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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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TOWARDS NATIONAL STANDARDS: COMPARATIVE ANALYSIS OF AI GOVERNANCE MODELS IN PHILIPPINE HIGHER EDUCATION

Authors: Villanueva, Marjun C.;

TOWARDS NATIONAL STANDARDS: COMPARATIVE ANALYSIS OF AI GOVERNANCE MODELS IN PHILIPPINE HIGHER EDUCATION

Abstract

Currently, there is no existing guideline or policy from the Commission on Higher Education (CHED) as to how Higher Education Institutions (HEIs) in the Philippines should regulate the use of artificial intelligence (AI) in academic settings. This lack of a national guideline prompted universities to come up with their own approaches to regulation, characterized as “soft,” “hybrid,” to “hard” regulatory mechanisms. The researcher puts forward that a productive starting point in formulating a nationally-accepted guideline is to discuss and consolidate these existing efforts. It is in this sense that the researcher comparatively analyzed publicly available guidelines and policies on AI use from eight (8) leading Philippine universities. Using document review and thematic analysis, the researcher shows that there is emerging consensus on the principles of ethical AI use; however, their approaches to regulation differ based on form, guideline, accountability measures, and risk management mechanisms. This paper found that some universities preferred discussing AI ethics by flexibly laying broad ethical principles; some guidelines are “recommendatory but strict in tone”; or employs “faith-based approach,” “competency-centric,” “policy-oriented,” “hard regulation,” among other descriptions to their approaches. These empirical descriptions add to the body of literature concerning AI governance which, as Birkstedt et al. (2021) observed, remains fragmented. It is the hope of the researcher that this can lend insights to how other HEIs would craft their own AI guidelines and ultimately, inform the formulation of a robust national guideline on ethical AI use in education.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green