How Do You Regulate a Self-Improving Algorithm?
At a large technology conference in Toronto this fall, Anna Goldenberg, a star in the field of computer science and genetics, described how artificial intelligence is revolutionizing medicine. Algorithms based on the AI principle of machine learning now can outperform dermatologists at recognizing skin cancers in blemish photos. They can beat cardiologists in detecting arrhythmias in EKGs. In Goldenberg’s own lab, algorithms can be used to identify hitherto obscure subcategories of adult-onset brain cancer, estimate the survival rates of breast-cancer patients, and reduce unnecessary thyroid surgeries.
It was a stunning taste of what’s to come. According to McKinsey Global Institute, large tech companies as much as $30 billion into AI in 2016, with another $9 billion going into AI start-ups. Many people already are familiar with how machine learning—the process by which computers automatically refine an analytical model as new data comes in, teasing
