Approved For Release lial °°°°728ree"soozeecor- CONTENTS LIST OF ILLUSTRATIONS . 2. 6 2 ee ee se ee eee ee ee iii I OBJECTIVE. .- +262. s- e+e eee 8 # 8 ee He HH TT 1 II INTRODUCTION, AND BACKGROUND. . 2. 2+ © © © es © 5 © © © Oo 8 2 A. Location of Unknown SMA Tar cets . cee ee es 2 B. Remote Viewing (RV) as a Location Technology. .« . « «+ 2 Cc. Conclusion. ...-e +s eee 2 eee 8 fe eee cS) II] METHOD OF APPROACH... - + eee ss eters ses 6 A. Step 1--Microcomputer-Based Screening Training. . . - 6 l. Sequential Sampling Statistical Averaging Procedure... + ee eee see eee eee 8 2. System Error... - + eee te ese ree 12 3, Test Data... 2. +e ee eee etree 13 B. Step 2--Simulation Testing. - +--+ + te horrors 15 Cc. Step 3--Demonstration-of-Feasibility Field Study... 15 IV PROPOSED PROGRAM . 4 6 ee ee th te ee et et et 17 REFERENCES. «2. 6 6 es ee ee re te ee ee TH HT 18 19 APPENDIX. 2 6 0 ee ee ee ee ee te eH HH Approved For Release 20 | P)6-00788r001 300200001-6 ¢
Approved For Release 70°C ediieaina 0072220" 00200001 ILLUSTRATIONS 1 Computer Modeling Task... . 2 Decision Graph for Site Selection, e ° eo oe . . e oy oe e 3 Average Number of Trials ny to Screen Positive ..... 4 Decision Graphs for Site Selections Based on the Data of Subject 1 (Table 1) Screening Study, Resulting in Twelve Consecutive Correct Selections Approved For Release 2000 ° e . e . ° ° e e e Dp 96-00788r001300200001-6 id 10 11 14
tt Approved For Release 2000/ 8/07 : CIA-R P96-00788r001300200001-6 I OBJECTIVE The purpose of this document is. to provide an outline of a program to assess the feasibility of using RV detection techniques to determine the Oe oe *x location Of MEE 27° of interest. een ee Throughout this document the abbreviation RV refers to the term “remote viewing," not to its other use as "re-entry vehicle.” 1 Approved For Release 200 aia RPP96-00788r001300200001-6
a ee] F 96-00788r001300200094 -6 ry Approved For Release 2006 II INTRODUCTION AND BACKGROUND Location of Unknown | - Targets B. Remote Viewing (RV) as a Location Technology Of particular interest along the psychoenerpetic lines is a human information-accessing capability that we call "remote viewing” (RV). The RV phenomenon, under study at SRI International for the past nine years, pertains to the ability of certain individuals to access and describe, by means of mental processes, information blocked from ordinary perception by distance or shielding, and generally believed to be secure against such access, This has included the ability of subjects to view remote geographical locations given only geographical coordinates or a designated person on whom Ys p to target. The RV abilities of several subjects have been developed to the point where they can describe--often in great detail--geographical and technical material such as natural formations, roads, buildings, interior laboratory apparatus, and real-time activities, In problems of the location type (which have not been addressed in any detail in former programs) the general prospect of a continuum of 2 Approved For Release tP96-00788r001300200001-6
| ‘4 ‘at ll i. 00788r004 300200001-6 Approved For Release 2000/0 possible locations can often be reduced to that of a set of discrete possi- bilities. This is because, for example, only a finite number of ay sites a .. available, or because specifying one of a number of erid squares is sufficient to define location. If a location task can be so defined (to be one of a discrete sect of possibilities), then a detection method can be designed around One of the standard formats for RV testing, a statistical form of shell game which is a direct analog of the discrete location problem, One of the standard formats for RV testing is a computerized form of "shell" game which is a direct analog of the MER, tarcct location situa- tion. The testing procedure addresses the basic problem of choosing, by RV techniques, a “correct" answer from among a number of possible alterna- tives. An example is provided by an electronically-automated screening study carried out by SRI consultant Charles Tart. Subjects were asked to determine which one of ten possible positions on a circular display had been designated as an active target by the electronic test device's random number generator ,° From an unselected population of 2000 university students participating in a mass card screening program, seventy of the better subjects accepted an invitation to be further screened using the automated electronic testing system, Of these, ten were finally chosen to participate in a formal study involving 500 trials each, The results obtained with these ten subjects are shown in Table 1. It is seen that five of the ten subjects scored significantly above chance, all in the range of 1.5-2.5 times chance expectation, The best subject averaged a 24,.8° hit rate (~2.5 x chance) over the 900-trial sequence; the probability -? of such a result or better occurring by chance is only p = 2 x 10 28 Furthermore, as good as these results are, the potential utility of such results can be further enhanced by the use of error-correcting statistical averaging techniques, Such techniques have proven themselves Approved For Release 20 (UIE 0 06-00728r001200200001-6
