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the
time condition,
it
is 0.644
(minimum p = 0.121).
For the entire
experiment,
the minimum p-value
is still 0.002,
but
it
is based on
replications,
so
the overall
significance
level
is 0.032.
^
A more
interesting result with regard to potential
applications
is an estimate of
the reduction
in
the area
that would have
to be searched
if
the responses given by these subjects were used
instead
of randomly choosing
a starting point.
This can be computed by comparing
the average proportions given
in Table
1 with the chance average of
0.50125.
|
For Subject
837,
under
the
space condition,
the average
reduction would be
33%.
For example,
if
a search was undertaken for
a
kidnap victim,
and
this
subject achieved
the personal average
level of
functioning demonstrated
in
this experiment,
33% less area would have
to
be searched before
the victim was
found than
if a random starting point
was used.
Even though only one
subject had a significant result,
combining all
subjects'
guesses
in the space condition would still give an
average reduction of 6.5%
in
the area searched.
Depending upon the
application,
this reduction could still represent
a substantial
savings
in
expenditure of resources.
In the
time condition however,
the results
indicate
that
there would be no change
in search
time over chance.
_
Edition
to looking at
the average reduction
in search
area,
it
is of interest
for applications
to know what percent
of
the
trials would have resulted
in a smaller search area than expected by
chance.
For Subject
837
in the space condition,
18 out of
25,
or 72% of
all
trials resulted
in a savings.
This means
that
if this subject were
used repeatedly
to suggest
a starting point
for searches,
approximately
72% of all
targets would be found
in less
time than average,
and 28% would
require more
than
the average.
In contrast,
a random starting place
should result
in about
50% above and 50% below average search
times.
For
all subjects combined
in
the space condition,
104 out of
200,
or 52% of
all
trials resulted
in
a savings
in search area.
For
the
time condition
only,
102,
or 51% resulted
in
a smaller search area than would be expected
by chance.
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IV
DISCUSSION AND CONCLUSIONS (U)
I
^ The experiments discussed
in this report were designed
to
replicate and extend earlier findings which
indicated that selected
participants could use psychic means
to help search for a hidden target.
The computer-assisted search experiment,
which served as
a direct
replication of
the experiments conducted
in FY 1984 and FY 1986,
once
again showed promising results.
As
in the earlier experiments,
no subject
was able
to produce significant results
independently
in both the
time and
the space conditions.
Further,
the
two subjects who produced the best
results did
so* in the
space condition,
which replicated their performance
in the earlier experiments.
The best subject
in the time condition had
scored significantly
in the time condition
in FY 1986,
but not
in
space.
In general,
those who did well
in this experiment
(excluding one novice)
did
so
in the same condition for which they had previously scored
significantly
^
Even though n
is
small,
we were able
to speculate that
subjects bifurcate
into those who can search for fixed targets
(space)
and
those who can identify when
to register a guess
(time).
It would appear
that each subject would do best
in an experiment which contained only the
preferred condition.
A study done this year
to
test
that notion produced
completely chance results.
Thus,
it appears that even
if
this bifurcation
does exist,
it
is best
to present subjects with randomly scrambled
conditions.
Perhaps
the knowledge of exactly what
the task requires adds
an analytical component which
is hard
to overcome.
This has been observed
in other psychic
functioning,
such as forced choice guessing of targets m
remote viewing.
|
This
is
the third year
in which a computer-assisted search
experiment*has provided evidence
that psychic functioning may be of some
—
searching for hidden or
lost
use
in
targets.
Although such functioning
is not completely predictable,
it
appears
to be robust enough,
when selected subjects are used,
to
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r
significantly reduce
the average search time from what
it would be n
randomly located starting points were used.
(U) The Atocha
experiment, which was designed
to
see
if self-proclaimed
“dowsers"
would be able to locate a lost object using a grid overlaid on a map, did not produce a significant
finding, although a preliminary experiment showed very promising results.
