Ethic-Legal Challenges to Academic Integrity in the Era of Artificial Intelligence

Authors

DOI:

https://doi.org/10.29105/nomos.v3i5.48

Keywords:

Academic integrity, philosophy of law, ethical responsability, artificial intelligence, academic autorship

Abstract

The increasing use of generative artificial intelligence tools such as ChatGPT in academic environments has sparked complex ethical and legal debates. This article explores the challenges that AI poses to academic integrity from the perspective of the philosophy of law. It examines key concepts such as responsibility, authorship, truth, and merit, drawing on the works of Immanuel Kant and Paul Ricoeur to rethink the foundations of academic ethics in the digital era.

While Kant emphasizes moral autonomy and the imperative to act out of duty, Ricoeur contributes the notion of narrative responsibility—being accountable for one's actions and words as the author of a meaningful life story. In the context of AI-assisted academic production, these frameworks help question whether it is possible to preserve integrity when a significant part of the intellectual process is delegated to non-conscious systems.

The article also addresses issues of epistemic justice, unequal access to technology, and the potential erosion of academic merit when automated content becomes indistinguishable from human-authored work. Finally, it proposes normative principles to guide institutions: transparency, autonomy, proportionality, and ethical accountability.

Far from rejecting AI categorically, this work argues for a responsible and reflective integration of technological tools, placing the human agent at the center of the educational process. Philosophy of law offers an essential lens to ensure that the pursuit of truth and justice remains intact, even in the midst of technological transformation.

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References

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Published

2026-01-28

How to Cite

Rivera de la Rosa, V. (2026). Ethic-Legal Challenges to Academic Integrity in the Era of Artificial Intelligence . Nomos: Procesalismo Estratégico, 3(5), 109–127. https://doi.org/10.29105/nomos.v3i5.48