Zainab Hussain, attorney with Foundry Law Group in Seattle writes for Law Practice Today about artificial intelligence and privacy concerns in The ABCs of Machine Learning: Privacy and Other Legal Concerns.

A recent study at Cornell University concretely demonstrates how machine learning could directly attack one’s privacy. The researchers applied basic algorithms (i.e. less complex than those used commercially by the likes of Facebook and Google), to identify people in blurred, pixelated and encrypted images. They were able to “show how to train artificial neural networks to identify faces and recognize objects and handwritten digits” with 71% accuracy. For comparison, human accuracy was 0.19%.

Read more here.