Week 2: Machine Learning and Datasets

Schedule

Morning

  • Guest Lecture: Machine Learning as Idea, Technology, & Practice
  • Workshop: Getting to Know Google Teachable Machine

Afternoon

  • Lecture: The Ethics of ML Datasets (Crawford & Paglen, 2019; Gebru et al., 2021)
  • Workshop: Prototyping Datasets

Homework

Readings

  • Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data and Society, 3(1), 1–12. https://doi.org/10/gcd3mk
  • Mitchell, M., Wu, S., Zaldivar, A., Barnes, P., Vasserman, L., Hutchinson, B., Spitzer, E., Raji, I. D., & Gebru, T. (2019). Model Cards for Model Reporting. Proceedings of the Conference on Fairness, Accountability, and Transparency, 220–229. https://doi.org/10/gftgjg

Activities

  • Collect an image dataset

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