Title : Deregulation of artificial intelligence in healthcare and global governance: Ethical, regulatory and human rights challenges
Abstract:
Digital health is rapidly evolving, driven by advances in artificial intelligence (AI) and big data. While these technologies offer significant potential to improve healthcare delivery, their expansion has outpaced the development of adequate regulatory frameworks. This gap has created serious risks to equity, human rights, and ethical standards, particularly in low-resource settings. The dominance of commercial interests and the lack of global coordination further exacerbate existing health disparities. This presentation explores the risks associated with the deregulation of AI in healthcare and underscores the urgent need for a global governance framework grounded in human rights and equity. Through a qualitative and documentary analysis, the study draws on scientific literature, reports from institutions such as the World Health Organization (WHO), and emblematic case studies involving violations of rights and ethical breaches. A critical global health perspective is adopted to examine structural inequalities and the impacts of weak or fragmented regulation. Key findings reveal how unregulated AI applications in healthcare can perpetuate discrimination, such as algorithmic bias that favors white patients, or the misuse of sensitive data by digital health platforms. High-profile cases, including IBM Watson's flawed clinical recommendations and BetterHelp’s questionable data practices, highlight threats to privacy and patient safety. Moreover, the current regulatory fragmentation enables corporate interests to prevail over public health objectives, deepening global inequalities. The analysis also reviews international efforts toward ethical AI governance, including the European Union’s AI Act, the WHO’s guidance on ethics and AI in health, and the UN's "Pact for the Future." While these initiatives offer promising pathways toward human-centered regulation, they face significant opposition from powerful economic stakeholders. In conclusion, the presentation argues for the establishment of a robust global governance model for AI in healthcare—one that ensures transparency, accountability, and social justice. Effective regulation should include mandatory ethical impact assessments, algorithmic audits, and accessible mechanisms for redress. Emerging frameworks such as the AI Act, the Global Digital Compact, and proposals for taxing Big Tech represent viable strategies to safeguard fundamental rights and strengthen public health systems worldwide.
