DEMOCRATIC INNOVATIONS WORKSHOP
Abstract: Government agencies are increasingly using AI-based systems to make high-stakes policy decisions (e.g., on policing, welfare, education). In some cases, this has sparked substantial backlash, as people have confronted AI-guided decisions or grown aware of their use. How do views on the use of AI in guiding public policy decisions form and evolve in response to personal experience with the technology and to learning about its implications? We explore these questions through an experiment conducted in a real-world online labor marketplace. We track the attitudes of over 1,500 workers, where the boss who allocates them to tasks (human vs. AI) as well as the tasks’ content and valence are randomly assigned. Over a three-wave panel, we find that personal experience with AI-as-boss affected workers’ behavior on the job, but not their attitudes toward AI guiding various policy decisions. In contrast, exposure to information about the technology brought significant attitudinal change over time. The findings provide insight into the formation of attitudes on using AI in policy decisions and the potential politicization of this issue.
Shir Raviv is a postdoctoral researcher at the Data Science Institute at Columbia University and a non-resident fellow at the Democratic Innovations Program at ISPS. Her research focuses on the politics of AI and the public debate over its regulation. She employs surveys and field experiments to explore the conditions under which citizens are willing to accept the use of AI across various policy domains and how these views evolve over time as people become more engaged with the technology and its implications.
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