Artificial intelligence can transform medical treatments, but without an understanding of how it works, rapid deployment of digital health programs could harm patients, the WHO warned on Thursday.
“With the increased availability of healthcare data, and rapid advances in analytical techniques – machine learning capabilities of computers, based on logic or statistics – AI can transform the healthcare sector“, indicated the World Health Organization in this document devoted to the use of AI, intended to provide guidance to public authorities.
According to the WHO, AI can improve performance in clinical trials, diagnosis, development of a treatment protocol, and complement medical knowledge and skills.
For example, AI is useful in the absence of specialists, in the field of radiology for the interpretation of medical imaging and retinal images.
However, AI is being deployed rapidly, sometimes without adequate understanding of how these technologies work,”which can either benefit or harm users“, whether patients or professionals, warned the WHO.
Artificial intelligence systems applied to health allow access to personal data, which is why a solid legal framework is necessary to safeguard privacy, underlined the WHO.
“Artificial intelligence holds great promise for health, but also presents serious challenges, including unethical data collection, threats to cybersecurity, and the amplification of bias and misinformation.” said WHO Director-General Tedros Adhanom Ghebreyesus.
“This new guide will help countries to effectively regulate AI, exploit its potential, whether to treat cancer or detect tuberculosis, while minimizing risks.“, he added.
According to the WHO, artificial intelligence systems depend on the training data they use to learn, so better regulation can help manage the risks and dangers of bias present in existing data. amplified by AI.
“For example, it can be difficult for AI models to correctly represent the diversity of populations, leading to biases, inaccuracies and even failures.“, clarified the WHO.
“To help reduce these risks, regulations can be used to ensure that attributes, such as gender, race, and ethnicity of individuals in the training data are reported and that the entire data set is intentionally designed to be representative“, added the WHO.
The WHO recommends in its guide external validation of data, evaluation of systems to avoid errors and biases, consent for the collection of private data, and collaboration between regulators, patients, governments and health professionals .