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Cited by 422Ethics and Social Impacts of AIArtificial Intelligence in EducationArtificial Intelligence in Healthcare and Education

The DOI matches its Crossref record; 53 of the 56 references it cites were found in a registry or an index.

Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI) and higher education: A systematic review

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Memarian, Bahar, Doleck, Tenzin·2023·Computers and Education: Artificial Intelligence
DOI 10.1016/j.caeai.2023.100152
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Abstract

The use of Artificial Intelligence or AI is rising in higher education. With this rise, the morality of AI programs is being questioned. There is as such a need to understand how notions of Fairness, Accountability, Transparency, and Ethics or FATE are identified in the AI and higher education studies to date. This systematic review paper aims to understand definitions and studies on FATE and AI in higher education literature. The contribution of this work is to provide a summary of FATE development and the synthesis of the challenges and potentials of each of the reviewed studies. A total of 33 review publications from SCOPUS and Web of Science (WoS) were included in this systematic literature review. We examined definitions of FATE noted in the reviewed articles (may have been multiple in each study) and grouped them into descriptive (understandable by laypeople) and technical (containing jargon) definitions. We also examined the main FATE term studied in detail in each reviewed article and grouped them into qualitative and quantitative studies. Findings show more descriptive definitions exist (especially for fairness) and similarly quantitative definitions mostly emerge for Fairness. Findings also show more quantitative studies exist (especially for fairness) and qualitative definitions mostly emerge for ethics. Generally, though, there are more definitions than relevant studies conducted in the literature. This systematic literature review offers a summary of definitions and studies conducted for FATE terms and AI in higher education literature. Future work may benefit from bridging the gap between laypeople and experts by linking descriptive definitions with technical ones as well as qualitative studies with quantitative ones. Moreover, future work can study accountability and transparency further and make the study of FATE terms more longitudinal, open-access, and reproducible.

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Crossref · 10.1016/j.caeai.2023.100152

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  1. Quan, 2023, Vol. 119

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Metadata

Authors
Memarian, B., & Doleck, T.
Affiliations
Simon Fraser University (CA)
Corresponding author
Memarian, Bahar
ORCID
Venue
Computers and Education: Artificial Intelligence
Publisher
Elsevier BV
Published
2023
Volume
5
Pages
100152
ISSN
2666-920X (ISSN-L)
DOI
10.1016/j.caeai.2023.100152
OpenAlex
W4382133845
Semantic Scholar
77018f7f53c3c524c88994ea69d528411595b250
Cited by
416
References
56
Citations by year
2026: 138 · 2025: 173 · 2024: 93 · 2023: 12
FWCI
16.27
Type
journal article
Language
en
Open access
Licence
Locations
  • Computers and Education Artificial Intelligence (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • Canada Research Chairs
  • Simon Fraser University
  • Canada Foundation for Innovation
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
  • Social Sciences › Education › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
fairness, accountability, transparency, ethics, artificial intelligence in higher education, AI ethics

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