Opportunities and challenges of AI use in health care

Ethics and human rights must be put at the heart of AI design, deployment and use if it is to achieve its “great promise” and improve the delivery of healthcare and medicine worldwide, according to new WHO guidance.

And governments, providers, and designers must work together to address ethics and human rights concerns says the report, Ethics and governance of artificial intelligence for health – the result of two years of consultations with international experts.

“Like all new technology, artificial intelligence holds enormous potential for improving the health of millions of people around the world, but  it can also be misused and cause harm,” said Dr Tedros Adhanom Ghebreyesus, WHO Director-General.

“This important new report provides a valuable guide for countries on how to maximize the benefits of AI, while minimizing its risks and avoiding its pitfalls,” he added.

The report points out AI is already being used to improve the speed and accuracy of diagnosis and screening for diseases; to assist with clinical care; strengthen health research and drug development, and support diverse public health interventions, such as disease surveillance, outbreak response, and health systems management.

It says AI could also empower patients to take greater control of their own health care and better understand their evolving needs.

It could also enable resource-poor countries and rural communities, where patients often have restricted access to health care workers or medical professionals, to bridge gaps in access to health services.

However, it cautions against overestimating the benefits of AI for health, especially if it’s at the expense of core investments and strategies required to achieve universal health coverage.

It also points out that opportunities are linked to challenges and risks, including unethical collection and use of health data; biases encoded in algorithms, and risks of AI to patient safety, cybersecurity, and the environment.

The report also emphasizes that systems trained primarily on data collected from individuals in high-income countries may not perform well for individuals in low-income and middle-income settings.

AI systems should therefore be carefully designed to reflect the diversity of socio-economic and health-care settings.

They should be accompanied by training in digital skills, community engagement and awareness-raising, especially for millions of healthcare workers who will require digital literacy or retraining if their roles and functions are automated, and who must contend with machines that could challenge the decision-making and autonomy of providers and patients.

The six principles for the basis of AI regulation and governance in health:

1. Protecting human autonomy: In the context of health care, this means that humans should remain in control of health-care systems and medical decisions; privacy and confidentiality should be protected, and patients must give valid informed consent through appropriate legal frameworks for data protection.
2. Promoting human well-being and safety and the public interest. The designers of AI technologies should satisfy regulatory requirements for safety, accuracy and efficacy for well-defined use cases or indications. Measures of quality control in practice and quality improvement in the use of AI must be available.
3. Ensuring transparency, explainability and intelligibility. Transparency requires that sufficient information be published or documented before the design or deployment of an AI technology. Such information must be easily accessible and facilitate meaningful public consultation and debate on how the technology is designed and how it should or should not be used.
4. Fostering responsibility and accountability. Although AI technologies perform specific tasks, it is the responsibility of stakeholders to ensure that they are used under appropriate conditions and by appropriately trained people. Effective mechanisms should be available for questioning and for redress for individuals and groups that are adversely affected by decisions based on algorithms.
5. Ensuring inclusiveness and equity. Inclusiveness requires that AI for health be designed to encourage the widest possible equitable use and access, irrespective of age, sex, gender, income, race, ethnicity, sexual orientation, ability or other characteristics protected under human rights codes.
6. Promoting AI that is responsive and sustainable. Designers, developers and users should continuously and transparently assess AI applications during actual use to determine whether AI responds adequately and appropriately to expectations and requirements. AI systems should also be designed to minimize their environmental consequences and increase energy efficiency. Governments and companies should address anticipated disruptions in the workplace, including training for health-care workers to adapt to the use of AI systems, and potential job losses due to use of automated systems.

WHO says the principles will guide its future support of efforts to ensure the full potential of AI for healthcare and public health will be used for the benefit of all.