An official website of the United States government
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.
more »
« less
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.
more »
« less
- 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
More Like this
-
-
Fostering public AI literacy has been a growing area of interest at CHI for several years, and a substantial community is forming around issues such as teaching children how to build and program AI systems, designing learning experiences to broaden public understanding of AI, developing explainable AI systems, understanding how novices make sense of AI, and exploring the relationship between public policy, ethics, and AI literacy. Previous workshops related to AI literacy have been held at other conferences (e.g., SIGCSE, AAAI) that have been mostly focused on bringing together researchers and educators interested in AI education in K-12 classroom environments, an important subfield of this area. Our workshop seeks to cast a wider net that encompasses both HCI research related to introducing AI in K-12 education and also HCI research that is concerned with issues of AI literacy more broadly, including adult education, interactions with AI in the workplace, understanding how users make sense of and learn about AI systems, research on developing explainable AI (XAI) for non-expert users, and public policy issues related to AI literacy.more » « less
-
Abstract Artificial intelligence (AI) has long held the promise of imitating, replacing, or even surpassing human intelligence. Now that the abilities of AI systems have started to approach this initial aspiration, organization and management scholars face a challenge in how to theorize this technology, which potentially changes the way we view technology: not as a tool, but as something that enters previously human‐only domains. To navigate this theorizing challenge, we adopt the problematizing review method by engaging in a selective and critical reading of the theoretical contributions regarding AI, in the most influential organization and management journals. We examine how the literature has grounded itself with AI as the root metaphor and what field assumptions about AI are shared – or contested – in the field. We uncover two core assumptions of rationality and anthropomorphism, around which fruitful debates are already emerging. We discuss these two assumptions and their organizational boundary conditions in the context of theorizing AI. Finally, we invite scholars to build distinctive organization and management theory scaffolding within the broader social science of AI.more » « less
-
How can the public sector use AI ethically and responsibly for the benefit of people? The sustainable development and deployment of artificial intelligence (AI) in the public sector requires dialogue and deliberation between developers, decision makers, deployers, end users, and the public. This paper contributes to the debate on how to develop persuasive government approaches for steering the development and use of AI. We examine the ethical issues and the role of the public in the debate on developing public sector governance of socially and democratically sustainable and technology-intensive societies. To concretize this discussion, we study the co-development of a Finnish national AI program AuroraAI, which aims to provide citizens with tailored and timely services for different life situations, utilizing AI. With the help of this case study, we investigate the challenges posed by the development and use of AI in the service of public administration. We draw particular attention to the efforts made by the AuroraAI Ethics Board in deliberating the AuroraAI solution options and working toward a sustainable and inclusive AI society.more » « less
-
Advances in data science and artificial intelligence (AI) offer unprecedented opportunities to provide actionable insights, drive innovative solutions, and create long-term strategies for sustainable development in response to the triple existential crises facing humanity: climate change, pollution, and biodiversity loss. The rapid development of AI models has been the subject of extensive debate and is high on the political agenda, but at present the vast potential for AI to contribute positively to informed decision making, improved environmental risk management, and the development of technological solutions to sustainability challenges remains underdeveloped. In this paper, we consider four inter-dependent areas in which data science and AI can make a substantial contribution to developing sustainable future interactions with the environment: (i) quantification and tracking progress towards the United Nations Sustainable Development Goals; (ii) embedding AI technologies to reduce emissions at source; (iii) developing systems to increase our resilience to natural hazards; (iv) Net Zero and the built environment. We also consider the wider challenges associated with the widespread use of AI, including data access and discoverability, trust and regulation, inference and decision making, and the sustainable use of AI.more » « less
