DS457/DS657/JD673: Law and Algorithms

Course Overview

This cross-cutting and interdisciplinary course, taught jointly between the School of Law, the faculty of Computing and Data Sciences, and Computer Science investigates the role that algorithms and automated decision-making systems play in law and society. The course connects legal and computational concepts of transparency, fairness, bias, trust, and privacy, though a series of case studies that present recent applications of technology to legal and regulatory situations and explore the challenges in regulating algorithms.

Legal concepts explored will include evidence and expert witnesses, anti-discrimination law concepts of disparate impact and disparate treatment, sectoral information privacy regimes, and public access and transparency laws. Computational concepts explored will include artificial intelligence and machine learning, secure multi-party computation, differential privacy, and zero-knowledge proofs.

PLEASE NOTE: DUE TO THE CROSS LISTING OF THIS COURSE, THERE ARE SOME STRANGE LOGISTICS TO BE AWARE OF! MAKE SURE TO READ THE FOLLOWING!

  • THIS COURSE IS SCHEDULED FROM 2:10-4:10 in the Law Tower Room 203. Note that this is different than the listed time and location in student link for DS457/DS657
  • This course follows the Law School's Academic Calendar. That means that the first class period is on Thursday, January 19.

The syllabus for this semester (Spring 2023) can be found here. Please note that the syllabus currently lists the wrong room. We will be in Room 203.

Readings

Class 1: Intro to Law and Algorithms (Jan. 19)

Required

Intro to Computational Thinking:
Intro to Law and Legal Thinking
The Opportunities of Law & Algorithms:
The Collision of Law & Algorithms:
What Lies Underneath Technological Governance:
  • Catherine D’Ignazio and Lauren F. Klein, “The Power Chapter,” from Data Feminism (2020) – read sections on “Data Science by Whom?” and “Data Science for Whom?”

Optional

Class 2 – The Development and Legal Protection of Software (Jan. 27)

Required

How Software is Built, How Software Breaks
Concepts of Verification and Validation
How Software is Protected in Law
How Software is Examined in Litigation
Tensions in Intellectual Property and Software Scrutiny

Optional

Class 3 – Putting the TrueAllele Algorithm on Trial (Feb. 2)

Required

TrueAllele on Trial
Transparency as a Solution and its Critics
The Limits of Transparency Through Adversarial Litigation:
Alternatives:

Optional

Class 4 – Foundational Concepts in Privacy and Secrecy (Feb. 9)

Required

Introduction to Secrecy in Computing
Basic cryptography: encryption, signatures, and hashing
Advanced applications: secure multi-party computation and zero-knowledge proofs
Secrecy vs. Privacy
  • Daniel Solove, Understanding Privacy (2008) – read introduction to Chapter 1 (pp. 1–2); “The Concept of Privacy” (pp. 6–8); and “A New Theory of Privacy” (pp. 8–11)
Who is Centered in Cryptography Policy?

Optional