Approved For Release 27° (mmamag Pr28-00788"001300200001-8 Table 1 ELECTRONICALLY~AUTOMATED SCREENING STUD‘ Probability of Obtaining Such a Result by Chance (one-tailed) Hit Rate (10% Expected) Subject 2 y 10778 1 y 10714 2 x 1078 4 x 107° 5 2 ¥ 107 nonsignificant nonsignificant nonsignificant nonsignificant nonsignificant capable of amplifying even small statistical advantages to arbitrarily- high-accuracy results. To cite an example, Czech researcher Dr. Milan Ryzl, a chemist with the Institute of Biology of the Czechoslovakian Academy of Science, carried out an experiment with a subject. whose base performance level was that he was tencrally capable of encrating better than . 60% hit rate targeting on sequences of random binary digits, or bits (0, 1), where chance expectation was 50%. For the purpose of showing the power of psi enhancement by statistical averaging techniques, Ryzl chose as a task the acquisition, without error, of a 50-dipit random binary sequence. The effort took 19,350 calls, averaging 9 sec per call, The hit rate for individual calls was 61.9%, 11,978 hits and 7372 misses.” By means of repeated passes through the Approved For Release 2000 2DP46-00788r001300200001-6
"Approved 6LK-RDPSE | PP For Release 200) saClA-RDP96-00788r001300200001-6 , * sequence and an elaborate (though inefficient ) ma jority-vote protocol, entify with 100% accuracy all 50 bits. The y that he did so by chance is only one in 102°, the subject was able to id probabilit Cc. Conclusion Thus, data already extant from RV detection experiments indicate that (a) one target from among a number can, with some statistical advantage, be determined by RV detection techniques, and (b) the accuracy of doing so g techniques. These observations can be amplified by statistical averagin thus provide a sound basis upon which to estimate the feasibility of RV detection of randomly distributed BE tercets. and the protocols in use are essentially directly applicable in their present form, ee of about 20 could be expected on rocedure more optimum than that ok an increase in efficiency by a factor the basis of a statistical averaging Pp used in the experiment.” Appro — , | pproved For Release 20, 7s 00788r001300200001-6
Approved For Release 2000 6-00788r001300200001-6 III METHOD OF APPROACH with regard to determining the vulnerability of GEE tarccts to RV detection, an approach that recommends itself is a gradient-scale three- step program involving (1) microcomputer-based screening/training, (2) simulation testing, and (3) demonstration-of-feasibility field study. Each of these are discussed below, A. Step 1--Microcomputer-Based Screening /Training —— ert ee cree ning “raining The first step of the program would involve screening /training a population of volunteers using microcomputer-based modeling of the location problem. Basically, the individuals participating as remote viewers are asked, in repetitive trials, to determine which one of twenty possible locations (schematically represented as circles on a computer- driven graphics display) has been designated as the simlated target by the computer's random number generator, The computer display is driven by an LSI-11 microcomputer which, on a trial-by-trial basis, generates a new random display of the circles (to circumvent bias on the part of the remote viewer due to previous choices), The individual enters his selections by button press on a hand device positioned over an X-Y grid (sec Figure 1, where a one-in-ten case is shown), and the computer responds by giving immediate feedback as to the correct answer (to encourage learning), As the trials progress, the selections are computer analyzed on line by a statistical averaging program, the output of which indicates whether one of the possibilities has been chosen statistically significantly more often than expected by ciance, (In the later application phase essentially the same procedure is followed, with the circles internally 6 5 - ° a Approved For Release 2 oN 0° d-007s8r001300200001-6
© = Oo Oo Oo Oo N Oo So o — Oo vad co co m Oo 2 oO (o>) ou Q Approved For Release 2000 FIGURE 4 COMPUTER MODELING TASK. Monitor, a decision graph The circles representing possible tar is shown on the upper monitor. on hand device positioned Over x-y grid. get locations are shown in the lower video The remote viewer's choice is entered by button press rn m7 © & ® a Som 3) ng e) ® > © S. oY a6 IA-RDP96-00788r001300200001-6
Approved For Release 2000/08/07 : CIA-RDP96-00788r001300200001-6 keyed to actual target site possibilities. The procedure differs only in that trial-by-trial feedback would, of course, not be available), 1. Sequential Sampling Statistical Averaging Procedure An efficient statistical method for the screening /training process is provided by a sequential-sampling technique used in production- line quality control.