3.2 Ethical risks of AI in higher education
Explore why the most significant ethical risks of AI in higher education often arise from routine institutional uses that scale quickly across admissions, student support, learning platforms, and core administrative processes. This unit examines ethical risk as a governance responsibility, highlighting how leaders can safeguard fairness, inclusion, transparency, and accountability when AI systems influence decisions about students and staff, and why institutional oversight cannot be delegated entirely to vendors.
👉 Start with the video for a quick overview.
👉 Now, read the document to explore the topic in more depth.
Download PDF👉 Finish with the task to reflect and apply what you’ve learned.
Select one current or planned AI enabled use at your institution, for example a chatbot for student services, automated triage of student support requests, AI supported assessment design, predictive analytics for retention, or an external generative AI tool used by staff. Describe the intended benefit and who is expected to gain from it. Then analyse the ethical risk by focusing on three questions. First, what could go wrong for a student or staff member if the system is inaccurate, biased, or poorly explained. Second, what data are involved and whether individuals have a realistic ability to understand, contest, or opt out. Third, who is accountable for monitoring outcomes and acting when harms appear. Conclude with one concrete leadership measure that would reduce risk without stopping innovation, such as a requirement for transparency to users, a monitoring metric, a procurement condition, or a decision pathway for escalation. Write 200 to 300 words.
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