Stahl, B. C., Antoniou, J., Ryan, M., Macnish, K. and Jiya, T. (2021) Organisational responses to the ethical issues of artificial intelligence. AI & SOCIETY. 37(1), pp. 23-37. 1435-5655.
Stahl_etal_AI&Society_2021_Organisational_Responses_To_The_Ethical_Issues_of_Artificial_Intelligence (1MB) |
| Item Type: | Article |
|---|---|
| Abstract: | The ethics of artificial intelligence (AI) is a widely discussed topic. There are numerous initiatives that aim to develop the principles and guidance to ensure that the development, deployment and use of AI are ethically acceptable. What is generally unclear is how organisations that make use of AI understand and address these ethical issues in practice. While there is an abundance of conceptual work on AI ethics, empirical insights are rare and often anecdotal. This paper fills the gap in our current understanding of how organisations deal with AI ethics by presenting empirical findings collected using a set of ten case studies and providing an account of the cross-case analysis. The paper reviews the discussion of ethical issues of AI as well as mitigation strategies that have been proposed in the literature. Using this background, the cross-case analysis categorises the organisational responses that were observed in practice. The discussion shows that organisations are highly aware of the AI ethics debate and keen to engage with ethical issues proactively. However, they make use of only a relatively small subsection of the mitigation strategies proposed in the literature. These insights are of importance to organisations deploying or using AI, to the academic AI ethics debate, but maybe most valuable to policymakers involved in the current debate about suitable policy developments to address the ethical issues raised by AI. |
| Uncontrolled Keywords: | artificial intelligence, Ethics, AI Policy, Organisational response, case study, Artificial Intelligence, Human-Computer Interaction, Philosophy |
| Creators: | Stahl, Bernd Carsten, Antoniou, Josephina, Ryan, Mark, Macnish, Kevin and Jiya, Tilimbe |
| Faculties, Divisions and Institutes: | Faculties > Faculty of Business & Law > Business Systems & Operations |
| Date: | 16 February 2021 |
| Date Type: | Publication |
| Page Range: | pp. 23-37 |
| Journal or Publication Title: | AI & SOCIETY |
| Volume: | 37 |
| Number: | 1 |
| Number of Pages: | 15 |
| Language: | English |
| DOI: | https://doi.org/10.1007/s00146-021-01148-6 |
| ISSN: | 1435-5655 |
| Status: | Published / Disseminated |
| Refereed: | Yes |
| Related URLs: | |
| URI: | http://nectar.northampton.ac.uk/id/eprint/14398 |
Actions (login required)
 |
Edit Item |
Altmetric
Altmetric