Resources for Understanding the Ethical Implications of Artificial Intelligence (AI)

Illustration of an AI robot's head in profile alongside text that reads "Ethics + Artificial Intelligence"

Artificial intelligence (AI) is a topic on everyone’s mind. From ALA’s Annual Conference to the halls of Congress and even the White House, everyone seems to have an opinion on this technology and, moreover, intense worry about what it portends for the future. Alongside the need for regulations on AI, there are also complex ethical implications involved with this issue. Ahead of TIE‘s webinar “Inclusive and Ethical AI for Academic Libraries,” this resource list is intended to expand the discussion on the ethical implications and potential shortfalls of different AI technologies while enabling readers to envision more ethical outcomes.

In addition to delving into the resources below, readers interested in learning more on this topic are also encouraged to attend TIE‘s upcoming webinar as well as the upcoming webinar on AI ethics and citation from our sister blog LibTech Insights (LTI).

Race and AI

  1. Algorithms of Oppression: How Search Engines Reinforce Racism (2018) by Safiya Umoja Noble
  2. Assessing and Mitigating Bias in Medical Artificial Intelligence: The Effects of Race and Ethnicity on a Deep Learning Model for ECG Analysis” (2020) by Peter A. Noseworthy et al. in Circulation: Arrhythmia and Electrophysiology
  3. Distributed Blackness: African American Cyber Cultures (2020) by André Brock, Jr.
  4. Exclusive: OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic” (2023) by Billy Perrigo in TIME
  5. Making Kin with the Machines” (2018) by Jason Edward Lewis, Noelani Arista, Archer Pechawis, and Suzanne Kite in Journal of Design and Science
  6. Preventing Racial Bias in Federal AI” (2020) by Morgan Livingston in Journal of Science Policy & Governance
  7. Race After Technology: Abolitionist Tools for the New Jim Code (2019) by Ruha Benjamin
  8. Viral Justice: How We Grow the World We Want (2022) by Ruha Benjamin

Gender and AI

  1. AI Must Not Make Women’s Working Lives Worse” (2022) by Gina Neff in OECD.AI
  2. HashtagActivism: Networks of Race and Gender Justice (2020) by Sarah J. Jackson, Moya Bailey, and Brooke Foucault Welles
  3. Misogynoir Transformed: Black Women’s Digital Resistance (2021) by Moya Bailey
  4. These Women Tried to Warn Us About AI” (2023) by Lorena O’Neil in Rolling Stone

Disability and AI

  1. Ableism And Disability Discrimination In New Surveillance Technologies” (2022) by Lydia X. Z. Brown et al. from the Center for Democracy & Technology
  2. Artificial Intelligence and Disability: Too Much Promise, Yet Too Little Substance?” (2020) by Peter Smith and Laura Smith in AI and Ethics
  3. Can AI System Meet the Ethical Requirements of Professional Decision-Making in Health Care?” (2021) by Alan Gillies and Peter Smith in AI and Ethics
  4. Data Rich or Data Calm? A Rethinking of the Built Environment” (2022) by Louise Hickman for the Centre for Research in the Arts, Social Sciences and Humanities
  5. Definition Drives Design: Disability Models and Mechanisms of Bias in AI Technologies” (2023) by Denis Newman-Griffis et al. in First Monday
  6. Disability, Bias, and AI” (2019) by Meredith Whittaker et al. from the AI Now Institute
  7. “The Ethical Issues Raised By The Use Of AI Products For The Disabled: An Analysis By Two Disabled People” by Laura Smith and Peter Smith in Ethics in Online AI-Based Systems (2024)
  8. “The Robot Voice Contrasted With the Voice of Two Disabled People: A Reflective Piece” by Laura Smith and Peter Smith in AI Ethics and Higher Education: Good Practice and Guidance for Educators, Learners, and Institutions (2022)
  9. What Is the Point of Fairness? Disability, AI and the Complexity of Justice” (2019) by Cynthia L. Bennett and Os Keyes in SIGACCESS Newsletter
  10. Willful Dictionaries and Crip Authorship in CART” by Louise Hickman in Crip Authorship: Disability as Method (2023) ed. by Mara Mills and Rebecca Sanchez

