The possibilities and limits of explicable artificial intelligence (XAI) in education: a socio-technical perspective
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Explicable AI in education (XAIED) has been proposed as a way to improve trust and ethical practice in algorithmic education. Based on a critical review of the literature, this paper argues that XAI should be understood as part of a wider socio-technical turn in AI. The socio-technical perspective indicates that explicability is a relative term. Consequently, XAIED mediation strategies developed and implemented across education stakeholder communities using language that is not just ‘explicable’ from an expert or technical standpoint, but explainable and interpretable to a range of stakeholders including learners. The discussion considers the impact of XAIED on several educational stakeholder types in light of the transparency of algorithms and the approach taken to explaination. Problematising the propositions of XAIED shows that XAI is not a full solution to the issues raised by AI, but a beginning and necessary precondition for meaningful discourse about possible futures.
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Higher education institutions that calibrate their educational strategies according to the potential value of information tend to develop forms of organisational culture in which issues such as algorithmic transparency, user rights, or the prevention of bias become topics of continuous reflection.
“Higher education institutions that calibrate their educational strategies according to the potential value of information tend to develop forms of organisational culture in which issues such as algorithmic transparency, user rights, or the prevention of bias become topics of continuous reflection [29,30].”
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Self-citation
- Authors
- Farrow, R.
- Affiliations
- The Open University (GB)
- Corresponding author
- Farrow, Robert
- ORCID
- Farrow, Robert
- Venue
- Learning, Media and Technology
- Publisher
- Informa UK Limited
- Published
- 2023-03-10
- Volume
- 48
- Issue
- 2
- Pages
- 266-279
- ISSN
- 1743-9884 (ISSN-L)
- 1743-9892
- OpenAlex
- W4323844901
- Cited by
- 81
- References
- 65
- Citations by year
- 2026: 25 · 2025: 31 · 2024: 21 · 2023: 4
- FWCI
- 7.17
- Type
- journal article
- Language
- en
- Update notices
- correction (2024-09-16)
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Learning Media and Technology (publishedVersion, cc-by)
- Open Research Online - ORO (The Open University) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- socio-technical perspective, algorithmic transparency, explainability, interpretability, trust in AI, ethical AI, educational stakeholders, mediation strategies, learner comprehension
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