Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
The dark side of artificial intelligence in higher education
122
Zitationen
1
Autoren
2023
Jahr
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.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.553 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.444 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.943 Zit.
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
2019 · 6.792 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.