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Suggested Citation:"Appendix C: Workshop Statement of Task." National Academies of Sciences, Engineering, and Medicine. 2017. Challenges in Machine Generation of Analytic Products from Multi-Source Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24900.
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C

Workshop Statement of Task

The objective of this effort is to provide insights from world-class experts and technologists familiar with the extensive range of issues associated with the application of artificial intelligence to the Intelligence Community (IC) analytic tradecraft. Existing and emerging capabilities, technical implications, cultural, regulatory, policy, and legal issues are all of interest. This effort will require arranging and running a two-day workshop involving a wide range of technical disciplines in industry, academia, and government to investigate issues around the application of artificial intelligence techniques to IC analytic tradecraft. This unclassified workshop will address the following research challenges: (1) Machine-based methods for generating analytic products, and (2) Machine-based methods for automating the evaluation of analytic products. The workshop will explore the state-of-the-art and security implications of existing and emerging technologies pertinent to these topics. A workshop proceedings will be delivered after the workshop. The following tasks are anticipated:

Task 1: Form an ad hoc planning committee of experts to be approved by the leadership of the National Academies. The committee will include world-class experts and technologists familiar with the broad range of issues germane to the application of artificial intelligence techniques to IC analytic tradecraft. When developing the agenda for the workshop, the committee will consider the following research questions:

  • What are the technical objectives and metrics needed for success?
  • What are the primary issues?
  • What are the current and “next level” key performance metrics? What is the “level after next” of expected research and development performance?
  • What is the research knowledge base?
  • How can the government best prepare the scientific workforce to enhance discovery in this area?

Task 2: Arrange and execute a workshop of at least two days duration. This includes securing a venue, organizing and managing the workshop, and providing adequate facilitators and note takers to ensure that prepared materials and insights from the workshop are saved.

Task 3: Prepare a workshop proceedings, including presenters’ materials, that records the experts’ key arguments, information, and insights presented during the course of the workshop. The final reviewed draft proceedings will undergo sponsor security review before posting or otherwise publishing in whole or in part.

Suggested Citation:"Appendix C: Workshop Statement of Task." National Academies of Sciences, Engineering, and Medicine. 2017. Challenges in Machine Generation of Analytic Products from Multi-Source Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/24900.
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The Intelligence Community Studies Board of the National Academies of Sciences, Engineering, and Medicine convened a workshop on August 9-10, 2017 to examine challenges in machine generation of analytic products from multi-source data. Workshop speakers and participants discussed research challenges related to machine-based methods for generating analytic products and for automating the evaluation of these products, with special attention to learning from small data, using multi-source data, adversarial learning, and understanding the human-machine relationship. This publication summarizes the presentations and discussions from the workshop.

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