It
is difficult to base
conclusions on one experiment with a small sample
size.
However,
it appears that whatever
pi-oduced the functioning with selected subjects in the computer-assisted search in the laboratory
did not carry over to the conditions of the Atocha experiment.
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?»'**"** m7
December
1987
EEDBACK AND PRECOGNITION DEPENDENT
.cuntc VIEWING EXPERIMENTS
(U)
SRI
Project
1291
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ABSTRACT (U)
r
irT~\ Two different precognition experiments were conducted during
FY 1987.
The first of these involved a well-calibrated viewer
(Subject
372)
and used natural Bay Area sites as
targets.
Ten real-time and ten
precognitive trials
(counterbalanced)
yielded no statistical evidence for
remote viewing.
In the second experiment,
four viewers contributed
approximately 30 trials each
in a similar counterbalanced real-time
vs.
precQgnition protocol.
In this experiment,
however,
the target material
were photographs from a national magazine.
No statistical evidence for
remote viewing was observed
in this experiment.
In a third experiment
designed
to explore the role
of feedback upon remote viewing quality,
two
of
ftjmr viewers produced independently significant evidence
for remote
viewing.
A number of speculations are offered as
to possible mechanisms
including real-time data acquisition and global precognition with noise
reduction.
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I INTRODUCTION (U)
S since
1973,
remote viewing
(RV)
has been observed under a wide
variety of different conditions.
A few of many possible examples are
coordinate
RV*
(targeting by geographical coordinates),
1 beacon RV
(known
person at
the remote
site)
, 2 abstract
targeting
(targeting by the word
"target"
or by a random number or binary number)
, 3 and targeting by remote
tasking
,
in which
the task
is sealed
in an envelope which
is
geographically isolated from the viewer.
To first order,
all of these
(and more)
have been demonstrated successfully
in
’
laboratory,
t
^
conditions.
'#
j
The main difficulty
in trying
to understand
the various
successes of RV from a fundamental point of view
is
that RV appears
to
require a large number of basic
theories
to explain
the variety of
observables.
How
is
it possible
to describe access
to remote information
with a single unifying concept when the target has been specified by a
complex series of random events,
separated
in time and space,
and these
events are completely unknown
to
the viewer?
This problem has been one of
the main sources of criticism about
the existence of
RV,
in that nothing
else
in nature appears
to have
such properties.
(It
is beyond the scope
of
this report
to argue
this point,
it suffices
to say that most of
the
great advances
in science contributed
to
the organization and
understanding of seemingly unrelated data.
The ultraviolet catastrophe
and early atomic spectra are but
two examples of
the confusion prior
to
the understanding provided by early quantum theory.)
(U)
SRI has been developing a heuristic model of psychoenergetic functioning4 that has
the potential of providing some understanding of the RV confusion described above.
It
is based
upon a concept called precognition.
Since the
1930s, the parapsychology literature has been
reporting experiments that claim to demonstrate the existence of precognition—remote viewing
of target material that had not been specified at the time of the viewing.
As yet, there
is not a
meta-analysis
of
this
literature, but
there
is
a
review
of
the experimental
support
for
(U)
References may be found at the end of this report.
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II METHOD OF APPROACH (U)
A.
(U) Real-Time vs. Precognition Experiment
(U)
During FY
1987, SRI conducted two experiments to examine the
effects of target
generation time in RV data acquisition. The first of these was with a selected viewer using natural
locations within 30 minutes driving time from SRI as target material.
In the other experiment,
four experienced viewers used photographs from the National Geographic Magazine as target
material.
In both experiments the time of target generation (before or after the RV session) was
unknown to either viewers or monitors.
1.
(U) The Beacon RV Series
(U) To examine the role of target generation upon out-bound RV experiments, SRI
asked an experienced viewer (Viewer 372)
to participate
in a 20-trial series.
