Resources

Normative vs. Descriptive / Ethical Frameworks

General / High-Level Overviews

  • Hare (1952), The Language of Morals [PDF]
    • This is the canonical book that explains, in excruciating but necessary detail, the linguistic “core” of the descriptive-versus-normative distinction. It’s overkill to read from cover-to-cover if you just want the gist of the concepts, but if you’re curious about how we can develop a “logic” of normative statements like we have for descriptive statements, this is the key text imo!
  • Korsgaard (1996), The Sources of Normativity [PDF]
    • This is… definitely up there among my favorite books of all time on this topic (after wading through many of them during the PhD exam gauntlet I mentioned in Week 1): it does what I wish every ethical-philosophy book did, which is, continuing to ask but why?!? to every theory of ethical justification, until it reaches a perspective which (not coincidentally) is quite close to the perspective we adopt early on in this course!
  • Roemer (1996), Theories of Distributive Justice [PDF]
    • I won’t lie to you, this book is pretty brutal in terms of being a mathematical “deep dive” into how the ethical frameworks we discuss in this class can be built up from a set of axioms. So, I don’t recommend the whole thing (that’s why there are two more Roemer books in this section, which are more applied looks at particular ethical frameworks!)
    • The two parts we will draw on, which I do therefore recommend, are the explanations of utility functions in Chapter 1 and of Social Welfare Functionals in Chapter 4

Particular Examples / Frameworks

  • Roemer (1988), Free to Lose: An Introduction to Marxist Economic Philosophy [PDF]
  • Anderson (2017), Private Government: How Employers Rule Our Lives (And Why We Don’t Talk About It) [PDF] [EPUB] [MOBI]
  • Rawls (1971), A Theory of Justice [PDF]
  • Roemer (1998), Equality of Opportunity [PDF]

Fairness in AI / Context-Sensitive Fairness

  • Barocas, Hardt, and Narayanan (2023), Fairness and Machine Learning: Limitations and Opportunities [PDF]
    • This will be our main reference during this portion of the course, and is available for free (legally!) online!
  • Kasy and Abebe (2021), “Fairness, Equality, and Power in Algorithmic Decision-Making”, FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency [PDF]

Econometric Policy Evaluation

  • Björkegren, Blumenstock, and Knight (2022), “(Machine) Learning what Policymakers Value”, EAAMO (Equity and Access in Algorithms, Mechanisms, and Optimization) [PDF]

References

Anderson, Elizabeth. 2017. Private Government: How Employers Rule Our Lives (and Why We Don’t Talk about It). Princeton University Press.
Barocas, Solon, Moritz Hardt, and Arvind Narayanan. 2023. Fairness and Machine Learning: Limitations and Opportunities. MIT Press.
Björkegren, Daniel, Joshua E. Blumenstock, and Samsun Knight. 2022. “(Machine) Learning What Policies Value.” arXiv. https://doi.org/10.48550/arXiv.2206.00727.
Hare, R. M. 1952. The Language of Morals. OUP Oxford.
Kasy, Maximilian, and Rediet Abebe. 2021. “Fairness, Equality, and Power in Algorithmic Decision-Making.” In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 576–86. FAccT ’21. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3442188.3445919.
Korsgaard, Christine M. 1996. The Sources of Normativity. Cambridge University Press.
Rawls, John. 1971. A Theory of Justice: Original Edition. Harvard University Press.
Roemer, John E. 1988. Free to Lose: An Introduction to Marxist Economic Philosophy. Harvard University Press.
———. 1996. Theories of Distributive Justice. Harvard University Press.
———. 1998. Equality of Opportunity. Harvard University Press.