® The sequential method gives a rule of procedure for making one of three decisions (with regard to each of the possible choices) following each trial, which consists of a remote viewer entering a selection: the accumulated selections have met a pre-established hit- rate criterion (decision positive); the accumulated selection do not exceed chance expectation (decision negative): continue trials (insufficient data to make a decision). The sequential sampling procedure differs from tixed-trial-length procedures in that the number of trials required to reach a decision is not fixed, but depends on the results accumulated with each trial. The principal advantage of the sequential sampling procedure as comprred with other methods is that, on the average, fewer trials per decision are required for an equivalent degree of reliability. To apply the sequential analysis procedure to screening training, we must a priori define the hit rate we require to conclude that useful RV detection is taking place, and what statistical risks we are willing to accept for making an incorrect decision, To meet these criteria, sequential analysis requires the speci- fication of four parameters to determine from which of two distributions (chance or required-hit-rate) a data stream belongs. They are: p., the fraction of selections of a particular target expected in the chance condition (e.zf., Py = 1/20 for the case under discussion); Pie the fraction of selections expected in the presence of a functioning RV capability (e.g *e Py = 0.125 for a 2,5 x chance-expectation requirement, a value that might Approved For Release 20p0/08/0F eGi-RPP96-00788r001300200001-6 a ;
a i ee es es Ss a Approved For Release 2000/0 A-RDP96-00788r001300200001-6 be chosen because of previous performance in a successful one-in-twenty task); @, an a priori assigned acceptable error rate (c.g., @ = 0.05) for concluding that accumulated selections of a particular choice derive from the Py (RV) distribution when in fact they derive from the Py (chance) distribution (Type I error); 8, an a@ priori assigned acceptable error rate (e.g., 8 = 0.05) for concluding that accumulated selections of a particular choice derive from the Po (chance) distribution when in fact they derive from the Py (RV) distribution (Type II error), With the parameters thus specified, the sequential sampling procedure provides for construction of a decision graph of the type shown in Figure 2. The decision graph illustrates the rules of procedure for making one of the three possible decisions following each trial: continuc test before making a decision (unshaded middle region in Figure 2); decision positive (upper shaded region in Figure 2); decision negative (lower shaded area in Figure 2). The equations for the upper and lower decision lines are given in the Appendix, With the appropriate equations programmed into the microcomputer, the computer automatically records all data (trial number, target response pair), and displays on the video graphics system progress on a target decision graph. A cumulative record of remote viewer selections is compiled by the computer until either the upper or lower decision line is reached, at which point a decision is made, Also given in the Appendix are the equations for the average number of trials to make decisions, positive or negative. A plot of the average number of trials to reach a positive decision for typical cases of interest is shown in Figure 3, where 5% (a, 2) error rates have been assumed, As an example, we sce that for a 2.5 x expectation rate (k = 2,5) hitter, ny * 62 trials are required on the average to reach a positive decision on a one-in-twenty target. 96-00788r001300200001-6 ¢ Approved For Release 20 |
a | Approved For Release 2000/08/07 : CIA-RDP96-00788r001300200001-6 2. System Error The overall system error is dependent on the type of mode employed in site penetration attempts. (a) If the RV detection task is approached with a tentative choice having already been made (presumably by more conventional means), then the task of the remote viewer is to verify or reject the tentative decision as a backup test, In this mode, only a single decision graph is plotted in the target choice of interest, The probability of error due to chance (Pe ig) in this case ~a@, being given by the product of the probability of making a selection even though operating at chance, and the percentage of such selections that correspond to an incorrect decision: N- 1 P = a . e,c ( N (b) If the RV detection task is approached as a blind one-in-N task (¢e.g., One-in-20 task), the N decision graphs are plotted in parallel, one for each of the N target choices, as each selection is being made, In this case, to a good approximation the graphs can be treated in the chance condition as independent, and the probability of error due to chance (Pee? ~ NY, Specifically, it is given by the product of the probability of making at least one selection in the N graphs by chance (which is one minus the probability of making no selections), and the percentage of such selections that correspond to an incorrect decision: N- 1 N pe (4) b- a - | . For example, with N = 20, a 1% individual-target error rate (a = 0,01) leads to P = 0.17, or a confidence factor 1 - P = 0.83; re ec, this provides ~ a 17-fold increase in odds over the one-in-twenty confi- dence factor expected hy chance. Approved For Release 20 P96-00788r001300200001-6 r
