The dark side of artificial intelligence in higher education

Abstract

The paper focuses on the negative aspects of artificial intelligence in higher education such as biases in the datasets and algorithms, plagiarism, factual incorrectness, micromanagement of students and employees, manipulation of behaviour, überveillance, overreliance on AI, lack of or low explainability and transparency of AI’s decisions, loss of skills, and privacy concerns. The paper adopts an operations management perspective and discusses the negative aspects of AI in the various processes in higher education institutions such as enrolment of students, hiring of employees, teaching/learning/assessment, administrative activities, research, socialisation and well-being of students, remuneration, appraisal and wellbeing of employees. Special attention is paid to AI’s impacts on ethics, creativity and critical thinking. Potential solutions to avoid or mitigate the negative impacts of AI, theoretical, managerial and policy implications are discussed as well.