The Ethics of Automation: Exploring Educator Perceptions on Generative AI in Assessment Design

Aim: As generative artificial intelligence (GenAI) tools such as ChatGPT, Claude, and Gemini gain traction in higher education, their integration into assessment design raises pressing ethical questions.This research aimed to explore how pre-service teacher educators perceive the ethical implications of using GenAI in designing, administering, and evaluating student assessments.Specifically, it investigated issues around academic integrity, human judgment, bias, transparency, and institutional readiness. Methodology:The study adopted a qualitative design using semi-structured interviews with 18 pre-service teacher educators across diverse institutions.Data were analyzed thematically and triangulated with a review of recent global literature (2018-2024) on AI and ethics in education.Respondents were profiled in terms of their familiarity with GenAI, teaching roles, and institutional context.Results: Findings revealed a spectrum of views: while participants acknowledged the convenience and efficiency that GenAI brings to assessment design, many expressed concerns about overreliance, diminished authenticity, and potential threats to academic integrity.Ethical apprehensions included risks of plagiarism, algorithmic bias, lack of transparency, and erosion of human-centered judgment.Notably, participants stressed the importance of maintaining human oversight and advocated for institutional guidelines, professional training, and ethical awareness to guide AI use in teacher education. Conclusion:The study concludes that while GenAI presents transformative possibilities for assessment innovation, its ethical integration remains underdeveloped in many institutions.There is a critical need for teacher education programs to adopt human-centered approaches and develop explicit, values-based frameworks for AI use. Recommendations:The study recommends the institutionalization of ethical policies, provision of ongoing professional development, curricular integration of AI ethics, promotion of student integrity, and expanded research on local AI practices in education.These recommendations aim to ensure responsible, inclusive, and pedagogically sound adoption of GenAI in assessment systems.