"Building Political Superintelligence," Professor Andrew Hall

AI is fundamentally transforming political science research by enabling rapid, autonomous data analysis and providing personalized political guidance. While models offer the potential for an infinitely patient advisor, they currently face significant hurdles, including uneven access to information, data poisoning, and inherent biases that can lead to skewed voting recommendations. To navigate these risks, researchers must develop rigorous evaluation frameworks—or "evals"—to measure model performance and ensure accountability. Rather than viewing AI solely as a source of information, society must treat it as a powerful tool for processing complex decisions. Establishing cryptographic audit trails for digital content and creating transparent, public repositories for candidate information are essential steps toward building a resilient, AI-integrated democratic ecosystem that empowers citizens rather than disempowering them through opaque, automated advice.