nse erre essere . Approved For Release 2000/08/07 : CIA-RDP96-00788r001300200001-6 _ —_ 3. Test Data ™ As a test of the above procedure applied to real data, the data generated by Subject #1, Table 1, were processed by passing it through - the sequential analysis statistical averaging program (500 trials, 24,8% =~ hit rate on a one-in-ten task), With the parameters set to correspond to a twice-chance-expectation requirement and 5% (@, 8) error rates, the an results are as shown graphically in Figure 4: twelve correct selections, ina row, of one-in-ten targets were made in 452 trials, Although the _ data was gathered under the condition that the correct answers were stored in the computer during the runs, and therefore trial-by-trial feedback ma could be given as the random number generator stepped through its program, the conditions are nonetheless sufficiently similar to the projected task | that the results can he taken as evidence that the proposed approach is sound, = 4, Summary | In the screening.'training program, participants would be screened ei trained by carrying out the task described in this section, first with trial-by-trial feedback to encourage learning, and then without feedback wi to model properly an application study. In this initial phase the target for each run would be designated internally by the computer's random number = generator, Carried out on a large-enough scale, the screening training “ program described in this section would provide realistic estimates of the percentage of population trainable in this task, and the levels of - proficiency to which performance in this task could be developed. Ina . program designed to assess to its fullest the feasibility of locating a a WA 2" by RV detection techniques, it is recommended that suffi- ciently large-scale screening to meet these requirements be considered. “Approved For Release 200 P96-00788r001300200001-6
TT TT Approved For Release 2000/ 6-00788r001300200001-6 B. Step 2--Simulation Testing Sep eesoimulation testing The participants who emerge from Step 1 with successful performance profiles would then be asked to participate in Step 2. For this step, a model of an actual eee with a random one-in-twenty designated target would be constructed, The subject's access to the mockup during experimental runs would be by way of video monitor, although secondary means such as maps or photographs might be utilized in later stages of the study if appropriate. To carry out the test, a participant (or participants) would be briefed as to the task and then be asked to proceed as in Step 1. The sequential sampling parameters in the microcomputer analysis program would be set in accordance with the performance profile established by the par- ticipant(s) in the Step 1 screening ‘training study. In Step 2 the mechanics of microcomputer recording and analysis of subject selections would be the same as in Step 1, Step 2 differs from Step 1, however, in that a participant's selection from the random circle display, internally keyed to numbered sites, cannot be internally compared to a recorded correct answer. The results generated by the participant(s) in the site selection procedure would then be tabulated and discussed Qa > . Should the results appear encouraging, then Step 3 would’ be engaged, Cc, Step 3--Demonstration-o: -Feasibility Field Study ee eee ea ty Feid otuay The final step in the three-step vulnerability assessment. program would consist of a field-demonstration test involving <7 s - Data would be taken using the successful remote viewers of Step 2, both to determi ne the degree of correlation between performance on the tasks of Steps 2 and 3, and also to evaluate actual performance in the field study, Approved For Release 200 6- 10788r001300200001-6
‘ * 96-00788r001300200001-6 Approved For Release 200 7 | ‘ The possibility of success in such a field study is buttressed by ad the fact. that the procedures described here have been used by us success- fully in an exploratory program to determine the locations of hidden = Ce . Following a series of such tests, performance profiles for the individual remote viewers would be computed and the overall data set would be evaluated to provide an estimate as to the usefulness of RV 16 << Oe . ; -- Approved For Release 2 (QE) 95-00788r001200200001.8
t ft CC” _ Tt TT” TT TT Approved For Release 2000/ level-of-effort basis, of somewhat less than $200K for the first year is envisioned, - Approved For Release 2000/08/07 6-00788r001300200001-6 IV PROPOSED PROGRAM To accomplish the proposed program, SRI proposes to provide the necessary personnel, facilities, and materials to perform the outlined work, Summarized below, and to report on the results thereof, Provide to the sponsor the details of the statistical package and hardware setup tailored to sponsor-designated task requirements, Screen: train a population of volunteers on an LSI-11 microcomputer-modelled location problem, first with real-time feedback, then without (Step 1). Carry out simulation tests on mockups of an actual target situation uSing participants with successful performance profiles from Step 1 (Step 2). Carry out a demonstration-of-feasibility field study on a sponsor-designated test site of interest (Step 3). Evaluate data sets to provide estimates of: (a) Percentage of population trainable, (b) Level of proficiency to which task performance can be developed. {c) Usefulness of locating (ME tarcets by RV detection techniques, ; It is proposed that the above program be pursued on a three-man-year If programmed as a two-year effort, an expenditure An itemized cost breakdown can be provided on request. 17 Cl R P96-00788r001300200001-6