AI can’t solve the human factor

Two months ago, I visited the SPIE Medical Conference in San Diego. I like to go to such conferences periodically since they offer you a snapshot of what’s new and/or becoming popular and successful. And because about half of the attendees are healthcare professionals, it’s also an opportunity for us engineers to communicate directly with the experts who end up using our gear. There was a lot to discuss, and my group contributed no less than 7 papers and posters.

One particularly interesting talk was about federated learning. A relatively new kid on the block in the broad spectrum of deep-learning approaches, it involves breaking down large data sets into smaller pieces and spreading these out over multiple organizations – in my world, those would be medical and research centers. At first glance, this seems like a great idea because dividing the effort among multiple participants will reduce the computational and storage burden for each partner.