The search for a truly effective lie detector gained new urgency after the terrorist attacks of 11 September 2001. Several of the hijackers had managed to enter the US after successfully deceiving border agents. Suddenly, intelligence and border services wanted tools that actually worked. A flood of new government funding made lie detection big business again. “Everything changed after 9/11,” writes psychologist Paul Ekman in Telling Lies.
Ekman was one of the beneficiaries of this surge. In the 1970s, he had been filming interviews with psychiatric patients when he noticed a brief flash of despair cross the features of Mary, a 42-year-old suicidal woman, when she lied about feeling better. He spent the next few decades cataloguing how these tiny movements of the face, which he termed “micro-expressions”, can reveal hidden truths.
Ekman’s work was hugely influential with psychologists, and even served as the basis for Lie to Me, a primetime television show that debuted in 2009 with an Ekman-inspired lead played by Tim Roth. But it got its first real-world test in 2006, as part of a raft of new security measures introduced to combat terrorism. That year, Ekman spent a month teaching US immigration officers how to detect deception at passport control by looking for certain micro-expressions. The results are instructive: at least 16 terrorists were permitted to enter the US in the following six years.
Investment in lie-detection technology “goes in waves”, said Dr John Kircher, a University of Utah psychologist who developed a digital scoring system for the polygraph. There were spikes in the early 1980s, the mid-90s and the early 2000s, neatly tracking with Republican administrations and foreign wars. In 2008, under President George W Bush, the US Army spent $700,000 on 94 handheld lie detectors for use in Iraq and Afghanistan. The Preliminary Credibility Assessment Screening System had three sensors that attached to the hand, connected to an off-the-shelf pager which flashed green for truth, red for lies and yellow if it couldn’t decide. It was about as good as a photocopier at detecting deception – and at eliciting the truth.
Some people believe an accurate lie detector would have allowed border patrol to stop the 9/11 hijackers. “These people were already on watch lists,” Larry Farwell, the inventor of brain fingerprinting, told me. “Brain fingerprinting could have provided the evidence we needed to bring the perpetrators to justice before they actually committed the crime.” A similar logic has been applied in the case of European terrorists who returned from receiving training abroad.
As a result, the frontline for much of the new government-funded lie detection technology has been the borders of the US and Europe. In 2014, travellers flying into Bucharest were interrogated by a virtual border agent called Avatar, an on-screen figure in a white shirt with blue eyes, which introduced itself as “the future of passport control”. As well as an e-passport scanner and fingerprint reader, the Avatar unit has a microphone, an infra-red eye-tracking camera and an Xbox Kinect sensor to measure body movement. It is one of the first “multi-modal” lie detectors – one that incorporates a number of different sources of evidence – since the polygraph.
But the “secret sauce”, according to David Mackstaller, who is taking the technology in Avatar to market via a company called Discern Science, is in the software, which uses an algorithm to combine all of these types of data. The machine aims to send a verdict to a human border guard within 45 seconds, who can either wave the traveller through or pull them aside for additional screening. Mackstaller said he is in talks with governments – he wouldn’t say which ones – about installing Avatar permanently after further tests at Nogales in Arizona on the US-Mexico border, and with federal employees at Reagan Airport near Washington DC. Discern Science claims accuracy rates in their preliminary studies – including the one in Bucharest – have been between 83% and 85%.
The Bucharest trials were supported by Frontex, the EU border agency, which is now funding a competing system called iBorderCtrl, with its own virtual border guard. One aspect of iBorderCtrl is based on Silent Talker, a technology that has been in development at Manchester Metropolitan University since the early 2000s. Silent Talker uses an AI model to analyse more than 40 types of microgestures in the face and head; it only needs a camera and an internet connection to function. On a recent visit to the company’s office in central Manchester, I watched video footage of a young man lying about taking money from a box during a mock crime experiment, while in the corner of the screen a dial swung from green, to yellow, to red. In theory, it could be run on a smartphone or used on live television footage, perhaps even during political debates, although co-founder James O’Shea said the company doesn’t want to go down that route – it is targeting law enforcement and insurance.
O’Shea and his colleague Zuhair Bandar claim Silent Talker has an accuracy rate of 75% in studies so far. “We don’t know how it works,” O’Shea said. They stressed the importance of keeping a “human in the loop” when it comes to making decisions based on Silent Talker’s results.
Mackstaller said Avatar’s results will improve as its algorithm learns. He also expects it to perform better in the real world because the penalties for getting caught are much higher, so liars are under more stress. But research shows that the opposite may be true: lab studies tend to overestimate real-world success.
