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Dean's Smart Lab, 4th Floor, SBASSE
Reading Circle II - Fall 2026 | Values in Systems Thinking
AI is shaping how analysis is produced and how quickly. What genuinely changes in the knowledge we make, and what assumptions carry over untouched?
Machine learning systems encode values through the same mechanisms as any other analytical instrument: through what is optimised, what is measured, and what is left out. As generative tools enter modelling workflows, the question is which parts of analytical judgement are being automated, and whether accountability travels with them.
Suggested readings:
- Birhane, A., Kalluri, P., Card, D., Agnew, W., Dotan, R., & Bao, M. (2022). The values encoded in machine learning research. Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, 173–184.
- Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623.
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