UCL Faculty of Laws


Experts, crowds & algorithms: the three forms of (legal) prediction

07 March 2016, 6:00 pm–8:00 pm


Event Information

Open to



Centre for Ethics & Law


UCL Roberts G06 Sir Ambrose Fleming LT, Roberts Building, Torrington Place, London WC1E 7JE

Speaker: Professor Daniel Martin Katz (Illinois Tech – Chicago Kent College Law)
Chair: Professor Richard Moorhead (University College London)

About the talk

Lawyer’s obligations of competence will increasingly encompass the ability to meaningfully apply analytics to help support their decision making.  In this talk, Professor Katz will highlight the three forms of (legal) prediction – experts, crowds & algorithms and describe how ensembles of these various streams of intelligence can lead to better decision making. 

About the speaker

Daniel Martin Katz is a technologist, scientist and law professor, blending education and thought leadership with quantitative analyses of law and society. Professor Katz teaches at Illinois Tech – Chicago Kent College of Law, is the author of the “MIT School of Law” and is an editor for a number of academic and industrial journals. Dan’s forward-thinking ideas helped to earn him acknowledgement as a “Legal Rebel” by the ABA Journal and as a member of “Fastcase 50.” In addition to his academic work, Dan is the Chief Strategy Officer and co-founder of LexPredict (a Legal Analytics company) and serves as an advisor to a number of legal tech startups including NextLaw Labs – a global collaborative innovation ecosystem organised with Dentons (the world’s largest law firm).

Professor Katz received his Ph.D. in political science and public policy with a focus on complex adaptive systems from the University of Michigan. He graduated with a Juris Doctor cum laude from the University of Michigan Law School.  During his graduate studies, he 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 Centre for the Study of Complex Systems.