test is actually deceptive. This probability is the positive predictive value of the test. If the base rate of deceptive individuals in a population of examinees is 1 in 1,000, an individual who is judged deceptive on the test will in fact be nondeceptive more than 199 times out of 200, even if the test has A = 0.90, which is highly unlikely for the polygraph (the actual numbers of true and false positives in our hypothetical population are shown in the right half of part a of Table 2-1). Thus, a result that is taken as indicating deception on such a test does so only with a very small probability.

These numbers contrast sharply with their analogs in a criminal investigation setting, in which people are normally given a polygraph test only if they are suspects. Suppose that in a criminal investigation the polygraph is used on suspects who, on other grounds, are estimated to have a 50 percent chance of being guilty. For a test with A = 0.80 and a sensitivity of 50 percent, the false positive index is 0.23 and the positive predictive value is 81 percent. That means that someone identified by this polygraph protocol as deceptive has an 81 percent chance of being so, instead of the 0.4 percent (1 in 250) chance of being so if the same test is used for screening a population with a base rate of 1 in 1,000.3

Thus, a test that may look attractive for identifying deceptive individuals in a population with a base rate above 10 percent looks very much less attractive for screening a population with a very low base rate of deception. It will create a very large pool of suspect individuals, within which the probability of any specific individual being deceptive is less than 1 percent—and even so, it may not catch all the target individuals in the net. To put this another way, if the polygraph identifies 100 people as indicating deception, but only 1 of them is actually deceptive, the odds that any of these identified examinees is attempting to deceive are quite low, and it would take strong and compelling evidence for a decision maker to conclude on the basis of the test that this particular examinee is that 1 in 100 (Murphy, 1987).

Although actual base rates are never known for any type of screening situation, base rates can be given rough bounds. In employee screening settings, the base rate depends on the security violation. It is probably far higher for disclosure of classified information to unauthorized individuals (including “pillow talk”) than it is for espionage, sabotage, or terrorism. For the most serious security threats, the base rate is undoubtedly quite low, even if the number of major threats is 10 times as large as the number of cases reported in the popular press, reflecting both individuals caught but not publicly identified and others not caught. The one major spy caught in the FBI is one among perhaps 100,000 agents who have been employed in the bureau’s history. The base rate of major security threats in the nation’s security agencies is almost certainly far less than 1 percent.



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