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?
This workshop features 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.