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As generative AI technologies proliferate across higher education, many U.S. universities are still developing institutional policies to address their ethical, pedagogical, and accessibility implications. This posIT column critically examines AI policies and resources at 50 four year universities—one from each U.S. state—to assess alignment with the Association of Research Libraries’ (ARL) Guiding Principles for Artificial Intelligence. Through content analysis of LibGuides, AI taskforce membership, campus events, and public-facing policies, the study reveals widespread adoption of AI resources but a significant lack of clarity, consistency, and librarian involvement in policy development. While most institutions meet baseline criteria related to privacy, plagiarism, and algorithmic transparency, fewer address AI’s potential harms to marginalized communities or its impact on accessibility for students with disabilities. Notably, fewer than half of the AI taskforces surveyed included library staff, despite librarians’ expertise in digital literacy and ethical information use. This column urges academic librarians to actively seek leadership roles in institutional AI governance to help shape inclusive, responsible, and human-centered AI policy frameworks.
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This content will become publicly available on April 14, 2026
Chapter 7: Education
AI has entered the public consciousness through generative AI’s impact on work—enhancing efficiency and automating tasks—but it has also driven innovation in education and personalized learning. Still, while AI promises benefits, it also poses risks—from hallucinating false outputs to reinforcing biases and diminishing critical thinking. With the AI education market expected to grow substantially, ethical concerns about the technology’s misuse—AI tools have already falsely accused marginalized students of cheating—are mounting, highlighting the need for responsible creation and deployment. Addressing these challenges requires both technical literacy and critical engagement with AI’s societal impact. Expanding AI expertise must begin in K–12 and higher education in order to ensure that students are prepared to be responsible users and developers. AI education cannot exist in isolation—it must align with broader computer science (CS) education efforts. This chapter examines the global state of AI and CS education, access disparities, and policies shaping AI’s role in learning. This chapter was a collaboration prepared by the Kapor Foundation, CSTA, PIT-UN and the AI Index. The Kapor Foundation works at the intersection of racial equity and technology to build equitable and inclusive computing education pathways, advance tech policies that mitigate harms and promote equitable opportunity, and deploy capital to support responsible, ethical, and equitable tech solutions. The CSTA is a global membership organization that unites, supports, and empowers educators to enhance the quality, accessibility, and inclusivity of computer science education. The Public Interest Technology University Network (PIT-UN) fosters collaboration between universities and colleges to build the PIT field and nurture a new generation of civic-minded technologists.
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- PAR ID:
- 10603946
- Editor(s):
- Maslej, Nestor; Fattorini, Loredana; Perrault, Raymond; Gil, Yolanda; Parli, Vanessa; Kariuki, Njenga; Capstick, Emily; Reuel, Anka; Brynjolfsson, Erik; Etchemendy, John; Ligett, Katrina; Lyons, Terah; Manyika, James; Niebles, Juan Carlos; Shoham, Yoav; Wald, Russell; Walsh, Tobi; Hamrah, Armin; Santarlasci, Lapo; Betts_Lotufo, Juliamore »
- Publisher / Repository:
- The AI Index 2025 Annual Report
- Date Published:
- Edition / Version:
- 8
- Subject(s) / Keyword(s):
- artificial intelligence research report education
- Format(s):
- Medium: X Size: 3MB Other: per
- Size(s):
- 3MB
- Sponsoring Org:
- National Science Foundation
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