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.

摘要

本文重点论述了人工智能在高等教育中的负面影响，如数据集和算法中的偏差、抄袭、事实误差、对学生和员工的微观管理、操纵行为、过度监控、过度依赖人工智能、人工智能决策缺乏可解释性或透明度低、技能丧失以及隐私问题。本文从运营管理的角度出发，讨论了人工智能在高等院校招生、员工招聘、教学/学习/评估、行政活动、研究、学生的社会化和福利、员工的薪酬、考核和福利等各个流程中的负面影响。特别关注人工智能对道德、创造力和批判性思维的影响。此外，本文还讨论了避免或减轻人工智能负面影响的潜在解决方案，还讨论了包括理论、管理和政策影响。

KEYWORDS:

• Artificial intelligence
• higher education
• negative impacts
• ethics
• decision-making approaches

关键词:

• 人工智能
• 高等教育
• 负面影响
• 伦理
• 决策方法

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

No data is associated with this research.

Permission to reproduce material from other sources

The paper uses no material from other sources that requires permission to reproduce.

Additional information

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.