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TRV-2026-0189Version 1 · Certified

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TRUVACE RECORD VERSION
record: TRV-2026-0189
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-07-13T21:30:50.380023Z
status: published
lens: p_space
sector: policy
headline: From AI adoption to AI governance: Developing a Buddhist interpretive framework for higher education
dek: Artificial intelligence is increasingly being adopted in higher education to support teaching, learning, administration, quality assurance, and institutional planning. However, much of the current discussion remains focused on adoption, efficiency, and technological capability, with less attention to the interpretive and governance conditions required for responsible institutional use. This article addresses that gap by developing a Buddhist interpretive framework for AI governance in higher education. Drawing o…
gain_title: (none)
problem_title: Current discussion of AI in higher education focuses on adoption and efficiency with insufficient attention to interpretive and governance conditions needed for responsible institutional use
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Current discussion of AI in higher education focuses on adoption and efficiency with insufficient attention to interpretive and governance conditions needed for responsible institutional use
problem_evidence: much of the current discussion remains focused on adoption, efficiency, and technological capability, with less attention to the interpretive and governance conditions required for responsible institutional use
quick_read: As of May 2026, a peer-reviewed study examined AI adoption in higher education, noting its growing use to support teaching, learning, administration, quality assurance, and institutional planning. Based on interviews with 16 key informants, a focus group with 9 additional participants, and document analysis, the authors identified themes including AI as an institutional governance project and as a system-shaping force.

The article matters because it reframes the challenge from technical adoption to governance, proposing a Buddhist Interpretive Governance Framework using Patisambhida dimensions of purpose, principle, communicative, and judgment governance. It remains uncertain how this interpretive framework would perform across diverse institutions, regulatory environments, or at scale, as the source reports a conceptual synthesis rather than measured implementation outcomes.
limitation: Findings are based on a small qualitative sample of 16 interview informants and 9 focus group participants with document analysis, limiting generalizability beyond studied university contexts
tag: Evidence-backed problem
key_points: Study used semi-structured interviews with 16 key informants, focus group with 9 participants, and document analysis of academic and policy literature | Analysis identified four themes including AI as an institutional governance project and AI as a system-shaping force across core university functions | Authors reinterpret Patisambhida as governance architecture: Attha as purpose governance, Dhamma as principle governance, Nirutti as communicative governance, Patibhana as judgment governance | Proposed Buddhist Interpretive Governance Framework aims to explain move from adoption toward human-centered AI governance
rundown: The study triangulated data across interviews, focus group, and document analysis to strengthen interpretive validity and explored how AI is understood, justified, and governed within university contexts.

Rather than treating Buddhist thought as a symbolic ethical add-on, the authors reinterpret Patisambhida into four governance dimensions to structure responsible AI use in universities.
sources:
- peer_reviewed | Journal of Interdisciplinary Research in Artificial Intelligence and Society | https://doi.org/10.20897/jirais/18573 | 2026-05-19
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