Defense Advanced Research Projects AgencyTagged Content List

Technologies for Trustworthy Computing and Information

Confidence in the integrity of information and systems

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During the past decade information technologies have driven the productivity gains essential to U.S. economic competitiveness, and computing systems now control significant elements of critical national infrastructure. As a result, tremendous resources are devoted to ensuring that programs are correct, especially at scale. Unfortunately, in spite of developers’ best efforts, software errors are at the root of most execution errors and security vulnerabilities.
Dramatic success in machine learning has led to a torrent of Artificial Intelligence (AI) applications. Continued advances promise to produce autonomous systems that will perceive, learn, decide, and act on their own. However, the effectiveness of these systems is limited by the machine’s current inability to explain their decisions and actions to human users (Figure 1). The Department of Defense (DoD) is facing challenges that demand more intelligent, autonomous, and symbiotic systems. Explainable AI—especially explainable machine learning—will be essential if future warfighters are to understand, appropriately trust, and effectively manage an emerging generation of artificially intelligent machine partners.
As computing devices become more pervasive, the software systems that control them have become increasingly more complex and sophisticated. Consequently, despite the tremendous resources devoted to making software more robust and resilient, ensuring that programs are correct—especially at scale—remains a difficult and challenging endeavor. Unfortunately, uncaught errors triggered during program execution can lead to potentially crippling security violations, unexpected runtime failure or unintended behavior, all of which can have profound negative consequences on economic productivity, reliability of mission-critical systems, and correct operation of important and sensitive cyber infrastructure.