AI Futures in Higher Education

Abstract

Artificial intelligence has become part of higher education, yet its future role remains unsettled. Its growing presence raises questions about what counts as learning, how assessment can remain meaningful, what teachers and students should be expected to do, and which forms of educational life should be protected. This thesis examines these questions through education fiction: short speculative stories written within or about (future) educational settings. The thesis uses education fiction to study how AI futures are imagined, contested, and made meaningful by researchers and higher education stakeholders.

This research is grounded in a social constructivist understanding of futures as shaped through social interactions, cultural narratives, and shared expectations. Drawing on the theory of Social Construction of Technology (SCOT), it approaches the current moment of AI in education as one with high interpretative flexibility, where multiple and competing meanings of AI coexist. Fiction is positioned as a distinctive site for studying this process because stories give form to possible futures through conflicts, metaphors, omissions, and other narrative choices.

The thesis comprises four interrelated papers. Paper 1 reviews 100 published speculative fictions to map recently published visions of AI futures in education. Paper 2 develops a three-lens analytical framework for analysing education fiction by integrating literary analysis with educational research. Paper 3 uses a web-based story-crafting tool to elicit original education fictions from 69 stakeholders in Swedish higher education, generating empirical data about their hopes, concerns, and values regarding AI futures. Paper 4 deepens this analysis through semi-structured interviews with 17 of these participants, examining how and why their anticipations of AI futures are both generative and constrained. 

Across the studies, the thesis shows that AI futures in education are plural yet patterned. Stakeholder-written fictions clustered into four configurations: Enhancement, Transformation, Displacement, and Resistance. These configurations were structured by three recurring tensions: the human remainder, the assessment paradox, and the efficiency-depth trade-off. The thesis also develops the concept of bounded anticipation to explain why many imagined futures preserved familiar educational structures, roles, and relationships. These limits are interpreted as meaningful expressions of the educational values stakeholders sought to protect, even as they may narrow what becomes thinkable.

The thesis makes three types of contributions. Methodologically, it advances education fiction as a research approach and offers analytical tools for studying fiction as data, method, and narrative knowledge. Theoretically, it shows how education fiction participates in the social construction of AI futures and extends SCOT by highlighting the narrative and value-bounded character of interpretative flexibility. Practically, it provides a vocabulary for more values-explicit conversations about AI in higher education, showing how educators, students, researchers, institutional leaders, and designers may negotiate competing visions of technological change.

Link to DiVA