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The objective of this paper is to establish the fundamental public value principles that should govern safe and trusted artificial intelligence (AI). Public value is a dynamic concept that encompasses several dimensions. AI itself has evolved quite rapidly in the last few years, especially with the swift escalation of Generative AI. Governments around the world are grappling with how to govern AI, just as technologists ring alarm bells about the future consequences of AI. Our paper extends the debate on AI governance that is focused on ethical values of beneficence to that of economic values of public good. Viewed as a public good, AI use is beyond the control of the creators. Towards this end, the paper examined AI policies in the United States and Europe. We postulate three principles from a public values perspective: (i) ensuring security and privacy of each individual (or entity); (ii) ensuring trust in AI systems is verifiable; and (iii) ensuring fair and balanced AI protocols, wherein the underlying components of data and algorithms are contestable and open to public debate.
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Net versus relative impacts in public policy automation: a conjoint analysis of attitudes of Black Americans
Abstract The use of algorithms and automated systems, especially those leveraging artificial intelligence (AI), has been exploding in the public sector, but their use has been controversial. Ethicists, public advocates, and legal scholars have debated whether biases in AI systems should bar their use or if the potential net benefits, especially toward traditionally disadvantaged groups, justify even greater expansion. While this debate has become voluminous, no scholars of which we are aware have conducted experiments with the groups affected by these policies about how they view the trade-offs. We conduct a set of two conjoint experiments with a high-quality sample of 973 Americans who identify as Black or African American in which we randomize the levels of inter-group disparity in outcomes and the net effect on such adverse outcomes in two highly controversial contexts: pre-trial detention and traffic camera ticketing. The results suggest that respondents are willing to tolerate some level of disparity in outcomes in exchange for certain net improvements for their community. These results turn this debate from an abstract ethical argument into an evaluation of political feasibility and policy design based on empirics.
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- Award ID(s):
- 2131504
- PAR ID:
- 10523184
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- AI & SOCIETY
- Volume:
- 40
- Issue:
- 4
- ISSN:
- 0951-5666
- Format(s):
- Medium: X Size: p. 2571-2583
- Size(s):
- p. 2571-2583
- Sponsoring Org:
- National Science Foundation
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