On the Crossroads of Law and Economics Workshop: Crime and Computational Methods

Datum
vrijdag 3 dec 2021, 14:20 - 18:00
Type
Workshop
Ticket informatie

Participation in the workshop is free of charge, however, registration is required so we can send you ZOOM invitation. Register here.

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Erasmus School of Law

It is our pleasure to invite you to our bi-annual Workshop at the Crossroads of Law and Economics, this time on the topic of criminal law and criminal justice system, as investigated using computational methods. 

The workshop is co-organised by Erasmus School of Law and Erasmus School of Economics, with the support of Erasmus Centre of Empirical Legal Studies (ECELS), Behavioural Approaches to Contract and Tort: Relevance for Policymaking (BACT) and Erasmus Centre for Economic and Financial Governance (ECEFG). Presenters come from different fields (law, economics, psychology and others) and discuss their work relevant to legal questions and empirical research. Each presentation is then followed up by a stimulating discussion.

Programme

 December 3, 2021 (online)

14:20-14:30 

Testing of sound and presentations

14:30-15:15

Christoph Engel (Erasmus School of Law and Max Planck Institute for Research on Collective Goods) - Code is Law: How COMPAS Affects the Way the Judiciary Handles the Risk of Recidivism

(with Marina Höhne, Lorenz Linhardt and Marcel Schubert)

15:20-16:05 

Elliott Ash (ETH Zurich) - A Machine Learning Approach to Analyze and Support Anti-Corruption Policy

(with Sergio Galletta and Tommaso Giommoni)

16:10-16:55 

Frederike Zufall (Max Planck Institute for Research on Collective Goods) - Towards an automated legal assessment of criminal offenses: challenges and findings

(with Torsten Zesch and Marius Hamacher)

17:00-17:45

Daniel Chen (Toulouse School of Economics) -Training Effective Altruism

(with Sultan Mehmood and Shaheen Naseer)

17:45-18:00

Closing remarks

Organisers

Erasmus School of Law: Elena Kantorowicz-Reznichenko, Christoph Engel, Klaus Heine
Erasmus School of Economics: Jurjen Kamphorst, Rubén Poblete Cazenave.

For questions, please contact RILE@law.eur.nl.


 

About the speakers

A Professor of Experimental Law and Economics (ESL) as well as a director at the Max Planck Institute for Research on Collective Goods, and an Honorary Doctorate at the Hebrew University of Jerusalem. He is most visible for his research on behavioral law. Christoph Engel has brought paradigms, results and methods from behavioral economics and psychology to law. This has also led to his chair for experimental law and economics at the Erasmus School of Law. In many of his papers, he uses lab experiments: to define the need for legal intervention in behavioral terms, and to assess the effect of legal intervention. One pervasive challenge in experimental research are heterogenous treatment effects. He has developed machine learning methods to analyse such data. Another obvious challenge is external validity. In recent work, he increasingly complements experiments with computational methods applied to rich sets of observational data. He for instance, in an ongoing project for the first time uses the full data from the German Constitutional Court to study the determinants of judicial decision-making.

https://www.coll.mpg.de/engel

Elliott Ash is Assistant Professor of Law, Economics, and Data Science at ETH Zurich's Center for Law & Economics, Switzerland. Prior to joining ETH, Elliott was Assistant Professor of Economics at University of Warwick, and before that a Postdoctoral Research Associate at Princeton University’s Center for the study of Democratic Politics. He received a Ph.D. in economics and J.D. from Columbia University, a B.A. in economics, government, and philosophy from University of Texas at Austin, and an LL.M. in international criminal law from University of Amsterdam. Elliott's research and teaching focus on empirical analysis of the law and legal system using techniques from econometrics, natural language processing, and machine learning. His research has been published in the Journal of Law and Economics, Georgetown Law Journal, Journal of Politics, and Political Analysis. Elliott’s research has earned grant funding from the Swiss National Science Foundation, Swiss Data Science Center, U.S. National Science Foundation, the Turing Institute, and the Washington Center for Equitable Growth.

https://elliottash.com

A senior research fellow at the Max-Planck-Institute for Research on Collective Goods, Bonn. Frederike Zufall’s research addresses questions of Information Technology and Artificial Intelligence through interdisciplinary research and comparative law study. She passed the First and Second Legal State Exams in Germany with Honors and obtained her doctoral degree in law from Humboldt University of Berlin. She was appointed as an Assistant Professor at Waseda University, Tokyo.

https://www.coll.mpg.de/frederike-zufall

Professor at the Toulouse School of Economics. He is also a Senior Fellow at the Institute for Advanced Study in Toulouse, Collaborator at Harvard Medical School, advisor at NYU Courant Institute for Mathematics Center for Data Science, and the Lead Principal Investigator, DE JURE (Data and Evidence for Justice Reform) at the World Bank, Director of Research at the Centre National de la Recherche Scientifique (CNRS). He is the founder of oTree Open Source Research Foundation and Data Science Justice Collaboratory and co-founder of Justice Innovation Lab. Chen was previously Chair of Law and Economics at ETH and tenure-track assistant professor in Law (primary), Economics, and Public Policy at Duke University. Chen received his BA and MS from Harvard University in Applied Mathematics and Economics; Economics PhD from MIT; and JD from Harvard Law School. He has attained prominence through the development of open source tools to study human behavior and through large-scale empirical studies — data science, artificial intelligence, and machine learning — on the relationship between law, social norms and the enforcement of legal norms, and on judicial systems.

https://users.nber.org/~dlchen/


Registration

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