The Untapped Social Impact of Artificial Intelligence for Breast Cancer Screening in Developing Countries: A Critical Commentary of DeepMind

In January 2020, Google’s DeepMind team published an article demonstrating that a deep neural network– based artificial intelligence (AI) system could outperform a human radiologist at the task of interpreting mammograms. The most ground-breaking aspect of this study is not the machine learning architecture itself, rather it is the fact that the authors trained their system by using a wholly histologically labelled dataset, rather than data that used the radiologist’s opinion as the ground truth. With DeepMind focusing exclusively on British and American patients, this commentary discusses how they may have missed the social impact use-case for the technology to address the needs of the 5 billion women who do not undergo breast cancer screening in the developing world. The incidence of breast cancer is rapidly growing in the developing world, regions that do not have the financial or human resources to implement a traditional radiologist-led screening program. In these circumstances, the scalability and low cost of AI systems, such as that put forward by DeepMind, could be a viable solution. According to the current position statement of the World Health Organization (WHO):