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When artificial intelligence meets educational leaders’ data-informed decision-making: A cautionary tale
Resource type
Journal Article
Author/contributor
- Wang, Yinying (Author)
Title
When artificial intelligence meets educational leaders’ data-informed decision-making: A cautionary tale
Abstract
Artificial intelligence (AI) refers to a type of algorithms or computerized systems that resemble human mental processes of decision making. Drawing upon multidisciplinary literature that intersects AI, decision making, educational leadership, and policymaking, this position paper aims to examine promising applications and potential perils of AI in educational leaders’ data-informed decision making (DIDM). Endowed with ever-growing computational power and real-time data, highly scalable AI can increase efficiency and accuracy in leaders’ DIDM. However, misusing AI can have perilous effects on education stakeholders. Many lurking biases in current AI could be amplified. Of more concern, the moral values (e.g., fairness, equity, honesty, and doing no harm) we uphold might clash with using AI to make data-informed decisions. Further, missteps on the issues about data security and privacy could have a life-long impact on stakeholders. The article concludes with recommendations for educational leaders to leverage AI potential and minimize its negative consequences.
Publication
Studies in Educational Evaluation
Volume
69
Pages
100872
Date
2021-06-01
Series
From Data-Driven to Data-informed Decision Making:Progress in the Field to Improve Educators and Education
Journal Abbr
Studies in Educational Evaluation
ISSN
0191-491X
Short Title
When artificial intelligence meets educational leaders’ data-informed decision-making
Accessed
26/09/2025, 18:06
Library Catalogue
ScienceDirect
Citation
Wang, Y. (2021). When artificial intelligence meets educational leaders’ data-informed decision-making: A cautionary tale. Studies in Educational Evaluation, 69, 100872. https://doi.org/10.1016/j.stueduc.2020.100872
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