7 Key WHO Measures to Ethically Enable AI for Strengthening Global Healthcare System

Although artificial intelligence has tremendous potential to improve the health of millions worldwide, it can also be misused, causing harm,” a report on AI compiled by the World Health Organization (WHO) states. Providing a valuable guide for countries on how to maximize the benefits of AI while minimizing its risks and avoiding its pitfalls, this report is an important addition to the literature on artificial intelligence.

Employing artificial intelligence in medical imaging and other clinical and diagnostic procedures helps with automatic disease diagnosis and screening for diseases more quickly and accurately. AI can improve clinical care, drive health research and drug development, and support public health interventions, particularly disease surveillance and outbreak responses.

How AI can Help Both Patients and Healthcare Facilities

As a result of AI, patients could also better understand their health needs and take more control over their health care. Additionally, it could facilitate access to healthcare for those living in poverty-stricken countries or rural communities, where access to healthcare workers and professionals is often limited.

While AI has many benefits for health, WHO’s new report cautions against overestimating these benefits, even when they are at the expense of the strategic investments and investments necessary for universal health coverage. Recent developments in data labeling and annotation processes, e.g., radiology image annotation, dental image annotation, and others have fast-paced the AI implementation in healthcare. However, data collection, sharing, and use need to be in line with the ethical norms set out by the World Health Organization.

Using AI Without Compromising the Rights and Interests of Individuals

A data collection, storage, or sharing activity can be considered ethical when it is done according to ethical principles. These issues include securing consent, storing data safely, and obtaining permission to use or share data.

Despite the importance of both public and private sector investment in AI, unrestricted use of AI could compromise the rights and interests of individuals, communities, and governments to the powerful commercial interests of technology companies or government interests in surveillance and social control.

Also, the report highlights that algorithms trained primarily on data collected from individuals from high-income countries might not perform well in countries with lower and middle incomes.

Deploying AI in Socioeconomic & Healthcare Settings

It is therefore essential to design AI systems that represent the diverse nature of socioeconomic and healthcare settings. Training in digital skills and community engagement will be vital, especially for millions of healthcare workers whose roles and functions may be automated and whose autonomy may be challenged by machines that can challenge decision-making and behavior.

At every stage of the design development and deployment of an AI technology, governments, providers, and designers must work together to address ethical and human rights concerns based on existing laws, human rights mandates, new regulations, and policies that set down ethical principles.

WHO Guidelines for Ethical Implementation of AI to Improve Global Healthcare

WHO provides the following principles as the basis for AI regulation and governance to minimize the risks and maximize the opportunities inherent in AI for health:

Protecting Smustty of Users’ Data

As it relates to health care, this means that humans should maintain control over healthcare systems and medical decisions, security must be assured; and consent must be validly informed and protected through appropriate legal frameworks.

Promoting the welfare, safety, and interests of the public

AI technology designers should meet safety, accuracy, and efficacy requirements for well-defined uses or indications outlined in regulatory rules. Using Artificial Intelligence in practice must include quality control and quality improvement measures.

Make sure that the information is transparent, understandable, and comprehensible

An AI technology should be transparent by publishing or documenting sufficient information before it is designed or deployed. Public consultation and debate must be facilitated through such information, and the way the technology is designed and how it should or should not be used should be easily accessible.

Taking responsibility and holding people accountable

Even though AI technologies perform specific tasks, stakeholders must ensure that they are used by appropriately trained personnel under appropriate conditions. Individuals and groups who are adversely affected by algorithms should have effective mechanisms to question and redress the situation.

Integrating equity and inclusivity

AI for health must be designed to promote broad participation and access to AI regardless of age, gender, sex, income, race, ethnicity, sexual orientation, ability, or any other under the terms of human rights codes designed for protecting equity and inclusivity for all.

The above 5 key measures define the WHO guidelines for promoting the ethical use of AI in the course of AI use and implementation in developing healthcare applications and automated systems to undertake medical processes. Whether it’s a medical imaging annotation company or an AI-based healthcare product manufacturer, every entity in the pool needs to abide by the WHO framework for AI integration into healthcare processes.

Improving The Efficiency and Sustainability Of AI

Users, designers, developers, and medical imaging annotation companies should constantly and transparently evaluate healthcare AI applications during actual use to ascertain whether artificial intelligence responds adequately and appropriately to expectations and requirements defined for the healthcare processes. Prioritize minimizing the environmental consequences and increasing energy efficiency during the design, development, and deployment of the healthcare AI systems in medical practice.