Vector Analytics, North Carolina, United States
Keywords: technology readiness, commercial readiness, artificial intelligence, machine learning, technology landscapeCurrently DoD’s chief scientists and subject-matter-experts assess the technology readiness levels of warfighter technologies and military systems in a subjective manner. They rely upon their “manual” scan of current literature and patent activity, discussions with the industrial supply chain, attendance at conferences, review of SBIR/STTR solicitations and responses, etc. to build their view of the technology landscape they are responsible for monitoring and developing. Though today many of these tasks are augmented with software-as-a-service access to individual information databases, we propose building an Artificial Intelligence (AI) system that utilizes machine learning and human-computer interactivity to synthesize societal information about technology milestones and technology development patterns and which provides a qualitative intelligence summary and a quantitative assessment of warfighter technology or military system development. Warfighter technologies or military systems can be represented by a collection of textual documents, where examples of such collections could be a set of program descriptions or RDT&E budget item justifications. The proposed AI system will use these collections of textual documents along with other system inputs about societal technology trends to assign a readiness score to a warfighter technology and provide an intelligence summary of the technology landscape under study.