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Deceptive uses of Artificial Intelligence in elections strengthen support for AI ban (2408.12613v1)

Published 8 Aug 2024 in cs.CY and cs.AI

Abstract: All over the world, political parties, politicians, and campaigns explore how AI can help them win elections. However, the effects of these activities are unknown. We propose a framework for assessing AI's impact on elections by considering its application in various campaigning tasks. The electoral uses of AI vary widely, carrying different levels of concern and need for regulatory oversight. To account for this diversity, we group AI-enabled campaigning uses into three categories -- campaign operations, voter outreach, and deception. Using this framework, we provide the first systematic evidence from a preregistered representative survey and two preregistered experiments (n=7,635) on how Americans think about AI in elections and the effects of specific campaigning choices. We provide three significant findings. 1) the public distinguishes between different AI uses in elections, seeing AI uses predominantly negative but objecting most strongly to deceptive uses; 2) deceptive AI practices can have adverse effects on relevant attitudes and strengthen public support for stopping AI development; 3) Although deceptive electoral uses of AI are intensely disliked, they do not result in substantial favorability penalties for the parties involved. There is a misalignment of incentives for deceptive practices and their externalities. We cannot count on public opinion to provide strong enough incentives for parties to forgo tactical advantages from AI-enabled deception. There is a need for regulatory oversight and systematic outside monitoring of electoral uses of AI. Still, regulators should account for the diversity of AI uses and not completely disincentivize their electoral use.

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Authors (3)
  1. Andreas Jungherr (5 papers)
  2. Adrian Rauchfleisch (4 papers)
  3. Alexander Wuttke (3 papers)

Summary

Examining Attitudes Toward AI Use in Election Campaigns: Public Perception and Regulatory Implications

The paper "Deceptive Uses of Artificial Intelligence in Elections Strengthen Support for AI Ban" provides a comprehensive paper on the public perception and potential implications of AI utilization in political campaigns. Through a methodological approach involving a preregistered representative survey and two preregistered experiments with a substantial sample size (n=7,635), the authors, Jungherr, Rauchfleisch, and Wuttke, delve into the nuances of AI-enabled electoral activities and the varying public concerns associated with them.

Key Findings and Numerical Results

The research identifies three primary categories of AI use in elections: campaign operations, voter outreach, and deception. It highlights three core findings that capture the public's attitude towards these practices:

  1. Public Perception of AI Use in Elections: The respondents generally perceived AI use in elections negatively. However, they expressed the most substantial objection to deceptive AI uses compared to operational or voter outreach uses. For example, 76.37% of respondents disliked the use of AI for creating deceptive social media content.
  2. Impact of Deceptive AI Practices: Exposure to deceptive AI practices substantially increased public anxiety and perceived norm violations. Notably, individuals learning about deceptive AI use were more inclined to support stringent regulatory oversight and even a moratorium on AI development due to heightened perceptions of threat and norm violation. Public support for an AI ban increased from 29% to 38% upon exposure to deceptive uses.
  3. Partisan Responses: The paper observed limited punitive responses in party favorability among partisans, even after being informed of their party's involvement in deceptive AI practices. Equivalence tests revealed a lack of a substantial decrease in party favorability ratings despite the adverse use of AI, underscoring the insufficiency of public opinion as a deterrent for parties considering deceptive AI tactics.

Implications and Speculative Directions in AI

The paper's results underscore the need for nuanced regulatory frameworks addressing the diversity of AI uses in elections. Broadly, it illustrates a misalignment between political incentives and public trust. Given the limited coaction between public disapproval and political penalty, the authors argue this misalignment requires regulatory intervention to curb deceptive practices without stifling productive AI uses in electoral processes.

The paper further implicates how AI's role in elections could catalyze a broader discourse on AI governance, emphasizing safety over innovation when potential harms to democratic processes are perceived. It cautions regulatory bodies against adopting blanket restrictions, which could hamper beneficial AI applications in campaign operations and voter outreach that enhance democratic participation and engagement.

Future Developments

The research opens avenues for refining AI policy by highlighting areas such as AI fairness, transparency, and accountability in electoral contexts. It suggests international comparative research to understand diverse political environments' responses and explore the interplay between AI and public trust globally.

Moreover, the paper intimates the future need to balance innovation and regulation to leverage AI's positive potentials while curbing its use for detrimental purposes. With society's increasing dependence on technology, such regulatory foresight is pivotal. Future studies could seek to quantify the tangible impacts of AI regulations on electoral behavior and democratic health, potentially steering the dialogue toward more informed and effective AI governance strategies.

In conclusion, this research provides significant insights into the public's nuanced viewpoints on AI's role in elections. It offers critical considerations for policymakers striving to establish regulatory frameworks that uphold electoral integrity without curtailing the benefits of AI innovations in political engagement.

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