Artificial Intelligence and Responsible Innovation

Abstract

Researchers in AI often highlight the importance of socially responsible research, but the current literature on the social impacts of AI tends to focus on particular application domains and provides little guidance to researchers working in other areas. Additionally, such social impact analysis tends to be done in a one-off fashion, proposing or problematizing a particular aspect of AI at a time, rather than being deeply integrated into innovation processes across the field. This paper argues that work on the societal dimensions of AI can be enriched by engagement with the literature on “responsible innovation,” which has up until now focused on technical domains like nanotechnology, synthetic biology, and geoengineering. Drawing on this literature, the paper describes and justifies three interrelated aspects of what a more deeply integrated, ongoing practice of responsibility in AI would look like: consideration of the social contexts and consequences of decisions in the AI design space; reflectiveness about one’s emphasis on theoretical vs. applied work and choice of application domains; and engagement with the public about what they desire from AI and what they need to know about it. Mapping out these three issues, it is argued, can both describe and theorize existing work in a more systematic light and identify future opportunities for research and practice on the societal dimensions of AI. Finally, the paper describes how philosophical and theoretical aspects of AI connect to issues of responsibility and technological governance.