During the last decade, enhanced computing power and the availability of large amounts of data have prompted the practical use of artificial intelligence in health care. Health and medical journals now commonly include reports on machine learning and big data, and descriptions of the risks posed by, and the governance required to manage, this technology.
Machine learning algorithms are used to make diagnoses, identify treatments and analyze public health threats, and these systems can learn and improve continuously in response to new data.
The tension between risks and concerns on one hand versus potential and opportunity on the other has shaped this issue of the Bulletin of the World Health Organization on the new ethical challenges of artificial intelligence in public health. Data-driven discovery and analysis in health care can increase knowledge and efficiency as well as challenge social values related to privacy, data control and the monetization of personal information. In India, for example, the adoption of a system for assigning all citizens a unique identification number, linking it to individual health records and several health-related schemes, raises ethical, legal and social issues, and the need for an appropriate ethical framework and data governance
Goodman KW, Zandi D, Reis A, Vayena E. Balancing risks and benefits of artificial intelligence in the health sector. Bulletin of the World Health Organization 2020;98:230-230A. doi: http://dx.doi.org/10.2471/BLT.20.253823