Viewer 372 has
been
calibrated
in
this
particular
task
in
that
he/she
has
demonstrated
significant RV
performance in all
(2) of the beacon experiments conducted at SRI. 11
. 12
Furthermore, Viewer
372
has expressed strong preference
for
this type
of experiment rather than those
that use
photographs as targets.
^
The
target material consisted of
66 natural outdoor
locations within a half-hour's drive of
SRI.
The sites were selected on
the basis of
the past performance of Viewer
372.
Thus,
the target
selection criteria allowed sites
that would be more difficult
for novice
viewers.
The
intent was
to produce a target pool with a variety of
different material.
For Viewer
372,
the variety could be architectural
(and other details)
as well as general gestalt features.
a.
(U)
Protocol
(U) The viewer and the monitor were blind to both the target pool and the
individual
target
selections.
At
the
beginning
of each
trial,
the
viewer and monitor were
sequestered in the RV laboratory.
The assistant then selected the target generation time and,
if
appropriate, the target site. The target selection time for each trial was determined according to
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RESULTS AND DISCUSSION (U)
A.
(U) Real-Time vs. Precognition Experiments
1.
(U) The Beacon RV Series
(U) Table
1 shows the results of the 20-session beacon RV series.
Table
(U)
RESULTS FOR VIEWER 372
Condition
Trace
p-value
Real-time
45.5
0.154
Precognition
51.5
0.638
k
Overall, no condition met the criteria for statistical significance.
For Viewer 372, this represents
the first time at SRI that a series has not met statistical significance out of four attempts (counting
each condition as
a separate attempt).
Given Viewer 372’s track record, we allow
for some
speculation as to possible reasons for the results of this series.
^Viewer 372 first participated
in a six-trial RV experiment
in FY 1980.
That study produced four first place matches and two second
place matches
for a combined p-value of 0.003. 11
His/her second
participation was
in FY 1986.
when twelve beacon RV trials were conducted
with an overall p-value of 0.007. 12
Combined with the
two efforts
in FY
1987
(see Table
1)
the average p-value
is 0.201.
Using an exact
calculation, 16 the probability of observing an average p-value of 0.201
in
4 experiments
is
0.017.
This
is consistent with a minimum p-value
(0.003)
technique 17 which yields 0.012.
«
There are
at least
two possible hypotheses for this
experiment not reaching significance.
The first
(and most likely one)
is
given by Utts. 18
If one
is willing
to estimate a
"hit" rate given that RV
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is real,
then
it
is possible
to calculate
the probability of observing a
significant
study.
While
it
is difficult
to ascertain the actual
"hit"
rate for
RV,
Utts provides an estimate for a similar process—Ganzfeld.
For a 10-trial study the probability of observing a significant result
is
only 15%.
(MCE
is
5%,
of course.)
,
Secondly,
a new variable was
Introduced by the nature
of
the protocol.
The time between the remote viewing and the feedback was
greater than two hours.
This represents an order of magnitude
increase
over our other experiments.
The influence of
this
increase
is currently
unknown
2.
The T,arget Photograph Series
/
Table
2 shows
the results of
the four-viewer real-time
vs.
precognition experiment.
Based on the sum of ranks and their associated
p-values,
there was no significant evidence
of RV
in this
series.
Table
(U)
REAL-TIME VS.
PRECOGNITION RESULTS
Real-time
Precognition
All
Trials
rt/pc
009
(0.375)
(0.625)
119
(0.482)
15/15
105
(0.905)
(0.473)
112
(0.797)
13/13
177
(0.283)
(0.415)
(0.275)
9/12
454
(0.912)
(0.862)
138
(0.954)
15/15
Totals
220
(0.203)
227
(0.472)
447
(0.179)
52/55
(U)
Sum-of-ranks
(p-value)
Based on the past performance
(in real-time
RV)
of these
particular viewers,
the results are disappointing.
Yet,
because of their
record,
we speculate upon possible reasons why this experiment did not
reach significance.
