AI Ethics and Policymaking: Rawlsian Approaches to Democratic Participation, Transparency, Accountability, and Prediction

20 Pages Posted: 31 May 2023

See all articles by Morten Bay

Morten Bay

USC Annenberg School For Communication and Journalism

Date Written: May 27, 2023

Abstract

The AI ethics field is seeing an increase in explorations of theoretical ethics in addition to applied ethics, and this has spawned a renewed interest in John Rawls’ theory of justice as fairness and how it may apply to AI. But how may these new, Rawlsian contributions inform regulatory policies for AI? This article takes a Rawlsian approach to four key policy criteria in AI regulation: Democratic participation, transparency, accountability, and the epistemological value of prediction. Rawlsian, democratic participation in the light of AI is explored through a critique of Ashrafian’s proposed approach to Rawlsian AI ethics, which is found to contradict other aspects of Rawls’ theories. A turn toward Gabriel’s foundational theoretical work on Rawlsian justice in AI follows, extending his explication of Rawls’ Publicity criterion to an exploration of how the latter can be applied to real-world AI regulation and policy. Finally, a discussion of a key AI feature, prediction, demonstrates how AI-driven, long-term, large-scale predictions of human behavior violate Rawls’ justice as fairness principles. It is argued that applications of this kind are expressions of the type of utilitarianism Rawls vehemently opposes, and therefore cannot be allowed in Rawls-inspired policymaking.

Keywords: John Rawls, AI ethics, AI regulation, AI policy, transparency, accountability, prediction, democratic participation, basic structure, well-ordered society, difference principle

Suggested Citation

Bay, Morten, AI Ethics and Policymaking: Rawlsian Approaches to Democratic Participation, Transparency, Accountability, and Prediction (May 27, 2023). Available at SSRN: https://ssrn.com/abstract=4461219 or http://dx.doi.org/10.2139/ssrn.4461219

Morten Bay (Contact Author)

USC Annenberg School For Communication and Journalism ( email )

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
170
Abstract Views
554
Rank
325,108
PlumX Metrics