Finally, there are ways of fooling a brain scanner, just as there are countermeasures for other lie-detection techniques. Ganis says, “I’ve done a study showing that you can play mental tricks with fMRI. You mentally associate the important events of your life to items that are shown during the test.” By bringing those events to mind at the right time, volunteers could bamboozle the scans, and slash their accuracy from 100% to just 33%. “If you ever want to apply a technique like this in real cases, where people have motivation to beat the test, that’ll become an important issue,” says Ganis.
Doubts and concerns
FMRI scanners will undoubtedly improve, but the problems of countermeasures and the subjectivity of memory, may be harder to solve. A report from the Royal Society on neuroscience and the law said that these problems were “seemingly insuperable”. Ganis agrees: “If you want a general lie detector, that’s definitely science fiction right now.”
That hasn’t stopped fMRI from being marketed as a tool for lie detection – two companies called Cephos and No Lie MRI currently offer such services, the latter under a tagline of “New truth verification technology”. Nor has it deterred brain scans from being presented in courtrooms, with varying success. In recent years, two US judges have dismissed fMRI-based evidence, but a murder suspect in India was sentenced to life imprisonment after brain scans supposedly revealed that she had knowledge about a crime that only the killer could have possessed.
Possible misuse of this developing technology has raised ethical concerns about the future of brain-based lie detection. Daniel Langleben from the University of Pennsylvania, who did much of the pioneering work in this field, recognises the limitations of the technique, but thinks that it could be improved to the point where it could be usefully applied in practical settings. But he worries that the current doubts will stifle the research necessary to improve the technology.
“It would be nice if for every new review and commentary, and I include myself here, there was new data,” he says. “Every time you have a negative critical review, it has a chilling effect on people who want to do this research. As we speak, I’m sitting on a data set that I haven’t submitted because I just don’t have the energy to deal with [the reactions].”
For now, we know there are broad differences between an honest brain and a dishonest one. To turn that knowledge into a practical test, “you need a lot of boring validation work,” says Langleben. “We need clinical trials, just as for every medical device or test.” Such trials would try to work out how accurate the scans are in more realistic settings, and how often they make errors. They would assess the effects of age, motivation, mental disorders, medication, countermeasures and more. They would likely cost tens of millions of dollars, and would need to include thousands of people – far more than the dozens who take part in typical fMRI lab studies.
For now, a foolproof lie detector is a far-away goal, but it will be even more distant if no one can afford to do the necessary research. That, at least, is no lie.
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