An exploratory qualitative analysis of AI ethics guidelines

Abstract

Purpose As Big Data and Artificial Intelligence (AI) proliferate, calls have emerged for ethical reflection. Ethics guidelines have played a central role in this respect. While quantitative research on the ethics guidelines of AI/Big Data has been undertaken, there has been a dearth of systematic qualitative analyses of these documents. Design/methodology/approach Aiming to address this research gap, this paper analyses 70 international ethics guidelines documents from academia, NGOs and the corporate realm, published between 2017 and 2020. Findings The article presents four key findings: existing ethics guidelines (1) promote a broad spectrum of values; (2) focus principally on AI, followed by (Big) Data and algorithms; (3) do not adequately define the term “ethics” and related terms; and (4) have most frequent recourse to the values of “transparency,” “privacy,” and “security.” Based on these findings, the article argues that the guidelines corpus exhibits discernible utilitarian tendencies; guidelines would benefit from greater reflexivity with respect to their ethical framework; and virtue ethical approaches have a valuable contribution to make to the process of guidelines development. Originality/value The paper provides qualitative insights into the ethical discourse surrounding AI guidelines, as well as a concise overview of different types of operative translations of theoretical ethical concepts vis-à-vis the sphere of AI. These may prove beneficial for (applied) ethicists, developers and regulators who understand these guidelines as policy.

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