WHO unveils AI ethics and governance guidance for LMMS

For governments, technology companies, healthcare providers

In a move aimed at addressing the ethical challenges and governance posed by large multi-modal models (LMMs) in artificial intelligence (AI), the World Health Organization (WHO) has unveiled guidance that outlines crucial recommendations for governments, technology companies, and healthcare providers.

LMMs are a fast-growing generative AI technology with growing applications and use in healthcare.

The new WHO guidance outlines more than 40 recommendations for consideration by governments, technology companies, and healthcare providers to ensure the appropriate use of LMMs to promote and protect the health of populations.

Wide scope

LMMs can accept one or more types of data inputs, such as text, videos, and images, and generate diverse outputs that are not limited to the type of data inputted.

LMMs are unique in their mimicry of human communication and ability to carry out tasks they were not explicitly programmed to perform. LMMs have been adopted faster than any consumer application in history, with platforms such as ChatGPT and Bard and Bert entering the public consciousness in 2023.

According to Dr Jeremy Farrar, WHO Chief Scientist: “Generative AI technologies have the potential to improve healthcare but only if those who develop, regulate, and use these technologies identify and fully account for the associated risks,”

“We need transparent information and policies to manage the design, development, and use of LMMs to achieve better health outcomes and overcome persisting health inequities.”

The WHO guidance outlines five broad applications of LMMs for healthcare:

• Diagnosis and clinical care, such as responding to patients’ written queries;
• Patient-guided use, such as for investigating symptoms and treatment;
• Clerical and administrative tasks, such as documenting and summarising patient visits within electronic health records;
• Medical and nursing education, including providing trainees with simulated patient encounters;
• Scientific research and drug development, including to identify new compounds.

Across the globe, LMMs are being increasingly used for specific health-related purposes. Still, there are also documented risks of producing false, inaccurate, biased, or incomplete statements, which could harm people using such information in making health decisions.

Furthermore, LMMs may be trained on data of inferior quality or bias, whether by race, ethnicity, ancestry, sex, gender identity, or age.

The newly issued WHO guidance also details broader risks to health systems, such as the accessibility and affordability of the best performing LMMs.

LMMS can also encourage ‘automation bias’ by healthcare professionals and patients, whereby errors that would otherwise have been identified or difficult choices are improperly delegated to an LMM. LMMs, like other forms of AI, are also vulnerable to cybersecurity risks that could endanger patient information or the trustworthiness of these algorithms and the provision of health care more broadly.

To create safe and effective LMMs, WHO underlines the need to engage various stakeholders, governments, technology companies, healthcare providers, patients, and civil society in all stages of development and deployment of such technologies, including their oversight and regulation.

Dr Alain Labrique, WHO Director for Digital Health and Innovation in the Science Division, said: “Governments from all countries must cooperatively lead efforts to effectively regulate the development and use of AI technologies, such as LMMs.”

Key recommendations for governments

The new WHO guidance includes recommendations for governments, primarily responsible for setting standards for developing and deploying LMMs and their integration and use for public health and medical purposes.

For example, governments should:

• Invest in or provide not-for-profit or public infrastructure, including computing power and public data sets, accessible to developers in the public. These private and not-for-profit sectors require users to adhere to ethical principles and values in exchange for access.

• Use laws, policies, and regulations to ensure that LMMs and applications used in health care and medicine, irrespective of the risk or benefit associated with the AI technology, meet ethical obligations and human rights standards that affect, for example, a person’s dignity, autonomy or privacy.

• Assign an existing or new regulatory agency to assess and approve LMMs and applications intended for use in health care or medicine – as resources permit.

• Introduce mandatory post-release auditing and impact assessments, including for data protection and human rights, by independent third parties when an LMM is deployed on a large scale. The auditing and impact assessments should be published and include outcomes and impacts disaggregated by the type of user, including age, race, or disability.

Key recommendations for developers of LMMs

The guidance also includes the following critical recommendations for developers of LMMs, who should ensure that:

• LMMs are designed not only by scientists and engineers. Potential users and all direct and indirect stakeholders, including medical providers, scientific researchers, health care professionals and patients, should be engaged from the early stages of AI development in structured, inclusive, transparent design and given opportunities to raise ethical issues, voice concerns and provide input for the AI application under consideration.

• LMMs are designed to perform well-defined tasks with the necessary accuracy and reliability to improve the capacity of health systems and advance patient interests. Developers should also be able to predict and understand potential secondary outcomes.

Featured image: LMMs have been adopted faster than any consumer application. Image: NCI