Before these tools are rolled out at scale, clearer evidence is required that they work across different cultures, or with groups of people such as psychopaths, whose non-verbal behaviour may differ from the norm. Much of the research so far has been conducted on white Europeans and Americans. Evidence from other domains, including bail and prison sentencing, suggests that algorithms tend to encode the biases of the societies in which they are created. These effects could be heightened at the border, where some of society’s greatest fears and prejudices play out. What’s more, the black box of an AI model is not conducive to transparent decision making since it cannot explain its reasoning. “We don’t know how it works,” O’Shea said. “The AI system learned how to do it by itself.”
Andy Balmer, the University of Manchester sociologist, fears that technology will be used to reinforce existing biases with a veneer of questionable science – making it harder for individuals from vulnerable groups to challenge decisions. “Most reputable science is clear that lie detection doesn’t work, and yet it persists as a field of study where other things probably would have been abandoned by now,” he said. “That tells us something about what we want from it.”
The truth has only one face, wrote the 16th-century French philosopher Michel de Montaigne, but a lie “has a hundred thousand shapes and no defined limits”. Deception is not a singular phenomenon and, as of yet, we know of no telltale sign of deception that holds true for everyone, in every situation. There is no Pinocchio’s nose. “That’s seen as the holy grail of lie detection,” said Dr Sophie van der Zee, a legal psychologist at Erasmus University in Rotterdam. “So far no one has found it.”
The accuracy rates of 80-90% claimed by the likes of EyeDetect and Avatar sound impressive, but applied at the scale of a border crossing, they would lead to thousands of innocent people being wrongly flagged for every genuine threat it identified. It might also mean that two out of every 10 terrorists easily slips through.
History suggests that such shortcomings will not stop these new tools from being used. After all, the polygraph has been widely debunked, but an estimated 2.5m polygraph exams are still conducted in the US every year. It is a $2.5bn industry. In the UK, the polygraph has been used on sex offenders since 2014, and in January 2019, the government announced plans to use it on domestic abusers on parole. The test “cannot be killed by science because it was not born of science”, writes the historian Ken Alder in his book The Lie Detectors.
New technologies may be harder than the polygraph for unscrupulous examiners to deliberately manipulate, but that does not mean they will be fair. AI-powered lie detectors prey on the tendency of both individuals and governments to put faith in science’s supposedly all-seeing eye. And the closer they get to perfect reliability, or at least the closer they appear to get, the more dangerous they will become, because lie detectors often get aimed at society’s most vulnerable: women in the 1920s, suspected dissidents and homosexuals in the 60s, benefit claimants in the 2000s, asylum seekers and migrants today. “Scientists don’t think much about who is going to use these methods,” said Giorgio Ganis. “I always feel that people should be aware of the implications.”
In an era of fake news and falsehoods, it can be tempting to look for certainty in science. But lie detectors tend to surface at “pressure-cooker points” in politics, when governments lower their requirements for scientific rigour, said Balmer. In this environment, dubious new techniques could “slip neatly into the role the polygraph once played”, Alder predicts.
One day, improvements in artificial intelligence could find a reliable pattern for deception by scouring multiple sources of evidence, or more detailed scanning technologies could discover an unambiguous sign lurking in the brain. In the real world, however, practised falsehoods – the stories we tell ourselves about ourselves, the lies that form the core of our identity – complicate matters. “We have this tremendous capacity to believe our own lies,” Dan Ariely, a renowned behavioural psychologist at Duke University, said. “And once we believe our own lies, of course we don’t provide any signal of wrongdoing.”
In his 1995 science-fiction novel The Truth Machine, James Halperin imagined a world in which someone succeeds in building a perfect lie detector. The invention helps unite the warring nations of the globe into a world government, and accelerates the search for a cancer cure. But evidence from the last hundred years suggests that it probably wouldn’t play out like that in real life. Politicians are hardly queueing up to use new technology on themselves. Terry Mullins, a long-time private polygraph examiner – one of about 30 in the UK – has been trying in vain to get police forces and government departments interested in the EyeDetect technology. “You can’t get the government on board,” he said. “I think they’re all terrified.”
Daniel Langleben, the scientist behind No Lie MRI, told me one of the government agencies he was approached by was not really interested in the accuracy rates of his brain-based lie detector. An fMRI machine cannot be packed into a suitcase or brought into a police interrogation room. The investigator cannot manipulate the test results to apply pressure to an uncooperative suspect. The agency just wanted to know whether it could be used to train agents to beat the polygraph.
“Truth is not really a commodity,” Langleben reflected. “Nobody wants it.”
Source: The GuardianRelated posts: