Safe, Effective Use of AI‑Powered Instruments in Optometry Education (Philippines, 2025): A Policy/Practice Analysis Aligned with Philippine Privacy and Medical Device Software Regulation
- AIOR Admin
- Feb 12
- 2 min read
Sherwin William B. Suarez
Centro Escolar University
Background: Artificial intelligence (AI)-powered instruments are entering optometry teaching clinics faster than local governance frameworks can keep up. In the Philippines, recent issuances such as the National Privacy Commission (NPC) Advisory 2024-04 and the draft Food and Drug Administration (FDA) circular on medical device software (MDSW) create new obligations for educators who deploy AI tools in student-facing clinical settings. However, there is little guidance on how to translate these regulatory signals into concrete procurement terms, classroom controls, and assessment frameworks. Methods: We conducted a targeted policy synthesis (1 January–26 October 2025, Asia/Manila) focused on (1) Philippine primary instruments (NPC Advisory 2024-04, draft FDA-PH MDSW circular, DTI NAISR 2.0, NEDA AI policy note); (2) professional guidance from the Royal College of Ophthalmologists and the College of Optometrists; (3) global AI governance frameworks (WHO guidance on large multimodal models, FUTURE-AI consensus); and (4) peer-reviewed Philippine evidence on diabetic retinopathy (DR) AI and tele-ophthalmology. We used site-restricted searches for government and professional domains, PubMed/Scopus database searches, two-stage screening, and a simple 0–2 quality appraisal rubric. We mapped legal and regulatory requirements (lawful basis, DPIA, post-market monitoring, change control) to operational classroom controls, procurement clauses, and key performance indicators (KPIs) for termly validation. Findings: The synthesis yielded a hierarchy of obligations with Philippine law and regulation at the apex, supplemented by professional and global frameworks. We developed an educator-led governance model comprising: (1) contract language for AI-powered instruments; (2) a KPI set covering safety, performance stability, subgroup fairness, human-in-the-loop overrides, and data governance; and (3) OSCE-style assessment stations for AI literacy and safe use. We illustrate application through a worked change-control case for an updated AI-assisted retinal imaging device. Conclusions: AI-enabled instruments can be safely integrated into optometry education when educators assert explicit control over procurement, validation, and ongoing monitoring. This framework offers a practical, regulator-aligned blueprint for Philippine optometry schools and may be adapted to other health-profession programs facing similar pressures to adopt AI tools.
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