Using Artificial Intelligence (AI) to generate a doctoral evaluation report offers administrative convenience, but submitting it with minimal editorial modifications raises critical issues of professional accountability, academic integrity, and fiduciary responsibility.

Perspective of Professional Accountability

• Non-Delegable Responsibility: Academic evaluation is an epistemic duty entrusted to an expert. The evaluator remains personally responsible for the validity, rigor, and fairness of the evaluation report, which cannot be delegated to an algorithmic model.
• Substantive Disciplinary Judgment: A doctoral thesis requires qualitative evaluation of original research, methodology, and theoretical contributions. While AI can detect structural issues, it lacks domain-specific judgment to assess scholarly depth.
• Duty over Convenience (Deontological Ethics): Immanuel Kant’s deontological framework emphasizes performing one’s duty out of moral obligation rather than personal convenience or administrative expedience.
• Procedural Fairness to the Researcher: The Ph.D. scholar is entitled to a thorough, independent evaluation, as the assessment directly impacts their academic career and professional standing.
• Institutional Trust & Epistemic Authority: Universities depend on academic rigor to preserve their institutional reputation; outsourcing doctoral evaluations damages public trust in higher education.

Perspective of Professional and Academic Integrity

• Academic Honesty and Authorship: Presenting an AI-generated assessment as one’s own expert judgment misrepresents authorship and breaches academic honesty.
• Efficiency vs. Moral Integrity: Administrative time constraints explain the action but do not ethically justify it. Expediency should not displace professional integrity.
• Fiduciary Relationship: Evaluators act as trustees of academic standards. Substituting algorithmic generation for rigorous reading breaches this duty of trust.
• Virtue Ethics Perspective: Aristotle’s concept of practical wisdom (phronesis) and intellectual virtue requires exercising informed discernment rather than relying on automated shortcuts.
• Transparency Deficit: If institutional rules permit AI assistance for literature organization or grammar review, its use should be openly documented and actively verified.

Ethically Appropriate Course of Action

• Permissible Technological Assistance: AI tools can be used for initial proofreading, structural formatting, or cross-referencing literature.
• Independent Human Verification: The evaluator must independently read the thesis, verify methodological accuracy, evaluate original contributions, and draft substantive qualitative remarks.
• Transparent Disclosure: Disclose the use of assistive digital tools in line with university academic policies.
• Personal Accountability: Assume full intellectual and professional responsibility for the final assessment.

Technological tools should support human judgment rather than replace it, ensuring efficiency does not compromise the meritocratic foundations of academic research.