In anticipation of the passage of the Sensible Classification Act later this fall, the Defense Department has funded the University of Maryland’s Applied Research Laboratory for Intelligence and Security (ARLIS) to conduct a major review of what automating the declassification process would entail and what technologies are most promising.
How might artificial intelligence and machine learning help in the declassification of an ever increasing number of documents and records? Are there promising systems available; what are their strengths and weaknesses? What new funding, staffing, bureaucratic, pilot programs and training might be required to automate the declassification process further?
NPEC held a workshop on November 16th to get the answers. It featured two brief presentations by Brad Gates, who worked at the National Geospatial-Intelligence agency to consolidate their classification guides, and Mike Brundage, associate research engineer at ARLIS.
November 16th, 2023
This and Future NPEC Over Classification Workshops
What Is the Applied Research Laboratory for Intelligence and Security
Why There Is a Need for Modernization of Classified Information
What Cultural Shifts Are Needed Before You Can Use Digital Tools
Can Improving Declassification Automation Produce Those Cultural Changes?
The Challenge of Handling Classified Imagery and What Programs Automatic Declassification Projects Are There and What Can We Learn From Them
How to Know if People Are Following Classification Guides and Who Should Be the Executive Agent for This Project?