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^
'
» As described above,
an estimate
(provided by Utts 18
)
of the
probability of a significant 10-15 trail RV series
is approximately 15%.
Yet
it remains surprising that no significant
series was observed
in eight
attempts
"a possible problem
is
that this particular experiment was
conducted after the successful tachistoscope experiment
(described below)
That experiment required 40 trials from each viewer.
Since this
experiment required 30 trails from each viewer,
a given viewer had to
produce 70 remote viewings
in approximately
days.
! In summary,
then,
we were unable
to demonstrate a
significant RV phenomenon
in the real-time
vs.
precognition experiments.
Considering the vast amount of data
in the literature that claim the
existence of .precognition,
we recommend that
the study should be continued
at
a later date.
B.
(U) The Tachistoscope Experiment
(U) Table
shows
the sum
of
ranks and
associated
p-values
for
the
tachistoscope
feedback experiment.
Table
(U)
TACHISTOSCOPE FEEDBACK EXPERIMENT*
Viewer
Result
009
131
(0.012)
105
182
(0.962)
137
159
(0.484)
177
104
(3
. 5xl0~
)
IL
—
r
(U)
Sum-of-ranks
(p-value)
Viewers 009 and 177 produced independently significant
results.
There are a number of ways
in which we could combine these data,
but
the most conservative
is
a binomial calculation assuming an event
probability of 0.05.
Two successes
in four trials corresponds
to an exact
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~—~i
p—Value of 0.014.
A more realistic estimate
is provided by a minimum
p-value
(3.5
x X0-6
)
technique which yields
1.4
x
10-*. 18
The important
point,
however,
is
that
this experiment produced strong evidence for an
informational anomaly.
Figures
3 and
show RV quality
(1
is
low,
is high)
plotted
against
intensity of
the feedback for Viewers
009 and
177,
respectively.
Shcpwn also
is
the regression
line for each viewer.
These figures are
to
be compared
to Figure
2,
the idealized expectations.
The result
that
is
easiest
to understand
in Figure
is
the positive correlation showing
increased RV performance with increased feedback intensity.
We did not
observe any such correlation with either of
the significant viewers.
In
fadt,
the
linear correlation coefficients were not significant.
f
^’ The lack of positive correlation
in the
light of significant
evidence of RV complicates
the
interpretation considerably.
The most
obvious conclusion
is
that
the viewers obtained their data
in real
time
and not from the later feedback.
But,
if
the argument posited
in Section
I
ip correct
(that precognition
is unfalsif iable)
,
then the experiment was
doojned
to failure from the
start.
Another equally likely hypothesis
is
that
the underlying assumption
that cognitive awareness constitutes
feedback information
is
incorrect.
If
this were
true,
we would expect
to
see no correlation with intensity even
if the precognition model were
correct.
i
Viewer
177' s average sum of ranks was significantly
(p
< 0.02)
greater than his/her sum of ranks
in the real-time
vs.
precognition
experiment.
Viewer 009 produced
a strong and similar trend that obtained
a probability against chance of 0.08.
Assuming these differences are
meaningful,
we can speculate
that something
in
the tachistoscope
experiment resulted
in a significant noise reduction.
Possibly,
short
exposures
to feedback material allow the viewer
to focus only upon the
majdr
items and thus reduce the noise—the precognition model
is assumed
here.
In any event,
continuing this experiment would shed light on
the
difficult feedback interpretation problem.
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FIGURE 4
(U) RV QUALITY VS. FEEDBACK INTENSITY: VIEWER 177
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Final Report
December
1982
REVISED JULY 1983
A REMOTE VIEWING EVALUATION PROTOCOL
(U)
"N
-€opy no.
...r.
This document consists of 48 pages.
SR+/ef^0W7
I
I *
For Release 2001/03/07
: CIA-RDP96-0
333 Ravenswood Ave.
• Menlo Park. CA 94025
TWX
910-373-2046
•
~^lex' 334 486
J
32001600^01=9.
