Artificial intelligence and higher education
This systematic review explores the definitions and research surrounding Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI) within higher education literature. The study aims to provide a comprehensive synthesis of FATE’s evolution and the challenges and opportunities identified across the analyzed papers. The review encompasses 25 SCOPUS articles published between 2019 and 2023. FATE definitions were classified as either technical or descriptive, with some studies offering multiple definitions. Findings indicate a predominance of descriptive definitions, particularly for fairness, which are primarily quantitative. Ethics definitions are mostly qualitative, while fairness research tends to be quantitative. Future research could bridge the divide between experts and the public by integrating technical and descriptive definitions and combining qualitative and quantitative approaches.
Authors
- Puja Trivedi (ORCID: https://orcid.org/0000-0003-1874-8992)
- Subhasis Patra
- A. Behera (ORCID: https://orcid.org/0000-0002-6761-9313)
- Chandayya Makeni
Institutions
- National Council Of Educational Research And Training (IN)
- Nagaland University (IN)
- Central University of Rajasthan (IN)
Publication Details
- Journal
- American Journal of STEM Education
- Published
- 2025-05-15
- DOI
- https://doi.org/10.32674/0x43s107
- Citations
- 4
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 11.05