Researchers and academics sponsored by The Stanford Graduate School of Business, Stanford Business, Government, and Society Initiative, and University of Chicago Harris School for Public Policy met earlier this year with representatives of OpenAI, Google, Meta, and other AI titans to ask hard questions about AI’s possible effects on democracy. What are the risks? What are the potential benefits? And what should we be doing to prepare for the first election in the age of Generative AI in 2024? The result of this session is the white paper, Preparing for Generative AI in the 2024 Election: Recommendations and Best Practices Based on Academic Research.
At a panel event Introduced by Stanford GSB Dean Jonathan Levin, the authors of the paper, Andrew Hall, Professor of Political Economy at Stanford GSB, and his counterpart at the University of Chicago Harris School of Public Policy (and interim Harris School Dean) Ethan Bueno de Mesquita presented their worrisome – and hopeful – findings. Bueno de Mesquita opened with the bombastic possibility of a potential “Deepfake October Surprise” where a less-than-ethical campaign launches a convincing AI video, causing scandal for their opponent too soon before the election for a response. Bueno de Mesquita also presented less flamboyant dangers, such as the erosion of the public’s trust in political systems and their own eyes. Several campaigns worldwide have already used “It’s an AI fake” to explain away very real, very damning evidence against them.
Andy Hall then focused on threats they found to be overhyped – like fears that elections could be stolen with microtargeted ads, and under-hyped – like the most commonly asked question to chatbots about elections: “Where is my polling place?” a fact chatbots do not know but could easily and confidently lie about. Professor Hall also highlighted ways AI could be a political benefit: helping down-ticket candidates grow their campaigns, providing voters with understandable syntheses of party platforms and candidates’ policies, and giving voters an accessible way to learn about politics.
During the panel discussion session, professors Gregory Martin and Emilee Chapman from Stanford and Kristian Lum from U. Chicago tackled numerous potential political landmines and windfalls of AI, discussing algorithmic bias, consolidation or even monopolization of the information environment, and the replacement of reporters in traditional media with Gen AI journos.
During the post-panel Q&A, audience members representing both schools posed challenging, and at times hopeful questions, asking if GenAI could help third-party candidates break the duopoly of the American political system The panelists were doubtful) and if a consolidation under AI could save us from the divisiveness of the current media landscape—and whether that would necessarily be a good thing. (The panelists said further study was required)
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