‘Approved For Release 2000/08/10 : CIA-RDP96-00789R003800440001-2 6 l (U) reasonable—-i.e., only one or two bit assignments were arguable, and their reassignment would not have resulted in a significant p-value, which this session seemed to merit. (U) With analyst error seemingly eliminated, attention was focused on the efficacy of the descriptor list itself. It was concluded that the list was deficient in its ability to capture certain kinds of information, which largely accounted for the perceived accuracy of the response, including: @ «The juxtaposition of elements (ie., spatial relationships) The “novelty factor” of certain elements in the response ® The high specificity of named (or alluded to) target elements. (U) No mechanism exists, as yet, within descriptor list technology for capturing the information contained in the spatial relationships between elements. Clearly, as in the example cited in Figure 4, this type of information can be very significant--i.e., the viewer drew his response from the beacon’s actual perspective on the target. Spatial relationships appear to be particularly significant in advanced RV responses, in which complex,‘composite drawings are much more prevalent than in novice responses. This type of information may eventually be accounted for by employing new technologies such as rule-based expert systems (see Section IV.B.), which lend themselves well to recognition of juxtaposed elements. (U) Another factor that is often thought to be important both in novice and advanced RV responses is-—for want of a better term—-the novelty or strangeness of an element in a response. An example of this in Figure 4 might include the odd shape of the structure’s roof--ies a curved roof is a slight departure from normal expectation. The operative information here is embodied in the idea of “architectural oddity,” a concept that is quite central to the target and is higher in information content than what is expressed by the various combinations of pattern and structure descriptors alone. Another example is the viewer’s statement, “...like a fence present but not a fence...,” which is a somewhat odd and uncertain phrase, but actually describes the catwalk guardrails in the target quite well. An experienced analyst might consider this latter type of information to be qualitatively better, because it represents a viewer’s attempt to objectify his perception without succumbing to the pitfalls of analytical overlay (AOL). Analyst observations about response novelty can be systematically tested by devising an element-by—element analysis that can be applied across a wide qualitative range of responses. If the analyst “lore” is correct, it might be captured either by a “novelty” fuzzy weighting factor applied to descriptor lists or by expert systems capabilities. 23 Approved For Release soot N CLAS OIELER ssocsso001-2°
a « Ema sé { eS pawy obTeerS . sine’ . Like WooKsnc em Ar SoMETHIAG THATHARAWS AS Ir Goes AWA FRO WHEee You STD. feasseennve ‘ @ f . Fear- WATER MATER LAAT . or as? Cocarca Ar EU8a OF WATER. ° ”. ED S e A 08 ee Let . UNCLASSIFIED FIGURE 4 (U) BAYLANDS NATURE INTERPRETIVE CENTER, WITH RV RESPONSE Approved For Release zooobd Ch Ace SHEER 22004400012
Mf BY 2 Approved For Release 2000/08/10 : CIA- RDP96- 00789R003800440001 UNCLASSIFIED © if the descriptor list quantifying it cannot register detail. In the 2 Figure ‘4 example, pertinent . ‘(and possibly unique) pieces of data--like poles being used in the structure’s construction—-are relegated to relatively nonunique bit categories such as “patterns of straight, parallel, or angled lines...” Additional highly specific, concrete descriptors (e.g., poles, pathways, etc.), therefore, are essential for descriptor lists quantifying high-quality RV data. (U) The question of whether a viewer is better able to devise his own descriptor list remains unanswered. Subjectively, it is felt that analyst-derived lists have tended to be more concrete in nature and that the advanced series described here would have benefited from that kind of emphasis. There is also the additional fact that the viewer was not aware of the logical consistency rules governing descriptor formulation and application, and that an analyst’s awareness of these procedural mechanics would have been beneficial to the construction of the list. The viewer's insights into abstract descriptor composition, however, were quite invaluable and hold important implications for novice list construction in particular. . a C. (U) Target Definition: Implications for Target Pool Composition (U) A few preliminary guidelines governing target pool composition have been distilled from two sources: (1)-the opinions of RV monitors about the appropriateness of various kinds of RV targets for novice viewers, and (2) RV analysts’ assessments about the difficulties encountered in using the twenty-bit descriptor list to score the 412 targets currently in the novice target pool. (U) As a general rule, the current subjective consensus is that targets are inappropriate for training purposes if they exhibit any of the following qualities: @ They are contrary to the viewer’s expectations. e They are imbued with negative emotional impact.