Week 8: Automating Justice?

Guiding Questions

While last week was about how automation can hurt vulnerable minorities, this week’s meeting is about the opposite: How can the same be used to fight discrimination? Discrimination is notoriously hard to detect and to prove, whether the decision-maker is a human or an algorithm. We also look at a case where automation helped to undo a racial disparity: California’s clearing of past marijuana convictions, which fell disproportionately on Black residents.

Required readings

• Kleinberg, Jon and Ludwig, Jens and Mullainathan, Sendhil and Sunstein, Cass R (2018). Discrimination in the Age of Algorithms. Journal of Legal Analysis, 10, pp. 113–174.
• Pahlka, Jennifer (2023). Recoding America: Why Government Is Failing in the Digital Age and How We Can Do Better. New York: Metropolitan Books. [PDF on Moodle] Chapter 12.

Further reading

• Bertrand, Marianne and Mullainathan, Sendhil (2004). Are Emily and Greg More Employable Than Lakisha And Jamal? A Field Experiment on Labor Market Discrimination. American Economic Review, 94(4), pp. 991–1013.
• Edelman, Benjamin and Luca, Michael and Svirsky, Dan (2017). Racial Discrimination in the Sharing Economy: Evidence from a Field Experiment. American Economic Journal: Applied Economics, 9(2), pp. 1–22.
• Hangartner, Dominik and Kopp, Daniel and Siegenthaler, Michael (2021). Monitoring Hiring Discrimination Through Online Recruitment Platforms. Nature, 589(7843), pp. 572–576.