Human faces evolved to be highly distinctive; it's helpful to be able to recognize individual members of one's social group and quickly identify strangers, and that hasn't changed for hundreds of thousands of years. But, in just the past five years, the meaning of the human face has quietly but seismically shifted. That's because researchers at Facebook, Google, and other institutions have nearly perfected techniques for automated facial recognition. This development rested on two major trends that enabled the recent explosion in machine learning: the exponential improvement in computing power and growth of digital imagery, including labeled photos of human faces. In most cases, those images weren't created in order to train facial recognition algorithms, but they were borrowed for that purpose.

Human faces evolved to be highly distinctive; it's helpful to be able to recognize individual members of one's social group and quickly identify strangers, and that hasn't changed for hundreds of thousands of years. Then in just the past five years, the meaning of the human face has quietly but seismically shifted. That's because researchers at Facebook, Google, and other institutions have nearly perfected techniques for automated facial recognition. The result of that research is that your face isn't just a unique part of your body anymore, it's biometric data that can be copied an infinite number of times and stored forever. In this video, we explain how facial recognition technology works, where it came from, and what's at stake.