I always said that Artificial Intelligence is basically like a child, and it can become a weapon with two blades – it all depends what data you feed it. Things can get out of hand unless good and skilled people feed it data. AI should always work for humanity and not vice-versa, and the best field in which it can turn out to be helpful is medicine.
Well, it seems that the WHO is now addressing the ways in which AI could be regulated for health. Check out the latest reports about this below.
WHO addresses the use of AI in healthcare
The World Health Organization (WHO) has recently published a guide that highlights the essential regulatory considerations for the use of Artificial Intelligence (AI) in healthcare.
The guide emphasizes the importance of ensuring the safety and effectiveness of AI systems, making them available to those in need promptly, and fostering communication between stakeholders – including developers, regulators, manufacturers, health workers, and patients.
The health sector has the potential to be transformed by AI tools due to the increasing availability of health care data and the rapid progress in analytic techniques, such as machine learning, logic-based or statistical methods.
WHO acknowledges the benefits of AI in improving health outcomes by strengthening clinical trials, enhancing medical diagnosis, treatment, self-care and person-centred care, and supplementing health care professionals’ knowledge, skills and competencies. For instance, in areas where there is a shortage of medical specialists, like interpreting retinal scans and radiology images, AI could be very useful.
However, AI technologies, including large language models, are being rapidly deployed, sometimes without a full understanding of how they may perform. This could either benefit or harm end-users, including health-care professionals and patients.
When using health data, AI systems could have access to sensitive personal information, necessitating a robust legal and regulatory framework for safeguarding privacy, security, and integrity. This publication aims to help establish and maintain such a framework.
“Artificial intelligence holds great promise for health, but also comes with serious challenges, including unethical data collection, cybersecurity threats and amplifying biases or misinformation,” said Dr Tedros Adhanom Ghebreyesus, WHO Director-General. “This new guidance will support countries to regulate AI effectively, to harness its potential, whether in treating cancer or detecting tuberculosis, while minimising the risks.”
Six areas for regulating AI for health
In order to responsibly manage the rapid rise of AI health technologies, there is a growing need to establish regulations. In response to this need, a publication has outlined six key areas for regulating AI in the healthcare industry.
To promote trust, transparency, and documentation are emphasized as crucial factors. This includes documenting the entire product lifecycle and tracking development processes.
For effective risk management, factors such as ‘intended use’, ‘continuous learning’, human interventions, training models and cybersecurity threats must all be comprehensively addressed.
More than that, models should be kept as simple as possible.
Ensuring the safety of Artificial Intelligence (AI) systems is crucial for their regulation.
One way to achieve this is through external validation of data and clearly defining the intended use of AI. Moreover, a commitment to data quality through rigorous evaluation of systems before release is essential to avoid amplifying biases and errors.
Complex regulations such as the General Data Protection Regulation (GDPR) in Europe and the Health Insurance Portability and Accountability Act (HIPAA) in the United States of America pose challenges that can be addressed by understanding the scope of jurisdiction and consent requirements.
This is necessary to protect privacy and ensure data protection.
Collaboration among regulatory bodies, patients, healthcare professionals, industry representatives, and government partners can facilitate compliance with regulations throughout the lifecycle of products and services.
AI systems are intricate and depend not only on the code they are built with but also on the data they are trained on, which comes from clinical settings and user interactions. Better regulation can help manage the risks of AI amplifying biases in training data.
We suggest that you check out the complete WHO data in order to learn all available info on the matter.
