Charles River Analytics Inc., developer of intelligent systems solutions, created the Causal Models to Explain Learning (CAMEL) approach to help artificial intelligence effectively communicate with human teammates.
Under DARPA’s Explainable Artificial Intelligence (XAI) effort, we led a team that included Brown University, the University of Massachusetts at Amherst, and Roth Cognitive Engineering. The team developed probabilistic causal modeling techniques and an interpretive interface that enable users to naturally interact with machines. CAMEL simplifies explanations of how these complex, deep learning machines work.
Our approach will significantly impact the way that machine learning systems are deployed, operated, and used inside and outside the Department of Defense (DoD).
Learn more about how CAMEL makes it easier for humans and machines to communicate.
To learn more about Charles River or our current projects and capabilities, contact us.
About Charles River Analytics: Since 1983, Charles River Analytics has been delivering intelligent systems that transform our customers' data into mission-relevant tools and solutions to support critical assessment and decision-making. Charles River continues to grow its technology, customer base, and strategic alliances through research and development programs for the DoD, DHS, NASA, and the Intelligence Community. We address a broad spectrum of mission areas and functional domains, including sensor and image processing, situation assessment and decision aiding, human systems integration, cyber security, human-robot interaction, and robot localization and autonomy. These efforts have resulted in a series of successful products that support continued growth in our core R&D contracting business, as well as the commercial sector. Charles River became an employee-owned company in 2012, to set the stage for the next-generation of innovation, service, and growth.