Machine Learning (ALA Midwinter 2019)

I gave a talk at the American Library Association 2019 Midwinter conference entitled “Machine Learning: How Does It Work?!?”

Slides: .key (original version), .pdf

Bibliography

If you’re here because I encouraged you to check out my talks page to educate yourself on ML and its discontents, thanks! I extracted the bibliography from the slides for your convenience.

Library AI Examples

In Which Hilarity Ensues

Critical Awareness & Social Impact

  • Matthew Reidsma, “Algorithmic Bias in Library Discovery Systems” (if you read only one, make it this)
  • Data for Black Lives: @data4blacklives, http://d4bl.org/ — D4BL runs an outstanding conference whose livestreams you can find on YouTube.
  • Pro Publica Machine Bias series
  • Montana State University IMLS-funded work on Algorithmic Awareness — This will produce an undergraduate course at MSU as well as training materials for librarians at other institutions.
  • Syllabus for Dorothea Salo’s “Code and Power” course at UW-Madison
  • Meredith Broussard, Artificial Unintelligence: How Computers Misunderstand the World
  • Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor — you can also see video of her presenting on the book’s topics
  • Safiya Noble, Algorithms of Oppression: How Search Engines Reinforce Racism
  • Cathy O’Neil, Weapons of Math Destruction:  How Big Data Increases Inequality and Threatens Democracy

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