Christus University

A successful first Global Dialogue on AI Governance will be one that turns shared concern into shared responsibility. Artificial intelligence is already part of healthcare decision-making, including clinical laboratories, where results directly affect diagnoses, treatments, and patient outcomes. For this reason, success should not be measured only by broad principles, but by the ability to agree on practical safeguards that protect people. One essential outcome is a common understanding that AI in healthcare must meet the same level of rigor as any diagnostic tool. Systems should be reliable, validated, and continuously monitored, in line with established quality frameworks such as ISO 15189. Behind every dataset and every algorithm, there is a patient whose safety must remain the priority. Another key outcome is the clear affirmation that human oversight is indispensable. AI can support professionals, but it cannot replace responsibility, clinical judgment, or ethical accountability. Decisions that affect people's lives must always remain under human supervision. The Dialogue should also foster trust by encouraging transparency. Healthcare professionals need to understand how systems work, their limitations, and when not to rely on them. Finally, success depends on inclusion. Many countries still lack access to the infrastructure, data, and training needed to benefit from AI. Without deliberate efforts, these gaps will grow. A truly global dialogue must ensure that no country—and no patient—is left behind. Ultimately, success will mean building not only smarter systems, but fairer and more humane ones, guided by cooperation under the leadership of the Organização das Nações Unidas.

• Protection and promotion of human rights
• Safe, secure and trustworthy AI
• Open-source software, open data and open AI models
• Social, economic, ethical, cultural, linguistic and technical implications of AI

My selection reflects the reality that, in healthcare and clinical laboratory settings, artificial intelligence is not only a technological innovation but a matter of patient safety, ethics, and equity. I highlighted safe, secure and trustworthy AI because diagnostic and decision-support systems directly influence clinical outcomes. In this context, reliability, validation, and continuous quality assurance-aligned with standards such as ISO 15189-are essential to prevent harm and ensure confidence among healthcare professionals and patients. The social, economic, ethical, cultural, linguistic and technical implications of AI are equally important, as healthcare systems operate within diverse realities. AI solutions that are not adapted to local contexts may reinforce existing disparities, introduce bias, or fail to address real clinical needs, particularly in low- and middle-income settings. I also emphasized the protection and promotion of human rights, since the use of health data and automated systems raises concerns about privacy, informed consent, and accountability. Patients must remain at the center of all technological advancements, with their dignity, autonomy, and rights fully respected. Finally, I included open-source software, open data and open AI models because equitable access to AI is a critical global challenge. Open and collaborative approaches can support capacity-building, reduce dependency on proprietary systems, and enable countries with limited resources to benefit from innovation. Together, these areas reflect a balanced approach: ensuring that AI in healthcare is not only effective, but also safe, fair, transparent, and accessible, in alignment with global efforts led by the Organização das Nações Unidas.