Deep Learning is Human, Through and Through

Bengio and LeCun see no reason why deep learning systems cannot be made to reason. Said Bengio, "Humans also use some kind of neural nets in their brains, and I believe that there are ways to get to human-like reasoning with deep learning architectures." It was 10 years ago, in 2012, that deep learning made its breakthrough, when an innovative algorithm for classifying images based on multi-layered neural networks suddenly turned out to do spectacularly better than all algorithms before it. That breakthrough has led to deep learning's adoption in domains like speech and image recognition, automatic translation and transcription, and robotics. As deep learning was embedded into ever-more everyday applications, more and more examples of what can go wrong also surfaced: artificial intelligence (AI) systems that discriminate, confirm stereotypes, make inscrutable decisions and require a lot of data and sometimes also a huge amount of energy.