Research, media and corporate interest in autonomous road vehicles has exploded. Large industrial labs are hiring large teams to engineer solutions to the problem. As machine learners, I conjecture that it will be big data and cutting edge end-to-end reinforcement learning techniques that will have the best chance to achieve autonomy over the next decade and not the vastly hand engineered, rule based approaches of current teams. A crucial component of self driving car systems which is overlooked is model uncertainty. I claim that model uncertainty is as important as model accuracy, and encourage the community to pursue research in this direction. Good decisions require good predictions and well calibrated uncertainty estimates around those predictions.