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COMP_SCI 497: The Science of Law and Computation

Quarter Offered

Spring : 3:30 -6:20 Th ; Hartline & Linna

Prerequisites

Ph.D. status or permission of the instructors

Description

This advanced topics seminar explores the many parallels between the science of law and the science of computation. Both fields require understanding outcomes produced by the interpretation of written instructions, understanding when written instructions are effective, and understanding systems for producing effective written instructions. For example, on the computer science side, these written instructions include protocols, algorithms, and programs, while on the law side, these written instructions include rules, standards, contract clauses, regulations, and laws. This course aims to identify fruitful avenues for research that combine legal reasoning and the principles of the rule of law with computer science technical approaches (algorithms, machine learning, programming languages, cryptography, etc).

Coursework

​​Each week considers a different topic. Each student will present at least one paper and lead a discussion session. (Students must reach out to the instructors at least one week before their presentation to schedule a planning session with the instructors.)

Coursework includes a survey paper and a preliminary study for a research project. Each week, pairs of students must organize a one-hour meeting with CS and Law faculty advisors to discuss their research projects.

Logistics

Participants read and annotate papers before each meeting and engage in text-based discussion on a collaborative reading and annotation platform. Participants identify questions of interest at least 24 hours before each class meeting. Assigned students begin each session by presenting the week’s papers.

General meeting structure:

  • Paper 1: Paper presented for 15 minutes
  • Paper 2: Paper presented for 15 minutes
  • 90 minutes of discussion and collaborative note taking
  • 60 minutes: Students meet with CS and Law faculty mentors to discuss their survey papers and research projects
During each session, students assigned to present papers at the next class meeting are responsible for taking notes and circulating the notes to all participants within 24 hours after the class meeting.

Technology

  • Gather and Zoom
  • Online platform for reading, annotating the reading, and online text-based discussion about the readings.

Schedule

Week 1: Introduction and overview of topics
  • No readings
  • Presentation data sources, including from courts (follow up presentations intermittently throughout the rest of the term)
Week 2: Scientific Methods for Law

Summary:

Week 3: Rules vs Standards

Summary: Rules are specified precisely without regard to context, while standards must be interpreted in context. How do they compare in terms of producing desirable outcomes?

Week 4: Accountability

Summary:

  • David Freeman Engstrom & Daniel E. Ho, Algorithmic Accountability in the Administrative State, 37 Yale J. On Reg __ (forthcoming 2020) [49 pages], https://digitalcommons.law.yale.edu/yjreg/vol37/iss3/1/
  • Lukas Lazarek, Alexis King, Samanvitha Sundar, Robert Bruce Findler, and Christos Dimoulas. 2019. Does blame shifting work? Proc. ACM Program. Lang. 4, POPL, Article 65 (January 2020), 29 pages. DOI:https://doi.org/10.1145/3371133
Week 5: Verification

Summary:

  • Paul W. Grimm, Maura R. Grossman, Gordon V. Cormack, Artificial Intelligence as Evidence, 19 Northwestern Journal of Technology & Intellectual Property __ (forthcoming; pre-publication draft dated March 7, 2021).
  • Sections 1 and 2 of: Fisch B., Freund D., Naor M. (2014) Physical Zero-Knowledge Proofs of Physical Properties. In: Garay J.A., Gennaro R. (eds) Advances in Cryptology – CRYPTO 2014. CRYPTO 2014. Lecture Notes in Computer Science, vol 8617. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44381-1_18 (Excerpted article at: https://www.iacr.org/archive/crypto2014/86160292/86160292.pdf )
  • Section 1 of: Shafi Goldwasser and Sunoo Park. 2017. Public Accountability vs. Secret Laws: Can They Coexist? A Cryptographic Proposal. In Proceedings of the 2017 on Workshop on Privacy in the Electronic Society (WPES '17). Association for Computing Machinery, New York, NY, USA, 99–110. DOI:https://doi.org/10.1145/3139550.3139565
  • Glaser, A., Barak, B. & Goldston, R. A zero-knowledge protocol for nuclear warhead verification. Nature 510, 497–502 (2014). https://doi.org/10.1038/nature13457
  • Optional introductory materials: Jean-Jacques QuisquaterMyriam QuisquaterMuriel QuisquaterMichaël QuisquaterLouis GuillouMarie Annick GuillouGaïd GuillouAnna GuillouGwenolé GuillouSoazig Guillou, How to Explain Zero-Knowledge Protocols to Your Children (1989), http://pages.cs.wisc.edu/~mkowalcz/628.pdf
  • Optional: Yuqing Cui, Application of Zero-Knowledge Proof in Resolving Disputes of Privileged Documents in E-Discovery, Harvard Journal of Law & Technology (Spring 2019), https://jolt.law.harvard.edu/assets/articlePDFs/v32/32HarvJLTech633.pdf
Week 6: Validation (Better Legal Outcomes)

Summary: How can computational technology help enable accountability in legal systems?

Week 7: Network Theory
  • Pedraza-Fariña, Laura G. and Whalen, Ryan, A Network Theory of Patentability, University of Chicago Law Review, Volume 87, No. 1, (2020), https://lawreview.uchicago.edu/publication/network-theory-patentability
  • Lars Backstrom and Jon Kleinberg. 2014. Romantic partnerships and the dispersion of social ties: a network analysis of relationship status on facebook. In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing (CSCW '14). Association for Computing Machinery, New York, NY, USA, 831–841. DOI:https://doi.org/10.1145/2531602.2531642
Week 8: Bias and Fairness I

Summary:

Week 9: Bias and Fairness II

Summary:

  • Rebecca Wexler, Privacy Asymmetries: Access to Data in Criminal Defense Investigations (July 29, 2019). UCLA Law Review, Vol. 68, No. 1, 2021, Available at SSRN: https://ssrn.com/abstract=3428607
  • Michael Feldman, Sorelle A. Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian. 2015. Certifying and Removing Disparate Impact. In Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '15). Association for Computing Machinery, New York, NY, USA, 259–268. DOI:https://doi.org/10.1145/2783258.2783311
Week 10: Computational Antitrust Final Presentations (during Exam Week)
  • Student final presentations
  • Poster session with extended Q&A

COURSE COORDINATOR: Prof. Jason Hartline & Prof. Daniel W. Linna Jr.

COURSE INSTRUCTOR: Prof. Jason Hartline & Prof. Daniel W. Linna Jr.