ARTIFICIAL INTELLIGENCE PROGRAM RECOMMENDATIONS

• Document Type: CREST
• Collection: General CIA Records
• Document Number (FOIA) /ESDN (CREST): CIA-RDP85B01152R000700910072-4
• Release Decision: RIPPUB
• Original Classification: S
• Document Page Count: 8
• Document Creation Date: December 21, 2016
• Document Release Date: June 27, 2008
• Sequence Number: 72
• Publication Date: December 29, 1982
• Content Type: MEMO

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SECRET
29 December 1982
MEMORANDUM FOR: Deputy Director of Central Intelligence
Undersecretary of Defense for Research & Engineering
(as) Chairman,
Intelligence Research & Development Council
SUBJECT . Artificial Intelligence Program Recommendations C
REFERENCE (a) DDCI Memorandum
(b) IR&DC Report
Executive Summary
This memorandum responds to your request for recommendations
concerning the application of artificial intelligence (AI) technology in
the Intelligence Community (IC). Developed more fully below, the
Intelligence Research & Development Council (IR&DC) recommends that:
(1) Guidance be given to all IC Program Managers to include plans for
applying artificial intelligence within their recommended FY-85
programs. A sample of sug ested wording for such guidance is
provided as attachment.A.._
(2) A subcommittee of the IR&DC be established to provide needed
information exchange on AI matters within the Community. The scope
- of-this subcommittee would include technical information exchange,
interfacing- between basic-' AI -resea h and-IC--applications, and
coordinating IC Al activities.
(3) The IC continue to rely on the long-term financing of basic AI
research by the Defense Advanced Research Projects Agency (DARPA)
coordinating its requirements through the IR&DC AI subcommittee.
-(4) The IC, itself, continue to concentrate on applying AI and prepare a
list of applications which would solidify the commitment and alert
researchers and vendors to Community needs. An initial set of
candidate applications is included as attachment-B. 0
(5) Community ADP managers be advised that in all likelihood a more
diverse set of computing hardware and languages will be required to
support AI systems. Plans will need to be developed for maintaining
these tools and integrating them into existing computer environments.
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(6) Several nascent AI applications laboratories in the Community be
expanded, and their timetables advanced, so as to form focal points
for Al in the Community. Two such laboratories are those in the
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Engineering Topographic Laboratories (ETL) and the Office of Research
and Development (ORD).
(7) An unclassified AI computer facility be established for the Community
and networked with the existing AI research centers via the ARPAnet.
This facility would provide a cost-savings link betwee
Intelligence Community and the AI research community.
(8) End-users of AI systems begin to allocate resources for technology
transfer, recognizing their commitment to provide domain-specific
expertise to be built into the systems.
(9) The component agencies work together to plan, for the internal
development of Government personnel in Al.
As we indicated in our report, we are encouraged by recent breakthroughs in
AI and believe that there are many areas in the Community which could
benefit from applied AI technology. The recommendations contained in this
memorandum are aimed at accelerating current Community efforts in AI to
speed up the productive use of this technology throughout the Community.
Key among these recommendations are numbers 8 and 9. The projected
shortage of trained personnel, added to the normal security issues,
necessitates that the IC be able to supply a large proportion of its own AI
specialists. Therefore, training is paramount (Rec. 9). The importance of
Rec. 8, "End-User Planning", results from the lack of exposure of Community
components to the technology and their understandable general reluctance to
exchange current resources for future benefits. Although certain of these
recommendations may need to wait for FY-85, every effort should be made to
fake preparatory steps in FYw83 /84"and-Program Managers should be-asked-to --
address this specifically.
1. DCI Guidance
Given the strong potential' for AI appcatioiis'n th'e Community
the
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IR&DC recommends that guidance be given to all IC Program Managers to
aggressively pursue the technology and to plan for AI in their FY-85
;.,.programs. Each individual Program Manager will, of course, decide where Al
technology -can best support' hs-or' her' program. -It It i's"therefore
recommended that each Program Manager prepare a list of candidate projects
for early attention. -A sample "fist- s''prov ded -in attachment=`B.- Because'- i
of'the burgeoning technology and the Community's relative inexperience in
applying AI to intelligence problems, we recommend that the DCI resist at
this time the temptation to name a single AI focal point or lead office for
the Community. We suggest, instead, that the Community rely on developing
a program of information exchange concerning applied AI. Such a program
can and should be sponsored through the AI subcommittee of the IR&DC. 25X1
2. IR&DC Subcommittee on AI
To coordinate the exchange of information in this field, we recommend
that a new subcommittee be established within the IR&DC to exchange
technical information, track basic research, evaluate Community
requirements from a technical perspective, and review technically the
development of Community AI systems. This subcommittee would serve as the
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major coordinating body for AI activities within the Community as well as
coordinate AI research efforts on the outside. Specifically, as indicated
below, this subcommittee will interface with DARPA (a member of the IR&DC
but not of the IC). As another example, a series of specific
recommendations have been developed by the EXRAND, including several
involving AI technology and these are endorsed by the IR&DC. These are
summarized in attachment-C. As a part of its charter the new IR&DC AI
subcommittee would onitor the progress of AI activities such as those
proposed by EXRAND.
