Fair shares: building and benefiting from healthcare AI with mutually beneficial structures and development partnerships

Artificial intelligence (AI) algorithms are used in an increasing range of aspects of our lives. In particular, medical applications of AI are being developed and deployed, including many in image analysis. Deep learning methods, which have recently proved successful in image classification, rely on large volumes of clinical data generated by healthcare institutions. Such data is collected from their served populations. In this opinion article, using digital mammographic screening as an example, we briefly consider the background to AI development and some issues around its deployment. We highlight the importance of high quality clinical data as fundamental to these technologies, and question how the ownership of resultant tools should be defined. Though many of the ethical issues concerning the development and use of medical AI technologies continue to be discussed, the value of the data on which they rely remains a subject that is seldom considered. This potentially controversial issue can and should be addressed in a way which is beneficial to all parties, particularly the population in general and the patients we serve.

Automated summary

The development and deployment of AI algorithms in medical applications, particularly in image analysis, rely on high quality clinical data collected from healthcare institutions. Despite ongoing discussions about ethical issues, the ownership and utilization of this data remains a controversial yet important subject. Addressing the ownership and use of clinical data in AI technologies could lead to benefits for all parties involved, including the general population and patients served by these technologies.