Online Resources on AI

  1. Art, AI, and Disability Futures” (2022) talk by Lindsey Felt for Stanford University Human-Centered Artificial Intelligence 2022
  2. CLEARer Dialogues with AI: Unpacking Prompt Engineering for Librarians” (2023) webinar for LibTech Insights
  3. Coded Bias (2021) film directed by Shalini Kantayya for PBS
  4. Crip AI: Towards Disability-led Design” (2021) talk by Louise Hickman for the British Science Association
  5. Distributed AI Research Institute (DAIR)
  6. Experiments in Art, Access & Technology” (2023-24) exhibit curated by Vanessa Chang and Lindsey D. Felt for Leonardo CripTech Incubator
  7. Opportunities and Challenges of AI for Accessibility – Cynthia Bennett and Shari Trewin” (2023) talk by Cynthia Bennett and Shari Trewin for Accessibility NYC
  8. A Reading List for Algorithmic Bias: Five Great Books to Get You Started” (2023) by Marcella Fredriksson for LibTech Insights

General Sources on AI

  1. Algorithms for the People: Democracy in the Age of AI (2023) by Josh Simons
  2. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence (2021) by Kate Crawford
  3. Bias in Artificial Intelligence Algorithms and Recommendations for Mitigation” (2023) by Lama H. Nazer et al. in PLOS Digital Health
  4. Creating Human Nature: The Political Challenges of Genetic Engineering (2022) by Benjamin Gregg
  5. Data Ethics of Power: A Human Approach in the Big Data and AI Era (2021) by Gry Hasselbalch
  6. An Ethical Internet?” (2022) by Moya Bailey in Just Tech
  7. Ethical Machines: Your Concise Guide to Totally Unbiased, Transparent, and Respectful AI (2022) by Reid Blackman
  8. The Ethics Of Algorithms: Key Problems and Solutions” (2021) by Andreas Tsamados et al. in AI and Society
  9. Millions of Workers Are Training AI Models for Pennies” (2023) by Niamh Rowe in Wired
  10. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” (2021) by Emily M. Bender et al. Proceedings of the ACM Conference on Fairness, Accountability, and Transparency
  11. Semantics Derived Automatically from Language Corpora Contain Human-like Biases” (2017) by Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan in Science
  12. Sentencing and Artificial Intelligence (2022) ed. by Jesper Ryberg and Julian V. Roberts
  13. Technology Can’t Fix This” (2020) Editorial in Nature Machine Intelligence
  14. Towards Intellectual Freedom in an AI Ethics Global Community” (2021) by Christoph Ebell et al. in AI and Ethics
  15. Unmasking AI: My Mission to Protect What Is Human in a World of Machines (2023) by Joy Buolamwini

TIE is grateful to the following experts, including some Choice reviewers, who graciously contributed specialized recommendations to this list:

Headshot of Dr. Meryl Alper

Dr. Meryl Alper

Associate Professor, Department of Communication Studies, Northeastern University

Headshot of Dr. Moya Bailey

Dr. Moya Bailey

Associate Professor, Department of Communication Studies, Northwestern University

Lauren Delaubell headshot

Lauren deLaubell

Associate Librarian, SUNY Cortland

Vector illustration of a generic silhouette avatar of a person in black

Taylor Greene

Chair of Research and Instructional Services Division and Performing Arts Librarian, Chapman University

Headshot of Dr. Benjamin Gregg

Dr. Benjamin Gregg

Professor, Department of Government, University of Texas, Austin

Headshot of Dr. Mara Mills

Dr. Mara Mills

Associate Professor, Department of Media, Culture, and Communication, New York University

Vector illustration of a generic silhouette avatar of a person in black

Mark Mounts

Discovery Systems Librarian, Dartmouth College

Headshot of Dr. Archer Pechawis

Dr. Archer Pechawis

Assistant Professor, Department of Visual Art & Art History, York University, Canada

Headshot of Dr. Peter Smith

Dr. Peter Smith

Emeritus Professor, Department of Computer Science, University of Sunderland, UK


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Interested in contributing to TIE? Send an email to Deb V. at Choice dvillavicencio@ala-choice.org with your topic idea.


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