3. Basic AI Research
While artificial intelligence has been under development for more than
25 years, there remain many fundamental problems to be solved. We
recommend that continued encouragement be given to DARPA, NSF, ONR, and
other funding agencies to support basic research in artificial
intelligence. Historically, these agencies have been providing more than
$10 M per year for AI research during this period. We hope that similar
levels of support would be continued in the future. The IR&DC would then
serve a coordinatin ro a in expressing the needs of the Community to these
funding agencies.
IC Applications of AI
There are many areas where AI technology could be applied to
intelligence problems. Several initial efforts are already underway to
investigate the application of expert systems, natural language processing,
image understanding, and logic programming technologies and methods. A
preliminary l'ist`of'potential Community applications appears in attachment-
B. This initial list presumably will be expanded and continually refined
by the IR&DC AI subcommittee. As usual, identifying suitable applications
and expressing Intelligence Community requirements to the research
tc_mmunitywill be a challen ask requiring uiring a deep understanding of both
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5. AI Computing Environment
..n..t1- . rir- ;r 1, 7cn1. C.' t t:I.~7(Ji'~i '_a
Systems involving artificial intelligence generally"have'"9pecia'1
requirements which necesitate a computer environment that is somewhat
differenf'from` the class daI' data- processing centers of the Community'.
Consequently, the development of AI applications in the Community will
necessitate the member agencies' acquiring a diversity of computer
equipment (e.g., machines specifically designed to run the LISP programming
language). The various Program Managers should begin planning now to
allocate resources for these facilities. Admittedly a diversity of
computing equipment (and vendors) will be a hardship on ADP managers.
However, such equipment is essential at least for in-house research and
development efforts. Of course, every effort should be made as systems are
developed to ensure that operational systems will be as compatible as
possible with individual agency ADP masterplans and traditional mainframe
6. Classified In-House AI Laboratories
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Current efforts to establish classified, in-house AI laboratories such
as those in CIA-ORD, and ETL should be encouraged and expanded with
additional funds. The special research-user relationships needed to
develop applied AI support to operations argues for several distributed
facilities as opposed to a centralized approach. Quality Government
laboratory facilities will not only provide the computing resources
necessary to conduct AI research and development but will also provide a
mechanism for training Government personnel and attracting competent
researchers from the universities and private industry. While recognizing,
the special security and privacy needs of each of the agencies,
consideration should nonetheless be given to the electronic networking of
selected Community AI research facilities to further the exchange of
knowledge and information in the field. Recent advances in network
security and compartmented dissemination substantially reduce the risks
associated with such interconnections.
7. Unclassified AI Laboratory
In addition to-in-house facilities for developing classified AI
applications, the Community could also benefit from an unclassified
facility which is connected electronically to other unclassified AI
research centers outside the Community. Such a connection most likely
would be via the existing ARPAnet which already connects most of the AI
research centers in the U.S. The IC unclassified AI facility could be
operated under contract following models established by. DARPA such as the
Information Sciences Institute at the University of Southern California.
This facility could be used to cut down on Government commercial software
development costs by providing Government-furnished computer time to
contractors in an environment similar to the classified ent into
which the operational system must eventually be__placed.
8. End-User Commitment
- The bas-ic- -parad gm of- an- AI--syst-em=y-is to develop a -functionally
capable system in the laboratory and then to load it with specific
knowledge about the intended application. This knowledge is generally
obtained from the customers for whom the system is being built. We
recommmehd that-guidance?be?gvenr,to the various components to.plan for a
substantial consumer commitment to identify experts and to make them
available to provide -the. -required domain-specific-knowledge. -.Further,.
these internal customers for AI technology will also need to plan adequate
resources for operating and maintaining such systems once they are
developed. Active user involvement in technology transfer process
should be ensured from the beginning.