* e@ They violate the “spirit” of the descriptor list’s intended use. *(U) Laboratory anecdotal evidence suggests that targets having negative emotional impact often result in psi-missing responses. 25 Approved For Release 2000/0dhN GLAS SUP IEDs 500440001-2
Approved For Release 2000/08/4 >1A-RDP96-00789R003800440001-2 ; ; (U) A wide range of target types was used in the FY 1986 novice RV training series and have been subjectively determined on a post hoc basis to be of varying degrees of appropriateness for this task. Table 5 provides specific examples of how the current novice target pool may be problematic, given the following assumptions: (1) novice viewers had anticipated that targets for this series would consist of pictures taken from National. Geographic Magazine featuring large, outdoor, gestalt scenes (e.g. cities, mountains, lakes) of roughly the same dimensionality; and (2) the twenty-bit descriptor list was appropriate for coding targets of this type only and nothing else--e.g., use of the list for technical sites or for targets featuring “unnatural” expressions of the bits was inappropriate. (U) While it has yet to be determined empirically (i.e., by systematically examining figures of merit) whether these target types are aciually problematic, it is currently the subjective opinion of the evaluation team that these kinds of targets would pose the greatest difficulties for novice viewers. i ; Table 5 (U) POTENTIAL PROBLEM AREAS FOR NOVICE TARGETS . Condition Violated Target Type ee Viewer Emotional | Intended expectation| impact  |use of list Close-up photo of a small feature (e.g., a flower, tree trunk, etc.) Seraee™| ations in a still pool, [Moon-off-earth photos | [Sunken ship ruins "| Jondenics | Whale slaughter . Black & white photos Standing dead trees (without foliage) Photos with people and/or animals Ornate interior of the Vatican during a ceremony Significant target element for which there was no v v descriptor Significant target element for which there was no a descriptor Too complex for novices UNCLASSIFIED 26 Approved For: Release 200d NCLAS STEER oss004s0001 2
' Appreved For Release 2000/08/10 : CIA-RDP96-00789R003800440001-2 IV RECOMMENDATIONS (U) (U) The results of the FY 1986 evaluation effort have illuminated several areas of investigation that may hold promise for improving RV evaluation procedures. These areas include (1) identification of new descriptor lists that more accurately reflect target and response information, (2) implementation of enhancement techniques (e.g., fuzzy set theory) for attaining greater accuracy from descriptor lists, (3) systematic examination of inter—analyst reliability factors, and (4) development of new technologies (e.g., expert systems) for capturing analysts’ insights with greater efficiency. Several parallel approaches, ‘which address various aspects of these areas, have been targeted for preliminary research in FY 1987. These include: w © A “similarity” experiment (proposed by S. J. P. Spottiswoode) in which an attempt will be made to identify underlying semantic structures in remote viewing descriptions of target materials. ‘ @ An approach using artificial intelligence (AI) techniques (proposed by J. Vallee) for recognizing, analyzing, and describing target materials. @ In-house approaches directed at - Improvement of existing descriptor lists by incorporating more - abstract descriptors into novice lists and more concrete descriptors intol advanced lists. _ ~ Implementation of fuzzy set mathematical weighting factors into existing descriptor lists in an attempt to decrease their granularity. ~ Assessment of the relative merits of analyst-derived versu percipient—derived descriptor lists. p - Identification of possible percipient-specific “ideogramic dictionaries,” which might serve as prescriptive, guides for the RV analyst. - Development of mission~specific descriptor lists (e.g., for technical sites). Each of these approaches is outlined briefly below. A. (U) Similarity Experiment (U) According to the proposal submitted by consultant S. J. P. Spottiswoode, the proposed similarity experiment is aimed at improving existing evaluation techniques through 27 Approved For Release 2000 dINGLASSIEHERose00440001.2