Federated learning improves how AI data is managed, thwarts data leakage
Privacy is one of the big holdups to a world of ubiquitous, seamless data-sharing for artificial intelligence-driven learning. In an ideal world, massive quantities of data, such as medical imaging scans, could be shared openly across the globe so that machine learning algorithms can gain experience from a broad range of data sets. The more data shared, the better the outcomes.
That generally doesn't happen now, including in the medical world, where privacy is paramount. For the most part, medical image scans, such as brain MRIs, stay at the institution level for analysis. The result is then shared, but not the original patient scan data.