What you're missing about your conclusion is that you're ignoring the base rate of deception in the population you're testing. Within your hypothetical 80% deception indicated group, you could only conclude that more than half were lying if the base rate of deception was greater than 50%. If the base rate of deception is low, then the majority of your 80% deception indicated group would be false positives...
The bolded statement would only be true if we assume a priori that the polygraph doesn't work - i.e. it provides no information about the
actual individuals being tested - which is what we are meant to be investigating. It is equivalent to saying:
IF the
real deception rate in the tested subjects is low
AND the
polygraph's positive rate is high
THEN most of the positives are false - a completely contentless statement.
Continuing with the hypothetical example: I've forgotten what detection and false positive rates we're assuming (and can't be bothered trawling the entire thread to find out). Let's be conservative and say 70% detection and 10% false positive. We want to know the proportion of liars in the group that has tested positive. You are right that we also need to know the proportion of liars in the population under consideration – say 20%. Then:
Of 100
representative subjects:
20 are liars
80 are truthful
Of the 20 liars:
70% = 14 will be correctly detected
6 will not be detected
Of the 80 truthful subjects:
10% = 8 will be incorrectly 'detected'
72 will be found truthful
Summary:
True Negatives = 72
True Positives = 14
False Negatives = 6
False Positives = 8
Therefore, of the group that tests positive, 8 out of 22 i.e. 36% are false positives (innocent test failures) and not 'the majority'.
Imagine you run this test with 100 subjects every day for several years, with an average of 22 positives per day, and on one particular day 80 of the subjects test positive. That would certainly be anomalous.
So, reviewing the assumptions:
1) The detection rate (70%),
2) The false positive rate (10%),
3) The proportion of liars in the test's base population (20%),
4) That the group that scored 80% positive is representative of that population,
plainly, at least one of the above is wrong, but the numbers themselves cannot tell us which. If we got a batch of results like this in any kind of medical screening test we would begin by suspecting a malfunction in the assay or machine, or some administrative error. Failing that, we would consider the possibility that this batch of subjects was atypical in some way, and investigate whether or not this invalidated the results. (In the atheists example, the explanation could indeed be that professed atheists are several times more likely to lie than the general population - that would be quite consistent with the figures.)
My point is that it would be quite invalid to conclude that an anomalous high result well above the assumed base rate means that the subjects must be truthful and the polygraph incorrect.
If you knew that 80-90% of the people you were going to test were actually guilty, how hard do you think it would be to identify the guilty just through good interrogation alone?
As you point out, the accuracy of any test (false-positive and detection rates) is completely independent of the frequency of the condition (guilt and deception) in the test population. If you know that 80-90% of the subjects are guilty then yes, you could use interrogation techniques such that 80-90% confess, or a polygraph threshhold such that 80-90% test positive, but that does not 'identify the guilty'. If the test has no discriminatory power then you will still have equal detection and false positive rates - i.e. the test performs no better than chance. (This may be clear to you but it probably wasn't clear to most people reading this thread.)
But that's OK. "Polygraphs perform better than chance", so you have nothing to worry about. Nothing!!
It could be interesting to hear from those who are so impressed with the evidence just what they think the polygraphs can be used for.
The polygraph doesn't show that 80% of the subjects were lying. It shows that 80% of the subjects had a deviation from the baseline. To repeat and rephrase my earlier question which hasn't been answered yet (not directed particularly at you but for the proponents in general):
How can you tell the difference between a lie and a nervous reaction to a question when you don't know what the truthfull answer is?
CFLarsen, I see you have shifted your ground, and are no longer claiming that the basic concept is 'pseudoscience'. Good.
I don't think there are any 'proponents' of polygraphy here. My view is that there will probably never be any justification for routine use of the polygraph, and there is probably no justification for any (non-research) use at all at the moment. My motivation (and, I guess, skeptigirl's and drkitten's) was simply to correct a misconception - rather carelessly propagated by the anti-polygraph movement, and the 'skeptical' movement in general - that polygraph technology is bogus like
Rife cancer treatment machines and
electronic exercise belts and
diagnostic dowsing machines etc. The claim is often made by the 'anti' campaigners that the results are entirely due to a kind of reverse-placebo effect, and the actual discrimination is performed by the trained tester using information completely separate from the machine readings. The point is that this is the wrong argument, and can easily be demolished by polygraph enthusiasts (for example, by reference to the NA report, especially the
results of laboratory studies). The right argument is that the accuracy of the unaided technology is far below what is claimed (and commonly believed), and that it is therefore neither safe nor effective for any current or proposed use.
How could we use the polygraph in a real-world setting when we don't know the 'correct' result? .13., the important point to grasp is that the polygraph is no different in this respect from
any imperfect test – a medical screening test, for example. We do the basic research, conduct studies to determine the scope of validity and obtain the 'calibration' data. When we have enough confidence in the test we introduce it in the field, including QA to monitor and improve the test's performance.
As to distinguishing a nervous response from a guilty one, we assume that there are in principle some detectable differences between the two types of response, and try to refine the test to amplify these differences. As digithead suggests, there are theoretical reasons to suggest that the problem will be reduced by using GKT-type questions rather than CQT – I don't know how well this has been tested.