June 19, 2026 On June 18-19, 2026, the Cordillera Regional Health Research and Development Consortium (CRHRDC) hosted its 14th Regional Health Research Conference at Benguet State University in La Trinidad, Benguet. Guided by the theme “Binadang for Health: Bridging communities through research, collaboration, innovation and care” , the conference brought together leading voices to discuss the rapid transformation of health research through digital technologies.
A central highlight of the event was Plenary Session 1: “Artificial Intelligence, Ethics and Data Governance in Health Research: Advancing Innovation while Protecting Communities”. The session was structured as a dynamic, moderated panel discussion , featuring our very own Jose Maria Lorenzo De Vera, Statistician at 101 Health Research , alongside esteemed experts Dr. Eleanor Cuarte, a neonatologist and Research Ethics Committee (REC) member , and Dr. Cecilia Mercado, Chief Information Technology Officer and Data Protection Officer at Saint Louis University.
Moderated by Dr. June C. Corpuz , the panel provided a comprehensive overview of the modern operational opportunities, ethical challenges, and governance structures required for responsible AI deployment in healthcare.
The Dual Pathways of AI in Health Research
During the session, De Vera outlined the two primary branches of AI currently shaping the health research landscape:
- Generative AI: Tools like ChatGPT and Gemini are frequently utilized as assistants for scientific writing and data analysis. While these tools offer significant accessibility and time management benefits , researchers must remain vigilant against “AI hallucinations”.
- Predictive AI: De Vera emphasized a forward-looking approach, advocating for greater adoption of predictive AI methodologies. These models can be trained to read diagnostics like X-rays or monitor patient recovery trajectories in real-time, functioning as a standalone methodology rather than just an assistant.
The Human as the “Gold Standard”
As AI tools become increasingly prevalent, the panel addressed pressing questions regarding academic integrity and acceptable use. De Vera provided practical guidance for researchers navigating this space:
- The 50% Principle: When drafting academic papers, the majority of the work—at least over 50%—must come directly from the human researcher. Dr. Cuarte echoed this sentiment, noting that AI functions optimally when balanced 50/50 with human oversight.
- Accountability and Ownership: De Vera emphasized that AI should be viewed as an “add-on” or an extra tool, not a necessity. He challenged researchers to ensure they can confidently reproduce their work from scratch, stating, “You, as a human, are the gold standard for your research”.
- Vigilant Verification: Even when simply prompting an AI to “rephrase” text, researchers must double-check outputs to prevent unintentional plagiarism and ensure factual accuracy, as AI models are trained on pre-existing internet data.
Data Governance and Protecting Patient Privacy
The integration of AI inherently demands robust data stewardship.
- Anonymization is Non-Negotiable: For individual researchers conducting analysis via AI, De Vera strictly advised anonymizing all data sets before upload. Patient consent must be secured, especially when uploading visual data or sensitive health information that could be collected and stored by external AI servers.
- Institutional Readiness: Dr. Mercado reminded the audience that health records are classified as sensitive personal information under the Data Privacy Act. She stressed that institutions must proactively develop clear AI policies, emphasizing transparency, legitimate purpose, and proportionality in data collection.
The session concluded by reinforcing the spirit of Binadang. As health researchers leverage AI to push the boundaries of innovation, the true value of these tools relies entirely on responsible, ethical implementation and unwavering human oversight.