The World Health Organization (WHO) has issued a comprehensive publication outlining essential regulatory considerations for Artificial Intelligence (AI) in healthcare. This guidance underscores the significance of ensuring the safety and efficacy of AI systems, expediting their availability to those in need, and fostering collaboration among stakeholders, including developers, regulators, healthcare professionals, manufacturers, and patients.
POTENTIAL TO REVOLUTIONIZE
As the healthcare sector witnesses a surge in the availability of healthcare data and rapid advancements in analytic techniques, including machine learning, logic-based, and statistical methods, AI tools have the potential to revolutionize the field. WHO recognizes the transformative potential of AI in healthcare, offering benefits such as strengthening clinical trials, enhancing medical diagnosis and treatment, enabling self-care, promoting person-cantered care, and supplementing healthcare professionals’ knowledge and competencies. For instance, AI can prove invaluable in healthcare settings where specialized medical expertise is scarce, aiding in tasks like interpreting retinal scans and radiology images, among many others.
However, the rapid deployment of AI technologies, including large language models, has sometimes occurred without a comprehensive understanding of their performance, which could either benefit or harm end-users, including healthcare professionals and patients. AI systems working with healthcare data often have access to sensitive personal information, necessitating robust legal and regulatory frameworks to safeguard privacy, security, and data integrity.
Dr. Tedros Adhanom Ghebreyesus, WHO Director-General, highlighted the dual nature of AI’s potential, stating, “Artificial intelligence holds great promise for health, but also comes with serious challenges, including unethical data collection, cyber security threats, and amplifying biases or misinformation. This new guidance will support countries to regulate AI effectively, to harness its potential, whether in treating cancer or detecting tuberculosis, while minimizing the risks.”
SIX KEY AREAS
In response to the growing need for responsible management of the rapid rise in AI health technologies, the publication outlines six key areas for the regulation of AI in healthcare:
- Transparency and Documentation: Emphasizing the importance of transparency and documentation throughout the product lifecycle and development processes to build trust.
- Risk Management: Addressing issues such as ‘intended use,’ ‘continuous learning,’ human interventions, model training, and cyber security threats comprehensively to simplify AI models as much as possible.
- External Validation: Encouraging external validation of data and clarifying the intended use of AI to ensure safety and facilitate regulation.
- Data Quality Commitment: Rigorously evaluating systems pre-release to maintain data quality, preventing biases and errors.
- Complex Regulations: Addressing complex regulations like the GDPR in Europe and HIPAA in the United States by understanding jurisdiction scope and consent requirements, focusing on privacy and data protection.
- Collaboration: Promoting collaboration among regulatory bodies, patients, healthcare professionals, industry representatives, and government partners to ensure that products and services remain compliant with regulation throughout their lifecycles.
AI systems are intricate and rely not only on their code but also on the data used for training, often originating from clinical settings and user interactions. Better regulation can help mitigate the risks of AI amplifying biases in training data, ensuring that attributes such as gender, race, and ethnicity are accurately represented.
The WHO’s new publication aims to establish fundamental principles that governments and regulatory authorities can follow to develop new guidance or adapt existing guidance on AI at national or regional levels. These guidelines are pivotal in harnessing the potential of AI in healthcare while minimizing risks and ensuring ethical and responsible deployment.
