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86.2
The Chilling Effect of Governance-by-Data on Data Markets
Niva Elkin-Koren
Professor, University of Haifa Faculty of Law; Director, Center for Cyber Law and Policy, University of Haifa; Faculty Associate, Berkman Klein Center for Internet & Society, Harvard University.

We would like to thank Rabeea Assy, Harry First, Eleanor Fox, Tamar Indig, Marcel Kahan, Yafit Lev-Aretz, Hans-Wolfgang Micklitz, Alan Miller, Ariel Porat, Daniel Richman, Eden Sarid, Catherine Sharkey, Katherine Strandburg, Alina Wernick, participants of the Competition, Innovation, and Information Law (CIIL) Speakers Series and the Privacy Research Group at NYU School of Law, and The University of Chicago Law Review Symposium on Personalized Law for most thoughtful comments and discussions. Thanks to Ilana Atron, Saar Ben Zeev, and Lior Frank for most helpful research assistance. This research was supported by the Center for Cyber Law and Policy, University of Haifa. Any mistakes or omissions are the authors’.

Michal S. Gal
Professor and Director of the Forum for Law and Markets, University of Haifa Faculty of Law; President, Academic Society for Competition Law (ASCOLA).

Big data has become an important resource not only in the commercial sphere but also in the legal one. Governance-by-data can take many forms, including setting enforcement priorities, affecting methods of proof, and even changing the content of legal norms.

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86.2
Neuroscience and the Personalization of Criminal Law
Deborah W. Denno
Arthur A. McGivney Professor of Law, Founding Director, Neuroscience and Law Center, Fordham University School of Law. All statistics and case distributions discussed in this Essay and presented in the Appendix in Table 1 and Figures 1–5 are organized and on file with the author and with The University of Chicago Law Review.

I am most grateful to the following persons for their contributions to this Essay: Ruben Coen-Cagli, Nestor Davidson, Kathleen Ellis, Janet Freilich, Marianna Gebhardt, David Greenberg, Filippo Maria Lancieri, Jacob Nadler, Mark Patterson, Richard Squire, Ryan Surujnath, and Erica Valencia-Graham. I also thank Alissa Black-Dorward and the Fordham University School of Law library staff for superb research assistance as well as Timothy W. DeJohn for providing information about the Jones case. I received insightful comments on earlier versions of this Essay from the participants in presentations given at Stanford Law School (the BioLawLapalooza 2.0), the Fordham University School of Law, and at The University of Chicago Law Review Symposium on Personalized Law (organized by Omri Ben-Shahar and Ariel Porat). I am indebted to five sources for research funding, without which this project could not have existed: Fordham University School of Law, the Fordham Neuroscience and Law Center, the Gerald Adelman Fellowship, Roger Sacks, and the Barnet and Sharon Phillips Family Fund. No individual or organization acknowledged in this Essay necessarily supports the Essay’s interpretations or conclusions. Responsibility for any mistakes or misjudgments rests solely with the author.

Every criminal case is part of a larger personal story—some headline-grabbing, some entirely mundane; yet each narrative is important to how the criminal justice system assesses an individual’s level of culpability.

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86.2
A Framework for the New Personalization of Law
Anthony J. Casey
Professor of Law, The University of Chicago Law School.

I am grateful for research support from the Richard Weil Faculty Research Fund and the Paul H. Leffman Fund. Stephanie Xiao and Courtney Block provided excellent research assistance.

Anthony Niblett
Associate Professor and Canada Research Chair in Law, Economics, & Innovation, University of Toronto Faculty of Law. In the interests of full disclosure, Professor Niblett is also a cofounder of Blue J Legal, a start-up bringing machine learning to the law.

Personalized law is an old concept. The idea that the law should be tailored to better fit the relevant context to which it applies is obvious and has been around as long as the idea of law itself.

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86.2
Implementing Personalized Law: Personalized Disclosures in Consumer Law and Data Privacy Law
Christoph Busch
Professor of Law at the University of Osnabrück, Germany.

I am grateful to the participants of The University of Chicago Law Review Symposium on Personalized Law organized by Omri Ben-Shahar, Anthony Casey, Ariel Porat, and Lior Strahilevitz in April 2018 for their very helpful comments and suggestions. I would also like to thank Alberto De Franceschi and the participants of the conference on Granular Legal Norms at Villa Vigoni in March 2017 for their insightful inputs.

Mandated disclosures are probably one of the most widely used regulatory tools in consumer law and data privacy law on both sides of the Atlantic.

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86.2
Algorithmic Fair Use
Dan L. Burk
Chancellor’s Professor of Law, University of California, Irvine; 2017–2018 US-UK Fulbright Cybersecurity Scholar.

