Don't Kill the Baby: The Case for AI in Arbitration
<|reference_start|>Don't Kill the Baby: The Case for AI in Arbitration: Since the introduction of Generative AI (GenAI) in 2022, its ability to simulate human intelligence and generate content has sparked both enthusiasm and concern. While much criticism focuses on AI's potential to perpetuate bias, create emotional dissonance, displace jobs, and raise ethical questions, these concerns often overlook the practical benefits of AI, particularly in legal contexts.   This article examines the integration of AI into arbitration, arguing that the Federal Arbitration Act (FAA) allows parties to contractually choose AI-driven arbitration, despite traditional reservations. The article makes three key contributions: (1) It shifts the focus from debates over AI's personhood to the practical aspects of incorporating AI into arbitration, asserting that AI can effectively serve as an arbitrator if both parties agree; (2) It positions arbitration as an ideal starting point for broader AI adoption in the legal field, given its flexibility and the autonomy it grants parties to define their standards of fairness; and (3) It outlines future research directions, emphasizing the importance of empirically comparing AI and human arbitration, which could lead to the development of distinct systems.   By advocating for the use of AI in arbitration, this article underscores the importance of respecting contractual autonomy and creating an environment that allows AI's potential to be fully realized. Drawing on the insights of Judge Richard Posner, the article argues that the ethical obligations of AI in arbitration should be understood within the context of its technological strengths and the voluntary nature of arbitration agreements. Ultimately, it calls for a balanced, open-minded approach to AI in arbitration, recognizing its potential to enhance the efficiency, fairness, and flexibility of dispute resolution<|reference_end|>
@article{broyde2024don't,
    title={Don't Kill the Baby: The Case for AI in Arbitration},
    author={Michael Broyde, Yiyang Mei},
    journal={arXiv preprint arXiv:2408.11608},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.11608},
    primaryClass={cs.AI cs.CY}
}