The Defense Advanced Research Projects Agency (DARPA) wants autonomous systems to be able to evaluate how well they're doing a specific task and explain that to their human partners.
In a broad agency announcement issued Feb. 19, outlined the Competency-Aware Machine Learning (CAML) program, which aims to transform autonomous systems from tools into trusted partners by virtue of the systems' ability to evaluate their effectiveness and communicate that information to humans.
With CAML, machines will be able to match their behavior to human expectations and allow their operators to quickly understand how they are operating in complex, changing, high-stakes environments.
Today's machine-learning trained systems can adapt their behaviors to circumstances similar to those they've been trained on, but they are unable to communicate how they plan to carry out the task, the adequacy of their training relative to the job or other factors that could affect their probability of success. That means humans must help systems make choices -- a poor use of resources in a combat environment.
CAML plans to create a machine learning framework for object recognition, robotic navigation, action planning and decision-making that will significantly improve teaming capabilities between humans and autonomous systems.