R&D for Intelligence Processing

USIB-directed R&D data handling program, need for,
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funds, and manpower; they should authorize and encourage interagency communication and coordination; they should make the most of resources and results external to the community; they should require interchange between the community and other government agencies and between the intelligence and scientific communities; they must support federal objectives; and they should provide for measuring their own impact on community requirements and individual agency resources. Without such policy and objectives, the continuing development of more expensive equipment and more complex and intellectually demanding technology will consume more and more of the community's resources, even without unjustified duplication among the uncoordinated agencies.
As technology and R&D in data handling become more expensive, in both talent and funding, the last ounce of usefulness should be realized from every project. To this end IDH/R&D personnel should be better informed about completed and current R&D efforts everywhere.   As a rough estimate, one tenth of one percent of the intelligence funds earmarked for data-handling R&D in FY 66, if spent on improvement in the information usage patterns of IDH/R&D officers, would give each of them throughout the community the equivalent of a full semester of college-level education during the year. The improvement in the resultant R&D effort would conservatively be worth 100 to 1000 times that expenditure. The distribution of the recommended listing of information services and encouragement to use them is at least a slight first step toward such self-improvement.
Technical Considerations
In its effort to identify discrete areas of intelligence data handling so as to relate the R&D to managerial responsibilities, to applications, to intelligence products, and to funding, the task team after a great deal of deliberation chose two approaches. The first of these was to classify data-handling R&D by application, and twenty-two types of application were enumerated. These range from common ones like calculation of movements (say trajectories), cryptanalysis, and document retrieval to some that may not be obvious--the monitoring of systems (say lie detection systems), image interpretation, pattern recognition, predictive calculations (say in estimates), planning (say of penetration operations), problem solving (say in inductive intelligence analysis), etc.   This listing provided a basis for assessing current efforts and deficiencies.


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Posted: May 08, 2007 08:07 AM
Last Updated: Aug 05, 2011 08:58 AM