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Collective Reflective Equilibrium in Practice (CREP) and controversial novel technologies
Author(s) -
Savulescu Julian,
Gyngell Christopher,
Kahane Guy
Publication year - 2021
Publication title -
bioethics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.494
H-Index - 55
eISSN - 1467-8519
pISSN - 0269-9702
DOI - 10.1111/bioe.12869
Subject(s) - reflective equilibrium , coherence (philosophical gambling strategy) , process (computing) , function (biology) , public policy , preference , sociology , public relations , political science , psychology , social psychology , economics , computer science , law , microeconomics , physics , quantum mechanics , evolutionary biology , biology , operating system
Abstract In this paper, we investigate how data about public preferences may be used to inform policy around the use of controversial novel technologies, using public preferences about autonomous vehicles (AVs) as a case study. We first summarize the recent ‘Moral Machine’ study, which generated preference data from millions of people regarding how they think AVs should respond to emergency situations. We argue that while such preferences cannot be used to directly inform policy, they should not be disregarded. We defend an approach that we call ‘Collective Reflective Equilibrium in Practice’ (CREP). In CREP, data on public attitudes function as an input into a deliberative process that looks for coherence between attitudes, behaviours and competing ethical principles. We argue that in cases of reasonable moral disagreement, data on public attitudes should play a much greater role in shaping policies than in areas of ethical consensus. We apply CREP to some of the global preferences about AVs uncovered by the Moral Machines study. We intend this discussion both as a substantive contribution to the debate about the programming of ethical AVs, and as an illustration of how CREP works. We argue that CREP provides a principled way of using some public preferences as an input for policy, while justifiably disregarding others.