ORCID Profile
0000-0002-6490-3247
Current Organisation
University of Oxford
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Publisher: Project MUSE
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 28-02-2012
DOI: 10.1007/S00213-012-2657-5
Abstract: Implicit negative attitudes towards other races are important in certain kinds of prejudicial social behaviour. Emotional mechanisms are thought to be involved in mediating implicit “outgroup” bias but there is little evidence concerning the underlying neurobiology. The aim of the present study was to examine the role of noradrenergic mechanisms in the generation of implicit racial attitudes. Healthy volunteers ( n = 36) of white ethnic origin, received a single oral dose of the β-adrenoceptor antagonist, propranolol (40 mg), in a randomised, double-blind, parallel group, placebo-controlled, design. Participants completed an explicit measure of prejudice and the racial implicit association test (IAT), 1–2 h after propranolol administration. Relative to placebo, propranolol significantly lowered heart rate and abolished implicit racial bias, without affecting the measure of explicit racial prejudice. Propranolol did not affect subjective mood. Our results indicate that β-adrenoceptors play a role in the expression of implicit racial attitudes suggesting that noradrenaline-related emotional mechanisms may mediate negative racial bias. Our findings may also have practical importance given that propranolol is a widely used drug. However, further studies will be needed to examine whether a similar effect can be demonstrated in the course of clinical treatment.
Publisher: Springer Science and Business Media LLC
Date: 22-04-2015
Publisher: Elsevier BV
Date: 02-2013
Publisher: Wiley
Date: 04-05-2021
DOI: 10.1111/BIOE.12869
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.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Guy Kahane.