Revolutionizing the Practice of Law Through Data Science: Use Case and Applications Bennett Borden Drinker, Biddle & Reath LLP 1500 K Street, N.W. Washington, DC USA 20005 Bennett.Borden@dbr.com ABSTRACT Bennett B. Borden is Partner and Co-chair of As demonstrated at past DESI workshops at ICAIL, Drinker Biddle & Reath’s Information Governance advances over the past decade in artificial intelligence and eDiscovery Practice, as well as the firm’s Chief and machine learning have transformed the practice of Data Scientist. In his two decades of legal practice, he e-discovery in making legal search more cost- has conducted both offensive and defensive electronic effective and efficient. Similar forms of data analytics discovery in complex litigation. Bennett has had now hold the promise of similarly aiding the legal extensive experience counseling Fortune 500 clients profession across a spectrum of traditional activities, on the establishment of information governance and many of which consist of highly repetitive tasks. Law records management policies. He regularly advises firms are not, however, incentivized to be more multinational clients regarding data privacy, security efficient if they are simply giving away the efficiency and regulatory compliance. In his role as the firm’s gains without reaping a benefit for themselves. In Chief Data Scientist, he is responsible for the firm’s order to effectively apply data science to the practice overall data analytics strategy. Bennett advises the of law, a new billing mechanism needs to be applied firm and its clients on the development and use of so that the efficiency gains benefit both the client and analytics models that enable insight, data storytelling the firm, aligning their incentives. In this session, we and economic value generation. Bennett’s research will discuss how data analytics principles can best be into the use of machine-based learning and applied to the practice of law, with an eye towards unstructured data for organizational insight is now how AI methods are being used within law firms to being put to work in data-driven early warning complement human legal expertise. Illustrative use systems for clients to detect and prevent corporate cases will include using AI in contract analysis, fraud and other misconduct. Bennett also builds mergers & acquisitions, and employment and machine-based learning models to transform and whistleblower investigations. improve legal outcomes in key corporate events including mergers and acquisitions, information governance program development and enforcement, litigation, and investigations and business intelligence. He has been Chambers-ranked nationwide in e-discovery for the past four years, and In: Proceedings of the First International Workshop recently was appointed to the National Conference of on AI and Intelligent Assistance for Legal Lawyers and Scientists (NCLS) of the American Professionals in the Digital Workplace (LegalAIIA Academy for the Advancement of Science. 2019), held in conjunction with ICAIL 2019. June 17, 2019. Montréal, QC, Canada. § Bennett holds an M.S. in Business Analytics from New York University, a J.D., cum laude, from Copyright © 2019 for this paper by its authors. Use Georgetown University Law Center, and a B.A. with permitted under Creative Commons License highest honors from George Mason University. He is Attribution 4.0 International (CC BY a member of the Bars of the District of Columbia and 4.0). Published at http://ceur-ws.org. Maryland.