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Daniel Martin Katz

Daniel Martin Katz
[Hi-Res Photo]
Associate Professor of Law & Co-Director - ReInvent Law: A Law Laboratory Devoted to Innovation, Technology & Entrepreneurship
Law College Building
648 N. Shaw Lane Rm 230F
East Lansing, MI 48824-1300
517-432-6807
katzd@law.msu.edu

Ph.D. Political Science & Public Policy, University of Michigan (2011)
J.D. University of Michigan Law School (2005)
M.P.P. Ford School of Public Policy, University of Michigan (2005)
B.S. University of Oregon (2000)

  • Criminal Procedure: Investigation
    (Formerly Criminal Procedure I)This course provides students with an introduction to federal constitutional limits on police investigation under the Fourth, Fifth, and Sixth Amendments. This includes the governance of search and interrogation, and the right to counsel. Students can take Criminal Procedure: Investigation and Criminal Procedure: Adjudication in any order or at the same time. Students who have taken Criminal Procedure I are ineligible to enroll in this course.
  • E-Discovery
    This course teaches students the law, theory, and practice of discovery of electronically stored documents and information. The course covers both the federal and Michigan state law governing the production of electronic documents, privilege, motions to compel, and protective orders—as well as the applicable professional standards. Students will be provided a theoretical understanding of the dominant computer algorithmic techniques used in e-discovery (search terms and predictive coding) as well as the legal, ethical, and technological problems each presents. Emphasis will be on hands-on work with e-discovery software.
  • Entrepreneurial Lawyering
    Enrollment is by permission only. This course helps students understand the economic pressures, technological changes, and globalization facing the legal profession in the 21st century, and to assist students in successfully navigating their legal career given these challenges. The course explores the concept of a virtual law practice as well as the use of technology and cloud-computing in building a law practice; free and low-cost resources and tools will be shared that will help the entrepreneur-minded student identify ways to leverage leading-edge technology to defray start-up costs associated with launching a practice and to control overhead. Ethics, licensing, and malpractice issues will also be discussed. The course will be particularly useful for students who are contemplating solo practice, consulting, or engaging in an entrepreneurial venture, as well as those who are considering non-traditional uses for their law degree. Other topics to be covered include client development and networking, case studies of innovative legal services delivery mechanisms and alternative business structures, and work/life balance including the study of emotional intelligence and mindful lawyering practices. This course assumes students may (or may not) arrive with a range of experience in the use of technology—we will provide training for everything needed to succeed in this course.
  • Legal Analytics
    This course is designed to train students to efficiently manage, collect, explore and analyze various forms of legal data. Its purpose is to imbue students with the capability to:(1) understand the process of extracting knowledge from data with specific applications to domains such as legal prediction; (2) distinguish themselves in legal proceedings involving data or analysis;(3) distinguish themselves in firm management matters;(4) understand and communicate with information and software sector clients; and(5) use data to manage outside resources such as LPO or eDiscovery providers.Students will be introduced to sophisticated statistical techniques including machine learning and natural language processing.
  • Legal Information Engineering & Technology
    This course highlights the increasing role of legal information technology in the law practice of today (and the not too distant future). Students will be exposed to a number emerging approaches in legal automation, process engineering, informatics / ‘soft’ artificial intelligence (e-discovery, automated document generation), supply chain management, and quantitative legal prediction.
  • Litigation: Data, Theory, Practice, Process
    The primary goal of this class is for students to learn how to leverage data, theory, and process to obtain better results in litigation. Students will explore sources of data and the use of decision theory, game theory, and economic analysis to evaluate claims, predict outcomes, and improve litigation strategies. The litigation process will be deconstructed beyond the mechanics of procedural rules and into the specific tasks lawyers must perform. Deconstructing the litigation process allows lawyers to properly staff matters, complete tasks more efficiently, and demonstrate the marginal return on investment for each task. Students will also learn a number of practical skills necessary to be an effective litigator. Among the topics addressed are early case assessment, client counseling, settlement negotiations, drafting persuasive pleadings and motions, managing discovery, persuading the fact finder, managing litigation projects, budgeting, and developing effective value-added litigation strategies.
  • Quantitative Analysis for Lawyers
    This is an applied course designed to introduce student to various modes of quantitative thinking. The goals of this course are (1) to prepare students to be knowledgeable consumers of quantitative information as practicing lawyers and (2) to prepare students for technology infused law practice of the 21st Century. Course modules include (a) research design, (b) statistics in the courtroom, (c) introduction to probability and basic statistics, (d) data distributions, (e) statistical tests (f) regression analysis, (g) quantitative legal prediction and (h) a brief introduction to legal automation and the technology infused law practice of the present (and not so distant future).
  • Sports Law
    (Formerly DCL 351) This course explores the legal structure of and problems surrounding amateur and professional sports leagues and associations. Included will be an examination of the role of the collective bargaining process, representation of the professional athlete, individual contracts and arbitration in professional sports, anti-trust law implications and common problem areas, including the particular place of tort and criminal law in professional and amateur sports.

