How States Conceptualize AI and Equity in Education: A Policy Analysis of Emerging K–12 Guidance

• In Event: Data, AI, and Power: Critical Perspectives on Equity and Influence in Education

Abstract

As U.S. states race to define their positions on artificial intelligence (AI), questions about educational equity and the role of public education remain unresolved. This paper presents a qualitative policy analysis of official state-issued guidance documents, examining how states conceptualize AI in relation to public K–12 education and equity. Drawing on Orlikowski and Iacono’s (2001) typology of IT conceptualizations and a multidimensional equity framework (McDermott et al., 2013), the study reveals patterns in how AI is framed (e.g., tool, threat, agent of change) and the extent to which equity is meaningfully addressed. Findings offer insight into the tensions between innovation, governance, and justice, highlighting implications for leadership, policy design, and democratic accountability.

Authors

• Vincent Cho, Boston College

• Sergio David Barragán, Boston College

• Alex J. Bowers, Teachers College, Columbia University