Ethical Algorithm Design
CIS 4230/5230
Spring 2023
Tuesdays and Thursdays 10:15 11:45AM ET
Annenberg 110
Instructor:
Prof. Michael Kearns
mkearns@cis.upenn.edu
Office hours: Tuesday right after class until 1PM, in the lobby area right outside Annenberg 110
or by appointment
Teaching Assistants:
Neha Dohare
neha75@seas.upenn.edu
Office hours: Wednesday 10:3011:30AM in Levine 5th floor bump space
or by appointment
Declan Harrison
declanh@seas.upenn.edu upenn.edu
Office hours: Thursday 910AM in 4th floor 3401 Walnut
or by appointment
Natalie Ho
natabnho@sas.upenn.edu
Office hours: Wednesday 56PM in GRW 5th floor bump space
or by appointment
Jordan Hochman
jhawkman@seas.upenn.edu
Office hours: Thursday 5:156:15PM in GRW 5th floor bump space
or by appointment
Aakash Jajoo
aakashj1@seas.upenn.edu
Office hours: Tuesday 1:452:45PM in Levine 5th floor bump space
or by appointment
Course Description
This course is about the social and human problems that can arise from algorithms, AI and machine learning, and how we might design these technologies to be "better behaved" in the first place. It is first and foremost a science or engineering course, since we will be developing algorithm design principles. You can get a rough sense of course themes and topics by visiting the websites for the pilot versions of this course offered in 2021, 2020 and 2019. The first formal offering of the course was in Spring 2022.
Here are the lecture videos from the last pilot version. Please note that they will not correspond exactly to this year's lectures, and should not be viewed as a substitute for mandatory lecture attendance.
Prerequisites: Familiarity with some machine learning, basic statistics and probability theory will be helpful. While this is not a theory class, you need to be comfortable with mathematical notation and formalism. There will be some simple coding and data analysis assignments, so some basic programming ability is needed.
Course content will include readings from the scientifc literature, the mainstream media and other articles and books.
Grades will be based on a mixture of quizzes, coding assignments, written homeworks, and a written midterm and final.
CIS 423/523 fulfills the SEAS Engineering Ethics Requirement for these programs: ASCS, BE, CMPE, CSCI, DMD and NETS (but you should confirm with your academic adivsor to be certain).
Lecture Dates 
Topic 
Slides, Readings, Assignments, Announcements 

Thu Jan 12 
Course Introduction and Overview 
A generalaudience introduction to some of the themes of the course is given in the (recommended but not required) book The Ethical Algorithm: The Science of Socially Aware Algorithm Design, by M. Kearns and A. Roth. Also recommended but not required: Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, by C. O'Neil. 
Tue Jan 17 Tue Jan 19 
Foundations of Machine Learning 

Thu Jan 24 Tue Feb 26 
Bias in Machine Learning: COMPAS and ProPublica 
The following readings are required; you should read the two ProPublica pieces before the Jan 24 lecture so we can discuss them then. Practitioner's Guide to COMPAS Core (no need to read, but we'll peruse a bit together in lecture) COMPAS Risk Assesment Survey (just skim) Northpointe response to ProPublica ProPublica github repository, including dataset (we'll look at the dataset a bit in lecture)(technical, just skim) 
Tue Jan 31 Thu Feb 2 Tue Feb 7 Thu Feb 9 
Science of Fair ML: Models and Algorithms 
Readings (TBD): Inherent TradeOffs in the Fair Determination of Risk Scores. J. Kleinberg, S. Mullainathan, M. Raghavan.

Thu Mar 2 
Midterm Exam (in person, written)  . 