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CW-Net Uses Explainable Deep Learning to Help Humans Predict Self-Driving Car Mistakes

MIT and Motional developed CW-Net, a breakthrough explainable deep learning system that translates self-driving car decisions into understandable concepts like "approaching stopped vehicle." Road tests showed safety drivers using CW-Net could more accurately predict autonomous vehicle decisions, addressing a critical gap in transparency and safety of autonomous vehicles.