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 artificial intelligence (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 students who experience exclusion, 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. You can also check out this glossary of AI terms written specifically for educators.
Last updated: November 10, 2023
A Good Place to Start
- Unmasking AI By Joy Buolamwini
- Is ethical AI possible? The Gray Area Podcast with Sean Illing and guest Timnit Gebru. Transcript.
- Algorithms of Oppression: How Search Engines Reinforce Racism by Safiya Umoja Noble
- A People’s Guide To AI by by Mimi Onuoha and Diana Nucera, with design and illustration by And Also Too (Open Access)
- Algorithmic Accountability: A Primer by Joan Donovan, Jeanna Matthews, Robyn Caplan, Lauren Hanson (Open Access)
- Artificial Unintelligence How Computers Misunderstand the World and More than a Glitch Confronting Race, Gender, and Ability Bias in Tech by Meredith Broussard
- Coded Bias a Shalini Kantayya film
- Off Task: EdTech Threats to Student Privacy and Equity in the Age of AI by Center for Democracy & Technology (CDT)
Power, Privilege, Ethics, and Justice in Artificial Intelligence (AI)
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Advancing Racial Equity Through Technology Policy by Julia Rhodes Davis, Eliza McCullough, Sarah Treuhaft, and Rachel Gichinga
- Datasheets for Datasets by Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, Kate Crawford (Open Access)
- The Steep Cost of Capture by Meredith Whittaker
- Responsible Language in Artificial Intelligence & Machine Learning by Genevieve Smith, Ishita Rustagi, Alicia Sheares, and Julia Nee with support from Kellie McElhaney
- Algorithmic Bias in Education by Ryan S. Baker and Aaron Hawn
- Exploring the Ethics of AI (Website Resource)
- Algorithmic Fairness in Education by René F. Kizilcec and Hansol Lee (Open Access)
- Auditing Algorithms for Discrimination by Pauline Kim (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)
- The Problems AI has Today Go Back Centuries by Karen Hao (Open Access)
- Atlas of AI – Power, Politics, and the Planetary Costs of Artificial Intelligence by Kate Crawford
- Hard Choices in Artificial Intelligence by Roel Dobbea, Thomas Krendl Gilbert, and Yonatan Mintz (Open Access)
- Algorithmic Injustice: A Relational Ethics Approach by Abeba Birhane (Open Access)
- Ethics and Computing Repository from EngageCSEdu originally developed by the National Center for Women & Information Technology (NCWIT) and now operated by the Association for Computing Machinery, EngageCSEdu publishes high-quality, engaging, classroom-tested Open Educational Resources (OER’s) for computer science education with a focus on materials for introductory courses in computing.
Design and Artificial Intelligence (AI)
- Design Justice: Community-Led Practices to Build the Worlds We Need by Sasha Costanza-Chock (Open Access)
- Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI by Michael A. Madaio, Luke Stark, Jennifer Wortman Vaughan, and Hanna Wallach (Open Access)
(Dis)ability and Artificial Intelligence (AI)
- No, large language models aren’t like disabled people (and it’s problematic to argue that they are) by Emily M. Bender (Open Access)
- Disability, Bias, and AI from AI Now (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 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 - 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)
Artificial Intelligence (AI) Literacy and AI in PreK-12 Education Resources
- Towards social generative AI for education: theory, practices and ethics (Open Access) by Mike Sharples
- CrashCourse: Artificial Intelligence (Video Series: 21 Videos)
- Conceptualizing AI literacy: An exploratory review by Davy Tsz Kit Ng, Jac Ka Lok Leung, Samuel Kai Wah Chu, and Maggie ShenQiao (Open Access)
- Critically Conscious Computing: Methods for Secondary Education by Amy J. Ko, Anne Beitlers, Brett Wortzman, Matt Davidson, Alannah Oleson, Mara Kirdani-Ryan, Stefania Druga (Open Access)
- 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.
History of Artificial Intelligence (AI)
- The History of AI the Stanford Encyclopedia of Philosophy (Open Access)
- The History of Artificial Intelligence by Rockwell Anyoha (Open Access)
Guidelines and Frameworks for Artificial Intelligence (AI)
- Emerging Technology Adoption Framework: For PK-12 Education by Pati Ruiz, Eleanor Richard, Carly Chillmon, Zohal Shah, Adam Kurth, Andy Fekete, Kip Glazer, Megan Pattenhouse, Judi Fusco, Rita Fennelly-Atkinson, Lin Lin Sheryl Arriola, David Lockett, Valerie Crawford-Meyer, Sana Karim, Sarah Hampton, Belinda Beckford
- K-12 Generative Artificial Intelligence (Gen AI) Readiness Checklist by CoSN and Council of the Great City Schools
- The Ethical Framework for AI in Education (Open Access)
- Universal Guidelines for Artificial Intelligence (Website Resource) by The Public Voice
- UNICEF Policy guidance on AI for children. Recommendations for building AI policies and systems that uphold child rights
Policy and Advocacy Groups
- Design Justice Network
- Algorithmic Justice League – Unmasking AI Harms and Biases
- Data 4 Black Lives
- The AI Now Institute
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
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 Artificial Intelligence (AI)
- I’m a Teacher, Will Artificial Intelligence Help Me? by Judi Fusco and Pati Ruiz (Open Access)
- How Can AI Systems Support Teachers: 5 Big Ideas from the Learning Sciences by Pati Ruiz and Judi Fusco (Open Access)
- Reflections on the AI and Learning Environments Webinar: Classroom Orchestration by Sarah Hampton (Open Access)
- 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)
- Humanizing AI Research in Education by Broadening Community Engagement by Aditi Mallavarapu (Open Access)
- Educators, Artificial Intelligence, and the Future of Learning Webinar Series By Pati Ruiz and Kip Glazer
Additional High-quality Reading Lists
Other Resources
- The Artificial Intelligence Incident Database The AI Incident Database is the only collection of AI deployment harms or near harms across all disciplines, geographies, and use cases. The incident database is managed in a participatory manner by persons and organizations contributing code, research, and broader impacts.
- Teaching: Human-AI Interaction Resources by Iris Howley
- Home – Race, Technology, and Justice – LibGuides at Portland State University by Anders Tobiason
Do you have reading recommendations? Let us know @EducatorCIRCLS.
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