My thanks to members of the Oxford Internet Institute’s Digital Ethics Lab, participants in the Cambridge Faculty of Law CIPIL Intellectual Property Seminar Series, participants in the session on “Data Commons, Privacy, and Law” at the ECREA Digital Culture and Communication Section Conference, as well as to Oren Bracha,Pamela Samuelson, and participants in the CyberProf listserv conversation on algorithmic fair use for helpful discussion in preparation of this Essay. Portions of this research were made possible by support from the US-UK Fulbright Commission.

Law, like other human artifacts, is costly to produce, to distribute, and to apply.

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86.2
Personalizing Mandatory Rules in Contract Law
Omri Ben-Shahar
Leo and Eileen Herzel Professor of Law, The University of Chicago.

We thank Oren Bar-Gill and participants in The University of Chicago Law Review Symposium on Personalized Law for their comments, and Tal Abuloff and Tom Zur for excellent research assistance.

Ariel Porat
Alain Poher Professor of Law at Tel Aviv University and Fischel-Neil Distinguished Visiting Professor of Law at The University of Chicago.
Mandatory rules in contract law are meant to protect people from “bad” terms.
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86.2
Algorithmic Price Discrimination When Demand Is a Function of Both Preferences and (Mis)perceptions
Oren Bar-Gill
William J. Friedman and Alicia Townsend Friedman Professor of Law and Economics, Harvard Law School.

For helpful comments and suggestions, I would like to thank Omri Ben-Shahar, Yochai Benkler, Ryan Bubb, Glenn Cohen, Hanoch Dagan, Avihay Dorfman, Noah Feldman, Meirav Furth-Matzkin, Assaf Hamdani, Howell Jackson, Louis Kaplow, Alon Klement, Roy Kreitner, Tamar Kricheli-Katz, Adi Leibovitch, Adi Libson, Da Lin, Ariel Porat, Mark Ramseyer, Steve Shavell, Holger Spamann, Cass Sunstein, Doron Teichman, Eyal Zamir, and workshop and conference participants at Harvard University, Hebrew University, New York University, Tel-Aviv University, The University of Chicago, and the annual meeting of the Israeli Law and Economics Association.

To maximize profits, sellers like to engage in price discrimination—to set higher prices for consumers who are willing to pay more and lower prices for consumers who are willing to pay less.
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86.1
Taking Data
Michael C. Pollack
Assistant Professor of Law, Benjamin N. Cardozo School of Law.

I am grateful to Miriam Baer, William Baude, Maureen Brady, Christopher Buccafusco, David Carlson, Nestor Davidson, Myriam Gilles, Ben Grunwald, Daniel Hemel, Michael Herz, Orin Kerr, Timothy Mulvaney, Luke Norris, John Rappaport, Shelley Ross Saxer, Ric Simmons, Edward Stein, James Stern, Stewart Sterk, Lior Strahilevitz, Matthew Tokson, Felix Wu, Stephen Yelderman, and participants in the AALS New Voices in Property Law Workshop, Cardozo Junior Faculty Workshop, Law and Society Annual Meeting, Mid-Atlantic Junior Faculty Forum at the University of Richmond Law School, and Southeastern Association of Law Schools New Scholars Workshop for their guidance, suggestions, comments, and critiques. I thank the Stephen B. Siegel Program in Real Estate Law for research support.

On February 16, 2016, a federal court ordered Apple to “assist law enforcement agents in enabling the search” of an iPhone that had been lawfully seized during the investigation into a mass shooting in San Bernardino, California.

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86.1
An Empirical Analysis of Sexual Orientation Discrimination
J. Shahar Dillbary
Professor of Law at The University of Alabama School of Law. BA in Law, LLB in Economics, Bar-Ilan University; LLM, JSD, The University of Chicago Law School

We would like to thank Yonathan Arbel, Ronen Avraham, David Bernstein, Bill Brewbaker, the Honorable Joseph Colquitt, Mirit Eyal-Cohen, Richard Delgado, Bryan Fair, Ron Krotoszynski, Susan Lyons, Jonathan Nash, Caryn Roseman, Stephen Rushin, Daiquiri Steele, Fred Vars, the participants in the 2017 Midwestern Law and Economics Association Conference, the 2018 American Law and Economics Association Conference and the Consumer Financial Protection Bureau’s combined Workshop on Fair Lending and the Office of Research for their helpful comments; and Shannon McLaughlin, Joshua Polk, Laura Stephenson, and Nic Nivison for their excellent research assistance. We also want to thank an anonymous referee for insightful comments and suggestions. We are indebted to Blake Beals for his help in assembling the municipal database. Authors are ordered alphabetically.

Griffin Edwards
Assistant Professor of Business at The University of Alabama, Birmingham, Collat School of Business. PhD in Economics, Emory University.
Twenty years ago, a gay couple entered their local bank in Arroyo Grande, California to ask for a mortgage loan.

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