Artificial intelligence is entering hospitals faster than patient protection laws

At a time when hospitals around the world are racing to employ artificial intelligence in diagnosing diseases, analyzing medical images, and predicting health complications, a question arises that is no less important than the accuracy of these technologies: Who bears responsibility when the algorithm makes an error in diagnosing a patient or making a treatment recommendation?

This question forms the focus of an independent analytical report prepared by Professor Amid Khaled Abdel Hamid, Visiting Professor in the Ethics of Artificial Intelligence in Healthcare at the University of East London. The university published a presentation of its results on October 19, 2026, warning of a widening gap between the speed of adoption of artificial intelligence in health institutions and the development of the necessary guarantees to protect patients.

The report, titled “The Artificial Intelligence Governance Gap in Healthcare,” was based on an analysis of results published by the World Health Organization that included 50 responding countries in the organization’s European region. The data showed that 64 percent of these countries reported using artificial intelligence in medical diagnosis, while the percentage of countries that announced having a national strategy dedicated to health artificial intelligence did not exceed 8 percent.

The results also revealed that only 8 percent reported the existence of standards or guidelines regarding legal liability for artificial intelligence, while 86 percent of participating countries considered legal ambiguity to be an obstacle to adopting these technologies.

The seriousness of this gap is that the performance of AI systems may vary across patients and medical environments. An algorithm that achieves accurate results in a European hospital may not achieve the same level of performance when applied in another hospital that uses different equipment or deals with patients from diverse demographic and genetic backgrounds.

The report proposes six key safeguards that hospitals can adopt to transform ethical principles into practical actions, starting with clearly defining clinical and institutional responsibility, local clinical verification, staff training, and continuous monitoring of performance.

This issue is of particular importance in the Kingdom of Saudi Arabia, which is witnessing an expansion in digital health applications within Vision 2030. The report’s author believes that the Saudi experience provides an opportunity to develop practical models that combine technical progress and clinical oversight.

On the other hand, AI models have difficulty understanding different cultures. Researchers at Cohair Labs tested 28 models using cultural puzzles and found that the models tended to guess rather than admit ignorance, with the models admitting ignorance only in 0.7 percent of the cases.

Regarding mental abilities, some believe that artificial intelligence may be a “crutch” that weakens critical thinking, but the report believes that it can be used as a tool to sharpen minds by using it for self-testing, searching for experts, and developing ideas in a creative manner.