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

Abstract

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 non-governmental organizations. 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.

Putting AI ethics to work: are the tools fit for purpose?

“…This study contributes to the discussion about ethical AI by clarifying the different themes emerging in this landscape. It also serves to illustrate how complex this landscape is, and as others have noted [7,19,98,102,104,105], this provides a barrier to those developing or purchasing AI systems as to which tool is appropriate for their purposes.…”

A Value Sensitive Design Perspective on AI Biases

“…(10) Sustainability Sustainability refers to the development and deployment of AI to protect the environment, improve the planet's ecosystem and biodiversity, and creating more equal societies. (11) Solidarity Solidarity refers to sharing the prosperity created by AI and assessing the long-term implications before developing and deploying AI systems [18].…”

“…While some research focuses on the technical aspects of AI such as reshaping data processing and analysis [7], other research pays attention to organizational and societal impacts of AI such as the use and effects of AI applications in a variety of sectors including healthcare, transportation, and the production chain [8]. Recent work highlights the need to address emerging AI challenges through responsible development of AI and the need for participatory engagement in the creation of documents addressing the ethical implications of AI across organizations in all sectors [9,10,11]. Mapping system design onto principles for social good has also become the focus of recent explorations [12].…”

An Ontology for Standardising Trustworthy AI

“…More broadly, co-regulation is challenged by: the pacing problem, as AI technology develops faster than society's ability to legislate for it; international cooperation needed for common standards being impeded by AI's perceived role as a strategic economic or military resource; the perceived impediments of legislation to realising the competitive national economic and social benefits of AI; and the power asymmetry in AI capability being concentrated in digital platforms benefiting from network effects [9]. Over all types of works, a wide range of motivation have been identified [18], the incompatibility of some of which can further impede consensus on approaches to implementing trustworthy AI.…”