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Value alignment without institutional change cannot prevent the societal risks of Artificial Intelligence

Value alignment without institutional change cannot prevent the societal risks of Artificial Intelligence

Ferretti, Thomas ORCID logoORCID: https://orcid.org/0000-0003-4683-883X (2024) Value alignment without institutional change cannot prevent the societal risks of Artificial Intelligence. LSE Public Policy Review, 3 (3):2. pp. 1-12. ISSN 2633-4046 (Online) (doi:10.31389/lseppr.113)

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Abstract

One approach to mitigating the societal risks of Artificial Intelligence (AI) is value alignment, which aims to ensure that AI systems operate in ways that align with societal values. To complement this approach, one can adopt an institutionalist approach which looks at how AI systems interact with the social institutions in which they operate. This matters because the major background institutions of what John Rawls calls the ‘basic structure of society’ significantly influence the effects of new technologies. Consequently, societies with different basic structures will experience different effects of the same technology. In many cases, AI systems do not create new problems but merely reveal and amplify pre-existing vulnerabilities in our social institutions. In such cases, I argue that value alignment alone cannot mitigate the societal risks of AI unless underlying institutional vulnerabilities are addressed. Therefore, profound institutional change, sometimes to seemingly unrelated background institutions, is necessary to benefit from AI while mitigating risks.

Item Type: Article
Uncontrolled Keywords: Artificial Intelligence, ethics, governance, institutions
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
Faculty / School / Research Centre / Research Group: Greenwich Business School
Greenwich Business School > Executive Business Centre
Last Modified: 06 Nov 2024 14:59
URI: http://gala.gre.ac.uk/id/eprint/48551

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