Readings

In the fall semester we took a deep dive into various areas of AI harm. Here are some of the topics and readings we studied.

AI Bias and Discrimination

  1. Watch: Coded Bias. Shalani Kantayya. 2020. 
  2. “Machine Bias.” Julia Angwin, Jeff Larson, Surya Mattu, Lauren Kirchner. Pro Publica, 2016.
  3. “Amazon scraps secret AI recruiting tool that showed bias against women.” Jeffery Dastin. Reuters, 2018. 
  4. “The Hidden Biases of Big Data.”Kate Crawford. Harvard Business Review, 2013
  5. “Dissecting racial bias in algorithm used to manage the health of populations.” Zaid Obermyer, Brian Powers, Chrsitine Vogeli, Sendhil Mullainathan. Science, 2019. 
  6. “Algorithms are making decisions about health care, which may only worsen medical racism.” Crystal Grant. ACLU, 2022. 
  7. “The coming war on the hidden algorithms that trap people in poverty.” Karen Hao, MIT Technology Review, 2020. 
  8. “UK regulators warn banks on use of AI in loan applications.” Laura Noonan. Financial Times, 2022.
  9. Excerpts Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Cathy O’Neil. Random House, 2016. 
  10. “Predictive Policing is happening now — and police could learn a lesson from Minority Report.” David Robinson. Medium, 2016. 
  11. “One Month, 500,000 Face Scans: How China Is Using A.I. to Profile a Minority.” Paul Mozur. New York Times, 2019.

AI and the Environment

  1. Anatomy of an AI System: The Amazon Echo as an anatomical map of human labor, data and planetary resources. Kate Crawford, Vladan Joler. 2018. 
  2. “AI can help us fight climate change but it has an energy problem too.” Annette Ekin. Horizon: The EU Research & Innovation Magazine. 2019.
  3. Excerpts AI in the Wild: Sustainability in the Age of Artificial Intelligence. Peter Dauvergne. MIT Press, 2020.
  4. “Customer Experience in the Age of AI.” David C. Edelman, Mark Abraham. Harvard Business Review, 2022. 

AI Radicalization and Extremism  

  1. Listen: “Down the Rabbit Hole by Design – With Guillaume Chaslot.” Your Undivided Attention podcast. 2019.
  2. “Welcome to the ‘Rabbit Hole’.” Kevin Roose. The New York Times, 2020.
  3. “A glimpse into facebook’s opaque and potentially vulnerable trending algorithm.” Dave Gershgorn, Mike Murphy. Quartz, 2016. 
  4. “Fueling the Fire: How Social Media Intensifies Political Polarization” Paul Barret, Justin Hendrix, J. Grant Sims. NYU Stern, 2021.
  5. “A Genocide Incited on Facebook, With Posts from Myanmar’s Military.” Paul Mozur. The New York Times, 2018.
  6. “The Existential Threat of AI Generated Disinformation.” Bradley Honigberg. Just Security, 2022. 
  7. “Why Meta’s latest large language model lasted only three days online.” Will Douglas Heaven. MIT Technology Review, 2022. 
  8. “The Deepfake Dangers Ahead,” by Daniel Byman, Chris Meserolke and V.S. Subrahmanian, Wall Street Journal, 2023 
  9. “Can we no longer believe anything we see?” Tiffany Hsu and Steven Lee Myers. New York Times, 2023. 

Privacy and Surveillance in the Age of AI

  1. Excerpts from The Age of Surveillance Capitalism. Shoshana Zuboff. PublicAffairs, 2019. 
  2. “The Complicated Truth about China’s Social Credit System.” Kevin Hong. Wired, 2019.
  3. “OpenAI’s hunger for data is coming back to bite it.” Melissa Heikkilä. MIT Technology Review, 2023.
  4. “Facebook and Cambridge Analytica: What you need to know as fallout widens.” Kevin Granville. The New York Times, 2018.
  5. “Why I deleted Foursquare and why you should too.” Lee Kolbert. HuffPost, 2017. 
  6. “Scanning student rooms during remote tests is unconstitutional, judge rules.” Emma Bowman. NPR, 2022. 
  7. Executive Summary of The Perpetual Lineup (includes Key Findings and Recommendations). Claire Garvie, Alvaro Bedoya, Jonathan Frankle. Georgetown Law, 2016.
  8. “Your Face is Not Your Own” by Kashmir Hill, N.Y. Times (March 18, 2021) 
  9. “Eight Months Pregnant and Arrested After False Facial Recognition Match” by Kashmir Hill, N.Y. Times (August 6, 2023) available at 
  10. “Thousands of Dollars for Something I Didn’t Do,” by Kashmir Hill, N.Y. Times (March 31, 2023) available at 

AI’s Labor Problem

  1. Your AI is Human.” Sarah T. Roberts in Your Computer is On Fire. MIT Press, 2021. 
  2. “Chat GPT is about to revolutionize the economy. We need to decide what that looks like.” David Rotman, MIT Technology Review, 2023.
  3. “Inside the AI Factory.” Josh Dzieza. Intelligencer. 
  4. “OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic.” Billy Perrigo. TIME, 2023.
  5. “ChatGPT And More: Large Scale AI Models Entrench Big Tech Power” AI Now Institute, 2023.
  6. “The Dimensions of Data Labor.” Hanlin Li, Stevie Chancellor, Nicholas Vincent, Brent Hecht. FAcct, 2023.
  7. “The Cloud is a Factory.” Nathan Ensmenger in Your Computer is on Fire. MIT Press, 2021. 

How to Audit an AI

  1. “Inferences & Connections.” Alex Rosenblat, Tamara Kneese, and Danah boyd, 2014.
  2. “Model Cards for Model Reporting.” Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru. 2019.
  3. “Algorithmic Accountability: Journalistic investigation of computational power structures” Nicholas Diakopoulos, Digital Journalism, 2014.
  4. “Auditing Algorithms: Research Methods for Detecting Discrimination on Internet Platforms.” Christian Sandvig, Kevin Hamilton, Karrie Karahalios, & Cedric Langbort, 2014.