AI Ethics in the Public, Private, and NGO Sectors: A Review of a Global Document Collection

IEEE Transactions on Technology and Society · 2021 · 128 citations

• Political Science
• Political Science
• Public relations

In recent years, numerous public, private, and non-governmental organizations (NGOs) have produced documents addressing the ethical implications of artificial intelligence (AI). These normative documents include principles, frameworks, and policy strategies that articulate the ethical concerns, priorities, and associated strategies of leading organizations and governments around the world. We examined 112 such documents from 25 countries that were produced between 2016 and the middle of 2019. While other studies identified some degree of consensus in such documents, our work highlights meaningful differences across public, private, and NGO sectors. We analyzed each document in terms of how many of 25 ethical topics were covered and the depth of discussion for those topics. As compared to documents from private entities, NGO and public sector documents reflect more ethical breadth in the number of topics covered, are more engaged with law and regulation, and are generated through processes that are more participatory. These findings may reveal differences in underlying beliefs about an organization's responsibilities, the relative importance of relying on experts versus including representatives from the public, and the tension between prosocial and economic goals.

What's Next for AI Ethics, Policy, and Governance? A Global Overview

2020 · 164 citations

• Political Science
• Computer Science
• Sociology

Since 2016, more than 80 AI ethics documents - including codes, principles, frameworks, and policy strategies - have been produced by corporations, governments, and NGOs. In this paper, we examine three topics of importance related to our ongoing empirical study of ethics and policy issues in these emerging documents. First, we review possible challenges associated with the relative homogeneity of the documents' creators. Second, we provide a novel typology of motivations to characterize both obvious and less obvious goals of the documents. Third, we discuss the varied impacts these documents may have on the AI governance landscape, including what factors are relevant to assessing whether a given document is likely to be successful in achieving its goals.