"We need to work together to apply the right guardrails to the application of technologies like facial recognition that reflect the values of our society," said Fei-Fei Li, co-director of the Stanford Institute for Human-Centered Artificial Intelligence. A decade ago, Fei-Fei Li, a professor of computer science at Stanford University, helped demonstrate the power of a new generation of powerful artificial intelligence (AI) algorithms. She created ImageNet, a vast collection of labeled images that could be fed to machine learning programs. Over time, that process helped machines master certain human skills remarkably well when they have enough data to learn from. Since then, AI programs have taught themselves to do more and more useful tasks, from voice recognition and language translation to operating warehouse robots and guiding self-driving cars.

A decade ago, Fei-Fei Li, a professor of computer science at Stanford University, helped demonstrate the power of a new generation of powerful artificial intelligence algorithms. She created ImageNet, a vast collection of labeled images that could be fed to machine learning programs. Over time, that process helped machines master certain human skills remarkably well when they have enough data to learn from. Since then, AI programs have taught themselves to do more and more useful tasks, from voice recognition and language translation to operating warehouse robots and guiding self-driving cars. But AI algorithms have also demonstrated darker potential, for example as a means of automated facial recognition that can perpetuate race and gender bias.