Explainable AI: 4 industries where it will be critical

Let's say that I find it curious how Spotify recommended a Justin Bieber song to me, a 40-something non-Belieber. That doesn't necessarily mean that Spotify's engineers must ensure that their algorithms are transparent and comprehensible to me; I might find the recommendation a tad off-target, but the consequences are decidedly minimal. This is a fundamental litmus test for explainable AI – that is, machine learning algorithms and other artificial intelligence systems that produce outcomes that humans can readily understand and track backwards to the origins. Conversely, relatively low-stakes AI systems might be just fine with the black box model, where we don't understand (and can't readily figure out) the results. "If algorithm results are low-impact enough, like the songs recommended by a music service, society probably doesn't need regulators plumbing the depths of how those recommendations are made," says Dave Costenaro, head of artificial intelligence R&D at Jane.ai. I can live with an app's misunderstanding of my musical tastes.