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

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Although the potential of such technology to reduce the global disease burden of breast cancer is significant, there are a number of pitfalls in DeepMind's research that will hinder it from being universally adopted as a true replacement for a radiologist in the developing world. First is that the DeepMind team failed to disclose the technical architecture of their AI system. The second criticism is that DeepMind chose to exclusively use datasets from predominantly Caucasian patients. Although DeepMind made a strong case for the use of supplementary local data, clearly any attempt to create models that generalize globally require supplementary data from a number of diverse ethnic regions. Moreover, any models that are designed to generalize globally and be used in the developing world would require testing and validation in a variety of ethnogeographic regions.