Two researchers from Stanford University recently claimed to have constructed a machine learning algorithm that predicted sexual orientation from facial pictures. The researchers recognized the dangers in this themselves, observing that “in some cases, losing the privacy of one’s sexual orientation can be life-threatening.” The original study, a good example of the risks involved in data science research, is now under ethical review.
We live in an age where data is described as the new oil. Large amounts of information are collected and stored, and increasingly complicated techniques like machine learning are used to derive insights from it. But with such great insight comes great risk, not to mention tremendous power to influence people’s lives. Toon Borré, who heads the data department of consultancy firm TriFinance, remembers refusing a request to determine when it would be financially cheaper for a hospital to let someone die on the operating table. “We hear all the time about how data is the new oil,” says data scientist Charles Givre, “but I would argue that if mishandled, data can also be the new TNT.”