Organisational responses to the ethical issues of artificial intelligence

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.

From AI ethics principles to data science practice: a reflection and a gap analysis based on recent frameworks and practical experience

“…The willingness of actors to engage with AI ethics has been further confirmed Stahl et al, who put forward that European organizations are not only aware of ethical issues surrounding AI, but that they are also willing to assume responsibility for actively engaging with them [60]. At the same time, organizations are reported to focus only on a limited set of issues and mitigation measures, maintaining that a number of ethical concerns lie beyond the scope of their expertise and remit, and suggesting the need for a broader stakeholder framework to ensure a comprehensive engagement and coverage of AI ethics [60].…”

“…Our work with public authorities, for instance, shows that public bodies are aware of AI ethics and checklists on national level, but struggle to single-handedly align them with EU-level guidance and often look for external help in the translation process [30]. Studies further show that organizations have the capacity to deal with only on a limited set of issues and mitigation measures during the rolling out of a service, suggesting the need for a broader stakeholder framework to ensure a comprehensive engagement and coverage of AI ethics [60].…”

On the Contribution of Neuroethics to the Ethics and Regulation of Artificial Intelligence

“…A common objection found in the literature is that current AI guidelines risk being ineffective because of their level of abstraction and the difficulty in translating them into action-oriented recommendations [7,50,51]. Accordingly, there have been recent attempts to focus on how actual organizations understand and address the ethical issues raised by AI [52] and to develop frameworks for actionability of the guidelines [53,54]. Efforts to address this issue include providing preliminary landscape assessments (so as to bridge the distinction between what should be done and what can actually be done), calling for a richer engagement with diverse representative publics (so as to expand the scope of voices typically heard in the discussion of the issues), and for the creation of inclusive mechanisms for implementation.…”

AI Ethics Principles in Practice: Perspectives of Designers and Developers

“…Governments and organisations are beginning to develop mechanisms to make high-level AI ethics frameworks more actionable in practice. Governance, regulation, and legal frameworks concerning the development and use of AI systems and associated technologies are emerging in many countries [9], [10]. The EU has recently proposed a legal framework for AI for its member states [11].…”