Human-Centered AI at MIT is a collection of research and courses focused on the design, development, and deployment of artificial intelligence systems that learn from and collaborate with humans in a deep, meaningful way. We call this set of approaches “Human-Centered Artificial Intelligence,” which is defined by two goals: (1) the AI system must continually improve by learning from humans while (2) creating an effective and fulfilling human-robot interaction experience. This paradigm spans problem in human-sensing through computer vision, semi-supervised data annotation, natural language and non-verbal communication, managing bias in machine learning systems, and realistic simulation of human behavior in reinforcement learning and virtual reality contexts.
A central project connecting several branches of our research is the Human-Centered Autonomous Vehicle, which is a real-world shared autonomy research platform. Our motivating principle in this domain is that building effective, enjoyable, and safe autonomous vehicles is a lot harder than has historically been considered. The reason is that, simply put, an autonomous vehicle must interact with human beings. This interaction is not a robotics problem nor a machine learning problem nor a psychology problem nor an economics problem nor a policy problem. It is all of these problems put into one. It challenges our assumptions about the limitations of human beings at their worst and the capabilities of artificial intelligence systems at their best.