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    Algorithms and Precedent: How AI Can Provide Open-Access Legal Resources

    Algorithms and Precedent: How AI Can Provide Open-Access Legal Resources

    How can AI help prepare a legal case? Dr. Samuel Dahan discusses his open-access work training machines to read law texts and extract the precedent to assist lawyers and self-represented litigants in their research.

    Interviewee Name: 
    Dr. Samuel Dahan
    Topic: 
    Algorithms and Precedent: How AI Can Provide Open-Access Legal Resources
    Podcast: 
    Blind Date with Knowledge, Season 3, Episode 08
    Interviewed by: 
    Barry Kaplan
    Air date on CFRC: 
    November 13, 2019
    Episode length: 
    14:37
    Academic areas: 

    Dr. Samuel Dahan is an assistant professor in the Faculty of Law and a Queen’s National Scholar. He is the director of the Conflict Analytics Lab at Queen’s University, a LegalTech global consortium on the application of data analytics and AI to dispute resolution and negotiation. Dr. Dahan has worked as a legal secretary to the Court of Justice of the European Union and as a legal advisor for the Comparative Law Unit of the French Administrative Supreme Court. His research focuses on regulatory responses to the euro crisis from an empirical data perspective. He is also a nationally medaled athlete in Taekwondo.

    In this episode, Dr. Dahan discusses the Conflict Analytics Lab and his open-access work training machines to read law texts and extract the relevant information, typically the precedent, to assist lawyers and self-represented litigants in their research. He also discusses the limitations of algorithms in predicting subjective outcomes in judicial decision making.

    Please visit the for more information about Dr. Dahan’s research.

    Algorithms and Precedent: How AI Can Provide Open-Access Legal Resources

    Season 3: Episode 08