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Is AI set to redefine the legal profession? In this talk, we will see why claim is not supported by the current evidence. We will dive into AI’s increasingly prevalent roles in three types of legal tasks: information processing; tasks involving creativity, reasoning, or judgment; and predictions about the future. The ease of evaluating legal applications varies greatly across legal tasks, based on the ease of identifying correct answers and the observability of information relevant to the task at hand. Tasks that would lead to the most significant changes to the legal profession are also the ones most prone to overoptimism about AI capabilities, as they are harder to evaluate. We will conclude with recommendations for better evaluation and deployment of AI in legal
AI是否将重新定义法律行业？在这次讨论中，我们将看到为什么当前的证据不支持这一主张。我们将深入研究AI在三种类型的法律任务中越来越普遍的角色：信息处理；涉及创造力、推理或判断的任务；以及对未来的预测。根据确定正确答案的容易程度以及与手头任务相关的信息的可观察性，评估法律应用的难易程度在法律任务中差异很大。那些可能导致法律行业发生最重大变化的任务也是对AI能力过于乐观的任务，因为它们更难评估。我们将以对在法律环境中更好地评估和部署AI的建议结束讲座。
Sayash Kapoor is a Laurance S. Rockefeller Graduate Prize Fellow in the University Center for Human Values and a computer science Ph.D. candidate at Princeton University’s Center for Information Technology Policy. He is a coauthor of AI Snake Oil, a book that provides a critical analysis of artificial intelligence, separating the hype from the true advances. His research examines the societal impacts of AI, with a focus on reproducibility, transparency, and accountability in AI systems. He is especially interested in the interaction between AI and policy. He has previously worked on AI in various institutions in academia and the industry, including at Facebook, Columbia University, and EPFL Switzerland. Kapoor has been recognized with various awards, including a best paper award at ACM FAccT, an impact recognition award at ACM CSCW, and inclusion in TIME’s inaugural list of the 100 most influential people in AI.
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