by Pati Ruiz

As a former Spanish and computer science teacher, I think a lot about emerging technologies and how they apply in learning contexts. Recently, I have been focused on AI and how it affects students, their families, and communities. I am particularly interested in the consequences (intended and unanticipated) of these emerging AI technologies on historically excluded students, specifically Latinx, Black, Indigenous, and students with disabilities.

Working with the Center for Integrative Research on Computing and Learning Sciences (CIRCLS), I have seen work ranging from Intelligent Tutors and systems designed to adapt and personalize learning, including some that are developing pedagogical agents and robots. I’ve also seen work that seeks to minimize bias and promote equity in AI, projects using computer vision, natural language processing and speech technologies. Of all of these efforts, I consider the work to promote equity and accountability in AI to be the most important and I created this list to focus on those issues.

Last updated: May 14, 2021

Artificial Intelligence (AI)

• Exploring the Ethics of AI (Website Resource)
• Algorithmic injustice: a relational ethics approach by Abeba Birhane (Open Access)
• The History of Artificial Intelligence by Rockwell Anyoha (Open Access)
• Algorithmic Fairness in Education by René F. Kizilcec and Hansol Lee (Open Access)
• The Ethical Framework for AI in Education (Open Access)
• Algorithmic Accountability: A Primer (Open Access)
• Auditing Algorithms for Discrimination by Pauline Kim (Open Access)
• A People’s Guide To AI (Open Access)
• Disability, Bias, and AI from AI Now (Open Access)
• Facial Recognition Technologies: A Primer by Joy Buolamwini, Vicente Ordóñez, Jamie Morgenstern, and Erik Learned-Miller (Open Access)
• Facial Recognition Technologies in the Wild: A Call for a Federal Office by Erik Learned-Miller, Vicente Ordóñez, Jamie Morgenstern, and Joy Buolamwini (Open Access)
• The Whiteness of AI by Stephen Cave and Kanta Dihal (Open Access)
• AI and Accessibility By World Institute on Disability (Open Access)
• Toward fairness in AI for people with disabilities: A research roadmap by Anhong Guo, Ece Kamar, Jennifer Wortman Vaughan, Hanna Wallach, Meredith Ringel Morris (Open Access)
• Algorithms of Oppression: How Search Engines Reinforce Racism by Safiya Umoja Noble
• Design Justice: Community-Led Practices to Build the Worlds We Need by Sasha Costanza-Chock (Open Access)
• The problems AI has today go back centuries by Karen Hao (Open Access)
• Unintended machine learning biases as social barriers for persons with disabilities by Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl (Open Access) Note on title: Please see the previous article (The problems AI has today go back centuries) about using unanticipated when talking about the consequences of AI.
  “When people talk about unintended consequences, it sounds like they’re saying the consequences couldn’t have been predicted. But AI’s unintended consequences are in fact highly predictable if you just look back at history.” -Marie-Therese Png
• Film: Coded Bias
• Atlas of AI – Power, Politics, and the Planetary Costs of Artificial Intelligence by Kate Crawford

Critical Race Theory and Background Readings

• The Master’s Tools Will Never Dismantle the Master’s House by Audre Lorde (Open Access)
• The New Jim Crow: Mass incarceration in the age of colorblindness by Michelle Alexander
• Women of Color in Tech and/or Futures/Foresight Work
• Introduction: Race and/as Technology; or, How to Do Things to Race by Wendy Hui Kyong Chun (Open Access)
• Critical Race Theory (Third Edition): An Introduction by Richard Delgado, Jean Stefancic, Foreword By Angela Harris

AI in preK-12 Education Resources

• Curriculum: AI plus Ethics for Middle School by Blakely Payne (Open Access Curriculum)
• AI4ALL Open Learning a program designed to equip educators and community members to empower high school students with relevant and approachable AI education.
• Artificial Intelligence (AI) for K-12 (AI4K12) an initiative that is developing (1) national guidelines for AI education for K-12, (2) an online, curated resource Directory to facilitate AI instruction, and (3) a community of practitioners, researchers, resource and tool developers focused on the AI for K-12 audience.

Policy and Advocacy Groups

• Design Justice Network
• Algorithmic Justice League – Unmasking AI harms and biases
• Data 4 Black Lives

Research Centers

• UCLA Center for Critical Internet Inquiry
• The Center for Critical Race and Digital Studies (CR+DS)
• The IDA B. WELLS Just Data Lab
• AI Now Institute at New York University

EducatorCIRCLS on AI

• Three Visionary Projects Using AI in Education Return to Educator CIRCLS by Sarah Hampton (Open Access)
• AI and Formative Assessment by Sarah Hampton (Open Access)
• AI and the Future of Education by The Educator CIRCLS Team (Open Access)
• Introduction to Artificial Intelligence in Education By Sarah Hampton (Open Access)
• Harnessing Educational Data: Discussing Dr. Safiya Noble’s Keynote from Cyberlearning 2019 By Pati Ruiz, Sarah Hampton, Judi Fusco, Amar Abbott, and Angie Kalthoff (Open Access)

Other Guides and Resources

• Teaching: Human-AI Interaction Resources by Iris Howley
• Home – Race, Technology, and Justice – LibGuides at Portland State University by Anders Tobiason
• Educators, Artificial Intelligence, and the Future of Learning Webinar Series By Pati Ruiz and Kip Glazer

Do you have reading recommendations? Let us know @EducatorCIRCLS.