POWER ON! NOTES

  1. Encyclopedia Britannica, “Artificial Intelligence,” accessed November 5, 2020, https://www.britannica.com/technology/artificial-intelligence
  2. Oxford English Dictionary, “Algorithm,” accessed November 5, 2020, https://www.lexico.com/en/definition/algorithm
  3. See http://beauty.ai; Jordan Pearson, “Why an AI-Judged Beauty Contest Picked Nearly All White Winners,” Vice, September 5, 2016, https://www.vice.com/en_us/article/78k7ed/why-an-ai-judged-beauty-contest-picked-nearly-all-white-winners; Ruha Benjamin, Race after Technology (Cambridge: Polity, 2019); and Sam Levin, “A Beauty Contest Was Judged by AI and the Robots Didn’t Like Dark Skin,” Guardian, September 8, 2016, https://www.theguardian.com/technology/2016/sep/08/artificial-intelligence-beauty-contest-doesnt-like-black-people
  4. See Oscar Schwartz, “In 2016, Microsoft’s Racist Chatbot Revealed the Dangers of Online Conversation,” IEEE Spectrum, November 25, 2019, https://spectrum.ieee.org/artificial-intelligence/machine-learning/in-2016-microsofts-racist-chatbot-revealed-the-dangers-of-online-conversation
  5. See Cade Metz, “There Is a Racial Divide in Speech-Recognition Systems, Researchers Say,” New York Times, March 23, 2020, https://www.nytimes.com/2020/03/23/technology/speech-recognition-bias-apple-amazon-google.html
  6. See also Heidi Ledford, “Millions of Black People Affected by Racial Bias in Health-Care Algorithms,” Nature, October 24, 2019, https://www.nature.com/articles/d41586-019-03228-6
  7. Joy Buolamwini, “How I’m Fighting Bias in Algorithms,” video filmed November 2016 at TEDxBeaconStreet, Brookline, MA. Video, 8:36. https://www.ted.com/talks/joy_buolamwini_how_i_m_fighting_bias_in_algorithms
  8. Data given on this page comes from: National Center for Women and Information Technology, “By the Numbers,” April 21, 2020, https://www.ncwit.org/resources/numbers; and Allison Scott, Sonia Koshy, Meghana Rao, Laura Hinton, Julie Flapan, Alexis Martin, and Frieda McAlear, Computer Science in California’s Schools: An Analysis of Access Enrollment, and Equity (Oakland, CA: Kapor Center, 2019), https://mk0kaporcenter5ld7la.kinstacdn.com/wp-content/uploads/2019/06/Computer-Science-in-California-Schools.pdf.
  9. Data on this page reported by GLSEN in Joseph G. Kosciw, Caitlin M. Clark, Nhan L. Truong, and Adrian D. Zongrone, The 2019 National School Climate Survey: The Experiences of Lesbian, Gay, Bisexual, Transgender, and Queer Youth in Our Nation’s Schools (New York: GLSEN, 2020); reported in Robert R. Redfield, Anne Schuchat, Leslie Dauphin, et al., Youth Risk Behavior Surveillance—United States, 2017 (Washington, DC: US Department of Health and Human Services, Centers for Disease Control and Prevention, 2017); and reported in the Human Rights Campaign Foundation, 2019 Black and African American LGBTQ Youth Report (Washington, DC: Human Rights Campaign, 2019).
  10. For more information, see Unidos US’s “7 Ways Immigrants Enrich Our Economy and Society” fact sheet at https://www.unidosus.org/issues/immigration/resources/facts, and Marshall Fitz, Philip E. Wolgin, and Patrick Oakford, “Immigrants Are Makers, Not Takers,” Center for American Progress—Immigration, February 8, 2013, https://www.americanprogress.org/issues/immigration/news/2013/02/08/52377/immigrants-are-makers-not-takers/ .
  11. Jane Margolis with Rachel Estrella, Joanna Goode, Jennifer Jellison Holme, and Kim Nao, Stuck in the Shallow End: Education, Race, and Computing, updated ed. (Cambridge, MA: MIT Press, 2017).
  12. Ziad Obermeyer, Brian Powers, Christine Vogeli, and Sendhil Mullainathan, “Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations,” Science 336 (2019): 447–453.
  13. Cathy O’Neil, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (New York: Broadway Books, 2016).
  14. Ruha Benjamin, Race after Technology (Cambridge: Polity, 2019).
  15. Safiya Umoja Noble, Algorithms of Oppression: How Search Engines Reinforce Racism (New York: NYU Press, 2018).
  16. Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (New York: St. Martin’s Press, 2018).
  17. Computer Science ForAll: https://obamawhitehouse.archives.gov/blog/2016/01/30/computer-science-all
  18. CDC Drowning Facts: https://www.cdc.gov/drowning/data-research/facts/?CDC_AAref_Val=https://www.cdc.gov/drowning/facts/index.html
  19. Margot Lee Shetterly, Hidden Figures: The American Dream and the Untold Story of the Black Women Who Helped Win the Space Race (New York: William Morrow, 2016).