Artificial intelligence (AI) is increasingly used in health research. It can analyse medical records, images, speech, and other health information. It can also support literature reviews, writing, data analysis, diagnosis, and treatment planning. Although AI can improve research and health care, it also creates important ethical questions about privacy, fairness, safety, and human responsibility.
For example, an AI system may be developed to identify depression from a person’s speech. Even if the system appears accurate, researchers must ask whether participants understood how their recordings would be used. They must also consider whether the system works equally well for different languages, cultures, ages, and disabilities. These questions show why AI research requires careful ethical review.
The World Health Organization (WHO, 2026) explains that AI research should be reviewed throughout the study, not only at the beginning. AI systems may change when new data are added, and their results may be difficult to explain. Researchers should continue checking the system for errors, unexpected risks, privacy problems, and differences between research results and real clinical practice.
Basic ethical principles remain important. Researchers should respect people, avoid harm, provide possible benefits, and treat groups fairly. They should clearly explain how health data will be collected, stored, shared, and used. They must also protect participants from discrimination, stigma, incorrect information, and unsafe clinical decisions.
Fairness is a major concern. An AI system may work well for one group but poorly for another. For example, a system trained mainly with data from English-speaking adults may not work well for children, older adults, people with disabilities, or people from other cultural backgrounds. Researchers should use diverse data and report clearly where the system performs well and where it has limitations.
These issues are especially important in low- and middle-income countries. Data may be collected from local communities but used by organisations in other countries. The communities that provide the data may receive few benefits or have little control over its use. Ethical research should include local researchers, community involvement, fair benefit sharing, training, and long-term capacity-building.
Researchers should also describe clearly how AI was used. They should report the tool, its purpose, the data involved, and the methods used to check errors. Poor-quality or incomplete data can lead to unfair or unsafe results. Therefore, researchers should examine not only overall accuracy but also safety, usefulness, transparency, and performance across different groups.
AI may help ethics committees identify privacy risks, missing information, or possible bias. However, it should not replace human judgement. Ethical review requires understanding people’s rights, values, cultures, and experiences. Therapists and other health professionals should ask how an AI tool was developed, whether it was tested with their patients, and who is responsible when it makes a mistake.
AI may support better research, earlier diagnosis, and improved health services, but its benefits are not automatic. Responsible use requires privacy protection, fairness, transparency, high-quality data, and continued human oversight. The important question is not only whether AI works, but whether it works safely and fairly while supporting, not replacing, professional judgement and compassionate care.
References
World Health Organization. (2026). Artificial intelligence-related health research: Ethics review and oversight. World Health Organization.