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Artificial Intelligence's Role in Law

Robot lawyer

I recently attended the 18th Edition of the International Conference on Substantive Technology in Legal Education and Practice, or SubTech, an annual event which examines the impact of technology in law. While it was great to see technologists and legal scholars working together, there was a contrast during discussions that struck me. 

One of the speakers was Frank Schilder, senior director of research at Thomson Reuters. Schilder spoke about Thomson Reuters’ work on agentive AI in legal information systems, showcasing how combining language models with reasoning systems can revolutionize legal research and decision-making.  

One of the audience members expressed concern that the differences between different lawyers and law firms poses a challenge to automation in any form. The concern was that the bespoke nature of legal reasoning, with each case seen as unique, complicates the standardization necessary for scalable AI solutions. 

This tension between the scalable nature of computer science and the bespoke nature of the law is palpable. Computer science thrives on abstraction and scalability, while the law sees itself as far more individualized. Can we reconcile these differences to create AI systems that enhance the legal profession without compromising its core principles? 

The answer lies in finding commonalities within legal reasoning. While each case is unique, standard types of reasoning recur. Identifying these can help build scalable AI systems that assist in legal processes. This approach is not about replacing the nuanced human touch but augmenting it. AI can help lawyers analyze vast data, identify relevant precedents, and predict outcomes based on historical patterns. 

A good model for this can be found in medicine. AI and data science has had tremendous impact in medicine, not because we have ignored the human elements, but because we found ways in which to characterize the commonalities. Each case is different, but the similarities far outweigh the differences, and it is in those similarities where we find the solutions.   

Moreover, AI can significantly increase access to justice. By automating routine tasks and providing affordable legal advice, AI systems can make legal services more accessible to those who cannot afford traditional legal representation.  

The integration of AI into the legal profession offers tremendous potential. By focusing on commonalities in legal reasoning, we can develop scalable AI systems that support lawyers and judges. Addressing biases and ensuring ethical implementation will be crucial to this effort. Ultimately, AI should serve to augment the human elements of the legal system, promoting fairness and expanding access to justice for all. 

Kristian Hammond
Bill and Cathy Osborn Professor of Computer Science
Director of the Center for Advancing Safety of Machine Intelligence (CASMI)
Director of the Master of Science in Artificial Intelligence (MSAI) Program

 

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