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AI & Society

Week 2: Machine Learning and Datasets

Schedule

Morning (8:45-12:45)

  • Opening (8:45-9:00)
  • Workshop: Google Teachable Machine (9:00-11:00)
  • Lecture: Machine learning as an idea, technology, and practice (Hiram Rodriguez, NXP) (11:00-12:00)
  • Discussion (12:00-12:30)
  • Closing (12:30-12:45)

Afternoon (13:45-17:45)

  • Opening (13:45-14:00)
  • Lecture: Ethics of datasets (James Broadhead) (14:00-15:00)
  • Workshop: Prototyping datasets (15:00-17:00)
  • Discussion (17:00-17:30)
  • Closing (17:30-17:45)

Homework

Readings: 

  1. 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
  2. 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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