4 is
359-6200
•
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<u)
the transcripts
in order of
the best to least match for each of
the n
targets.
A simple numerical counting procedure
is then used to estimate
the likelihood that
the judge's transcript /target snatches are by chance
alone. 2
This early technique contained little systematic structure for
determining the
final order of matches.
,
The first
step toward systematizing the rank order judging
procedure was to preprocess
the raw data in the transcript by "concep-
tualizing" both the verbal and the pictorial responses.
Conceptualizing
a transcript requires an analyst to paraphrase the transcript into a list
of
coherent
statements.
This concept
list
is then compared and scored
concept-by-concept
to each
of the targets in the experiment.
The resulting
scores are ‘'averaged for each response,
and all responses are rank-ordered
on the basis
of
these scores. 3
This improved analysis procedurewa^PpUed
to
a number of experiments within the Technology Transfer Task^^PJ^^
%
(U)
The problem with the above technique is that there are no guide-
lines as to how the analyst
should paraphrase the transcript;
furthermore,
the method
in which the concepts are
to be assessed against
the targets
remains undefined.
The purpose of
the Evaluation Task in FY 1982 was to
identify a procedure that corrected these deficiencies.
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IV
CONCLUSIONS
(U)
'
-“*
• A protocol
has been developed
to address
the relative evaluation
portion
of
the overall
RV transcript assessment problem.
As
a demonstra-
tion of
the
technique,
we provide
in Appendix A an analysis
of
a series
of
four remote viewings
that were performed
as calibrations
-
_
—
^
In this
series
the remote
Viewing products were
of relatively high-quality,
but nonetheless require
A sensitive
technique
to differentiate because of
the similarity of
the
targets
and,
hence,
of
the descriptions.
(The
series was chosen primarily
tor
that reason.)
Application
of
the assessment technique resulted
in
the
correct' blind matching
(highest
scoring
in matches
versus
cross
ijnatches )
of
three
of
the
foui
.
(U)
Appendix
B
is
a one
page,
step-by-step procedure
for
the
Application
of
this evaluation
technique.
(U)
The material
in
this document
thus constitutes
an instruction
manual
or protocol
tor application of
a step-by-step procedure
for quan-
titative assessment
of
the relative
target/ transcript correlations
of
a
series
of
transcripts matched
into
a series
of
targets.
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ducted as
geted
On
14 December
1981,
four coordinate remote viewings were
calibrations during a* ^
remote viewing session
^sites of interest.
'
con-
tar-
These four calibrations were
chosen as
a test
bed for the evaluation procedure for the following
reasons,
(1)
they were conducted
in an
setting,
and
(2)
the
targets had many similar features,
and would thus provide
a sensitive
test
of
the protocol.
Figures A-l
through A-4 are the
transcripts
that were presented
to
the analyst.
They are exactly as they were when collected,
except
that
the coordinates have been removed.
Figures A-5 through A-8 are the
National Geographic magazine targets
that were used during the calibration
sessions.
Finally,
the task coordinator provided Tables A-l
through A-4
as target element
relevance scales for the four targets
in Figures A-5
through A-8.
This completes
the information that was given to the analyst,
and thus the analysis was carried out blind as
to the matching target/
transcript
pairs.
(U)
Table A-5
is
a compilation of
the completed work sheets
that
were used by the analyst
in this evaluation.
They are
shown in groups
by session number,
and alphabetized on the four targets.
(The
task
coordinator first
randomized the transcript order then assigned
the session
number used above.)
For each of
the transcripts,
the analyst simply
included all phrases and all drawings as concepts.
For example,
seven
concepts were found during Session 2.
(U)
All concepts were then analyzed as described in the text.
The
matching
target
element,
its relevance rating,
and the computed score are
shown for all possible combinations
of transcript/target pairs
in Table
A-5.
The score distributions and their resulting weighted averages
are
also shown
in Table A-5.
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