Daniel Martin Katz is an Associate Professor of Law at Michigan State University. He is also the Co-Founder & Co-Director of the ReInvent Law Laboratory.

He is the Editor of the International Journal of Law and Information Technology (Oxford University Press) and serves on the Editorial Board of the Journal of Artificial Intelligence & Law (Springer Scientific). He is also a member of the ABA Task Force on Big Data and the Law.

His academic interests include legal informatics, big data and the law, lawyer regulation, quantitative modeling of litigation and jurisprudence, law & entrepreneurship, computational legal studies, economics of the legal profession, positive legal theory, technology aided access to justice, legal complexity and the overall impact of information technology, analytics and automation on the market for legal services.

Professor Katz has published or forthcoming articles in scholarly journals such as Emory Law Journal, Illinois Law Review, Ohio State Law Journal, Virginia Tax Review, Cornell Journal of Law and Public Policy, Journal of Legal Education, Journal of Law and Politics, Physica A and the Proceedings of the International Conference on Artificial Intelligence and Law.

Professor Katz has presented his research at a number of leading institutions including:Georgetown Law, Texas Law, Vanderbilt Law, Emory Law, Illinois Law, Stanford Law, Colorado Law, Houston Law, Fordham Law, San Diego Law, UToronto Law,WashU Law, Berkeley Law, Kansas Law, Oregon Law and Santa Clara Law. He has also spoken at Princeton CITP, UPenn Linguistics, ETH Zurich, MIT Media Lab,Oberlin Computer Science, Santa Fe Institute, Duke Computer Science, Harvard Kennedy School and NYU Stern.

His work has been featured in print and/or online versions of publications including the New York Times, Slate Magazine, Wired Magazine, Bloomberg Business Week, U.S. News & World Report, Huffington Post, The American Lawyer, ABA Journal, National Law Journal, Law Technology News, California Lawyer, Data Informed.com, Legal Futures (UK), Law Society Gazette (UK), The Globe and Mail (Canada) and Folha de S. Paulo (Brazil).

Professor Katz has been recognized as a leading thinker about the future of the legal profession. Sponsored in part by a generous grant from the Ewing Marion Kauffman Foundation in 2012, Professor Katz co-founded the ReInvent Law Laboratory, a collaborative venture devoted to innovation, technology, and entrepreneurship in legal services. In 2013, he was also named as a member of the Fastcase 50, an award which "recognizes 50 of the smartest, most courageous innovators, techies, visionaries, and leaders in the law." He was also named to the 2013 Class of "Legal Rebels" by the ABA Journal.

Professor Katz is also an avid blogger; his posts can be found at Computational Legal Studies (www.ComputationalLegalStudies.com).

Professor Katz’s teaching interests include substantive courses such as Criminal Procedure, Criminal Law, Administrative Law, Electronic Discovery and Legal Ethics & Professional Responsibility. In addition, he is interested in process/analytic/theoretical courses such as Legal Information Technology, Economics of the Legal Profession, Legal Project Management, Entrepreneurial Lawyering, Legal Analytics, Quantitative Methods for Lawyers, Law as a Complex Adaptive System, Legal Process Engineering and Artificial Intelligence & Law. Beyond his law teaching, Professor Katz co-teaches "Complex Systems in the Social Sciences" at the University of Michigan ICPSR Summer Program in Quantitative Methods.

Professor Katz received his Ph.D. in Political Science and Public Policy (with a focus on Complex Adaptive Systems) from the University of Michigan in 2011. He graduated with a J.D. cum laude from the University of Michigan Law School in 2005, and simultaneously obtained a M.P.P. from the Gerald R. Ford School of Public Policy at the University of Michigan. Prior to joining the MSU College of Law faculty, Professor Daniel Katz was a Fellow in Empirical Legal Studies at the University of Michigan Law School and a National Science Foundation-IGERT Fellow at the University of Michigan Center for the Study of Complex Systems.


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