Vol. 2026 No. 1 (2026): 2026 Continuous Issue
Articles

Dr. AI Dependency vs. Doctoral Identity: How Generative AI is Challenging the Development of Independent Scholarly Thinking in Doctoral Students

Valerie Storey
Franklin University

Published 2026-03-16

Versions

Keywords

  • AI policy, doctoral education, doctoral identity, epistemic dependency, generative artificial intelligence (GenAI), independent scholarship

How to Cite

Storey, V. (2026). Dr. AI Dependency vs. Doctoral Identity: How Generative AI is Challenging the Development of Independent Scholarly Thinking in Doctoral Students. International Journal of AI in Pedagogy, Innovation, and Learning Futures, 2026(1). Retrieved from https://journals.calstate.edu/ijaipil/article/view/6971

Abstract

The rise of Generative Artificial Intelligence (GenAI) in higher education has altered the conditions under which doctoral students learn, research, and develop as scholars. Although doctoral student use of GenAI has accelerated rapidly, institutional frameworks for responsible and developmentally appropriate use have not kept pace. This paper examines a central paradox in doctoral education: the same tools that enhance research productivity may also weaken intellectual independence when used without guidance. Using a critical review methodology, the study synthesizes 47 sources on doctoral education, GenAI use, policy, and epistemic development. Three interconnected dimensions of risk emerged from the analysis: critical thinking attrition, knowledge authenticity erosion, and doctoral identity disruption. The paper introduces a conceptual distinction between AI as a productivity instrument and AI as a surrogate for independent scholarship, arguing that this distinction should guide doctoral AI policy. At the same time, the review recognizes that GenAI can support doctoral learning when institutions provide developmental boundaries, competency-based guidance, and active supervision.

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