AI is eating the world. Unfortunately, these machine learning models have drawn attention in recent years for automating discrimination and being “biased” — a broad term with many distinct manifestations. Within genomics, a field full of complicated ML, these biases lead to dramatically different health outcomes for persons of different socioeconomic status or ancestry. Neither AI nor genomics can be fully “de-biased” in a single semester, but we hope to provide a detailed overview of existing problems and known frameworks to detect and prevent bias through the emerging field of algorithmic fairness.

This student-led discussion group (with multiple anticipated guest speakers!) is designed to equip the next generation of researchers with the awareness and structural competencies to address bias, and is divided into two consecutive parts.

Part 1: Algorithmic Fairness in AI (approx. weeks 1-6, 8)

Part 2: Fairness and Model Portability in Genomics (approx. weeks 7, 9-15)

CS-focused enrollees may consider the 1-hour enrollment option, while Genomics or Computational Biology enrollees should opt for the complete 2-hour option. At the end of the course, we hope participants will be able to answer the following in their own terms:

1. What is fairness in machine learning, and what are common causes of unfairness?
2. How can cultural biases impact datasets and modeling assumptions? What kind of approaches can account for this situation?
3. (2-hour option) What parallels exist between algorithmic fairness and model portability in genomics?
4. (2-hour option) How can we account for patterns of genetic variation when analyzing genomic data?

We intend it to be straighforward to pass the class, and attendance and participation will count for a good portion of the grade.

1-hour enrollees should have much more attendance flexibility; 2-hour enrollees will be expected to attend most discussions (not necessarily all). Reading responses and surveys will constitute the second portion of the grade, and 2-hour enrollees will have a ~ 3-page short report (or alternatively, a short presentation) at the end of the DeCal.

For more details, please reach out to the creators and consult the syllabus on bCourses: https://bcourses.berkeley.edu/courses/1507691/assignments/syllabus

We welcome volunteers willing to present as a guest lecturer! :)

Enrollment will be open (first come, first served) Note: there is a 1-hour and a 2-hour enrollment option, so please make sure you enroll in the section you wish to receive credit for Calcentral course numbers for enrollment: 1 hour section: 33440 2 hour section: 33441 (no access code necessary, leave blank!)