding author
- Hedlund, Maria
- Venue
- AI & SOCIETY
- Published
- 2022-06-13
- Volume
- 39
- Issue
- 2
- Pages
- 453-464
- ISSN
- 0951-5666 (ISSN-L)
- 1435-5655
- OpenAlex
- W4282829606
- Cited by
- 39
- References
- 36
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 9 · 2023: 13
- FWCI
- 9.26
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- AI & Society (publishedVersion, cc-by)
- Lund University Publications (Lund University) (submittedVersion)
- Funders
- Marianne and Marcus Wallenberg Foundation (MMW 2018.020)
- Lund University
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Keywords
- expert responsibility, AI development, policy process, critical algorithm studies, deliberative democracy, professional expertise, unintended consequences of AI
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