Welcome to the homepage for MS&E234, Data Privacy and Ethics (Winter 2019). This course engages with difficult ethical challenges in the modern practice of data science. The three main focuses are data privacy, personalization and targeting algorithms, and online experimentation. The focus on privacy will raise both practical and theoretical considerations. As part of the module on experimentation, students will be required to complete the Stanford IRB training for social and behavioral research. The course will assume a strong familiarity with the practice of machine learning and data science. Strongly recommended: MS&E 226, MS&E 231, CS 229, or equivalents.
The course meets on Tuesdays and Thursdays in  Building 380, Room 380D, at 1:30-2:50pm. As a general rule Tuesdays will be lectures and Thursdays will be discussion seminars.


Instructor: Prof. Johan Ugander (MS&E), jugander@
Office hours: Thursdays 3-4pm
TA: Jan Overgoor (overgoor@)
Office hours:
  • Thu Jan 17 15:00-16:00 (Huang 306)
  • Tue Jan 22 12:00-13:00 (Huang 304)
  • Thu Feb 07 15:00-16:00 (Huang 306)
  • Tue Feb 12 12:00-13:00 (Huang 304)
  • Thu Feb 28 15:00-16:00 (Huang 306)
  • Tue Mar 05 12:00-13:00 (Huang 304)
The course evaluation consists of three parts: problem sets (40%), in-class discussion leading and participation (20%), and group project reports and presentations (40%). There will be 3 problem sets that include significant data manipulation and coding. These will be due during Week 3, Week 6, and Week 9. Students will rotate to lead Thursday discussions. Group projects will be developed over the course of the quarter and presented during Week 10.
The detailed course readings are given below. This is only the second time this course is being given, so the course content will change slightly between now and the start of the course. The evaluation criteria will not.


Week 1: Introduction (1/8, 1/10)


Week 2: Digital exhaust and privacy (1/15, 1/17)
Discussion paper: Sweeney (2000)


Week 3: Social networks, social data (1/22, 1/24)

Discussion paper: Kosinski et al. (2013)


Week 4: Data transparency, public records, right to be forgotten (1/29, 1/31)
Discussion paper: Bertram et al. (2018)


Week 5: Search engines and recommendation systems (2/5, 2/7)
Discussion paper: White & Horvitz (2015)


Week 6: Fingerprinting and Personalization (2/12, 2/14)
Discussion paper: Englehardt & Narayanan (2016).


Week 7: A/B testing, experimentation (2/19, 2/21)
Discussion paper: Kramer et al. (2014)


Week 8: Differential privacy (2/26, 2/28)
Discussion paper: Ji et al. (2014)


Week 9: Privacy Regulation, GDPR (3/5, 3/7)
Discussion paper: Goodman & Flaxman (2016)


Week 10: Presentations (3/12, 3/14)
  • Presentations by students.
Students with Documented Disabilities
Students who may need an academic accommodation based on the impact of a disability must initiate the request with the Office of Accessible Education (OAE). Professional staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter for faculty dated in the current quarter in which the request is made. Students should contact the OAE as soon as possible since timely notice is needed to coordinate accommodations. For more information: http://studentaffairs.stanford.edu/oae