9. AI Training
Perhaps the most important consideration for a long-term commitment to
artificial intelligence will be the establishment of an adequately trained
Government work force. Sufficient understanding of the tools and
techniques of AI will be required of Government personnel to identify
suitable applications, to monitor contracts, to select hardware and
software, and to apply commercially developed products to the Community's
needs. Because of strong-competition for the relatively few skilled AI
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systems people available, the Community will have to establish training
programs to develop its own internal expertise. Options available for
acquiring this expertise include:
9.1 Establishing close relationships with the major AI research centers
through summer institutes, post-doctoral fellowships, hosting
professors on sabbatical, and extended on-site apprenticeships with
the centers. FI
9.2 Encouraging and assisting employees to seek formal courses,-
graduate school training in AI and knowledge engineering.
9.3 Conducting an AI seminar or lecture series for members of t
Community.
9.4 Sponsoring periodic AI symposia similar to the one r cently hosted
by CIA-ORD and CIA-OSWR at CIA Headquarters.
9.5 Developing a series of internal training courses for AI system
9.6, Providing internships at Community AI laboratories for academic or
industrial AI researchers.
Early consideration should be given to recruitment and training in FY-83
and 84 to form a cadre of knowledgeable personnel which to build a
viable program of applications beginning in FY-85.
10. The Scale of Community Efforts
11. The Need for Artificial Intelligence
To reiterate, the Intelligence Community is faced with a continuing
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set of technical problems involving the collection, processing, and
reporting of intelligence. Advances in collection technology promise to
continue to provide more data than we can process with common data
processing technology. Valuable human expertise is lost every year as
knowledgeable analysts retire or otherwise move on from their positions.
Confusion mounts over just what it is that a particular quantitative
technique really models or how to set the parameters to make it work.
Information systems continue to be developed which are inflexible to
changes in requirements and costly to modify. In short, much is being
spent on developing automated systems, but the practical utility of such
systems is not all it could be.
In conclusion, we believe that artificial intelligence is the only
technology today with the promise of yielding the kinds of information
systems needed to process the projected volumes of data and present it in a
way that is meaningful to and efficient of our human analysts. The time is
now to begin to build the kinds of systems which will be required by the
mid- to late-E?bs, systems which employ the techniques of artificial
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CONFIDENTIAL
ATTACHMENT-A
SAMPLE DCI GUIDANCE
As in previous years, I wish to emphasize the importance of developing
innovative technical and operational solutions to the intelligence problems
that face us. Creative planning and application of appropriate technology
should al to achieve the significant progress of which we are
capable.
One can scarcely be unaware of breathtaking advances in computers
which touch every corner of our lives. We must redouble our efforts to
take fullest advantage of this technology. I am particularly persuaded
that the most advanced area of computer science, known (to my dismay) as
"Artificial Intelligence", has much to offer the Community. To this end, I
have reaffirmed and strengthened last year's DCI GOAL 12: "To Enhance
Manpower Talent and Productivity (U)". It has been modified to recognize
explicitly the potential contribution of advanced computer science.
GOAL 12: To Enhance Manpower Talent and Productivity L__1
Intelligence analysis and production remain a manpower intensive
effort and we continue to suffer from a critical shortage of scarce skills.
Methods must be found to ensure intelligence access to the necessary skills
and to leverage through computer technologies our resident talents. The
shortage of linguists and regional analysts will be particularly critical,
but engineers and technical specialists will also be in short supply.:Ways
must be found both to increase the skilled manpo ilable and to
improve the productivity of available personnel.
- " 'The capability of the Intelligence Community to recruit,,r-etain,.-and _.,, . .
ensure the productivity of necessary manpower remains limited. Colleges
and universities continue to produce insufficient graduates with the skills
required by the Community, nor is the shortage likely to be remedied
~_'through` the' decade.` ' Aind;? while publ-ic~ perceptions are slowly ;changing,, .-the,
problem is still compounded by: an impression among undergraduates that
past personnel cuts and hiring freezes reflect the long-term trend; a
residual negative public attitude toward intelligence; and, competition
from the private sector for the same skills. Consequently, it remains
difficult to find qualified personnel, even when manpower positions are
available.
You should endeavor to initiate programs that will improve the
Community's ability to recruit and retain the manpower necessary. Further,
you should endeavor to initiate programs, based upon the most promising
computer science advances, to multiply the productivity of available
manpower.
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