Cohere For AI - Jillian Fisher, PhD student, University of Washington

The Power of Bias: How AI Influences Political Decision-Making and What We Can Do About It

AI language models are increasingly integral to decision-making, communication, and public discourse, yet their inherent biases pose significant risks to impartiality and fairness. This talk delves into the findings of the paper Biased AI Can Influence Political Decision-Making, which demonstrates how partisan bias in AI can sway political decisions, even overriding individuals’ pre-existing partisanship. Through interactive experiments, the study highlights the subtle yet profound ways biased AI can alter opinions and amplify societal polarization. Beyond identifying these risks, the research also underscores the importance of mitigation strategies to reduce the influence of biased AI. One promising finding is that prior knowledge about AI and its potential biases can significantly decrease susceptibility, suggesting a critical role for public education in empowering users to critically assess AI-generated content. These strategies, combined with advancements in AI alignment and bias detection, offer a path forward to ensure language models serve as tools for fairness and inclusivity rather than instruments of division.

Jillain Fisher is a Statistics + CSE PhD student at the University of Washington researching AI alignment, safety, and impact. Advised by Yejin Choi in the Paul G. Allen School of Computer Science and Engineering and Thomas Richardson in the Statistics Department, her focus in on projects that leverage statistical tools to advance methods and insights in human-centric NLP challenges. Currently, her work centers on alignment, controllable generations, and impact of AI on society.

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