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ОглавлениеMinority Report: Predicting Criminal Intent
“If there’s a flaw, it’s human—it always is.”
—Danny Witwer
Criminal Intent
There’s something quite enticing about the idea of predicting how people will behave in a given situation. It’s what lies beneath personality profiling and theories of preferred team roles. But it also extends to trying to predict when people will behave badly, and taking steps to prevent this.
In this vein, I recently received an email promoting a free online test that claims to use “‘Minority Report-like’ tech to find out if you are ‘predisposed’ to negative or bad behavior.” The technology I was being encouraged to check out was an online survey being marketed by the company Veris Benchmark under the trademark “Veris Prime.” It claimed that “for the first time ever,” users had an “objective way to measure a prospective employee’s level of trustworthiness.”
Veris’ test is an online survey which, when completed, provides you (or your employer) with a “Trust Index.” If you have a Trust Index of eighty to one hundred, you’re relatively trustworthy, but below twenty or so, you’re definitely in danger of showing felonious tendencies. At the time of writing, the company’s website indicates that the Trust Index is based on research on a wide spectrum of people, although the initial data that led to the test came from 117 white-collar felons. In other words, when the test was conceived, it was assumed that answering a survey in the same way as a bunch of convicted felons is a good way of indicating if you are likely to pursue equally felonious behavior in the future.
Naturally, I took the test. I got a Trust Index of nineteen. This came with a warning that I’m likely to regularly surrender to the temptation of short-term personal gain, including cutting corners, stretching the truth, and failing to consider the consequences of my actions.
Sad to say, I don’t think I have a great track record of any of these traits; the test got it wrong (although you’ll have to trust me on this). But just to be sure that I wasn’t an outlier, I asked a few of my colleagues to also take the survey. Amazingly, it turns out that academics are some of the most felonious people around, according to the test. In fact, if the Veris Prime results are to believed, real white-collar felons have some serious competition on their hands from within the academic community. One of my colleagues even managed to get a Trust Index of two.
One of the many issues with the Veris Prime test is the training set it uses. It seems that many of the traits that are apparently associated with convicted white-collar criminals—at least according to the test—are rather similar to those that characterize curious, independent, and personally-motivated academics. It’s errors like this that can easily lead us into dangerous territory when it comes to attempting to use technology to predict what someone will do. But even before this, there are tough questions around the extent to which we should even be attempting to use science and technology to predict and prevent criminal behavior. And this leads us neatly into the movie Minority Report.
Minority Report is based on the Philip K. Dick short story of the same name, published in 1956. The movie centers on a six-year crime prevention program in Washington, DC, that predicts murders before they occur, and leads to the arrest and incarceration of “murderers” before they can commit their alleged future crime. The “Precrime” program, as it’s aptly called, is so successful that it has all but eliminated murder in the US capital. And as the movie opens, there’s a ballot on the books to take it nationwide.
The Precrime program in the movie is astoundingly successful—at least on the surface. The program is led by Chief John Anderton (played by Tom Cruise). Anderton’s son was abducted six years previously while in his care, and was never found. The abduction destroyed Anderton’s personal life, leaving him estranged from his partner, absorbed in self-pity, and dependent on illegal street narcotics. Yet despite his personal pain, he’s a man driven to ensuring others don’t have to suffer a similar fate. Because of this, he is deeply invested in the Precrime program, and since its inception has worked closely with the program director and founder Lamar Burgess (Max von Sydow) to ensure its success.
The technology behind Precrime in the movie is fanciful, but there’s a level of internal consistency that helps it work effectively within the narrative. The program depends on three “precogs”: genetically modified, isolated, and heavily sedated humans who have the ability to foresee future murders. By monitoring and visualizing their neural activity, the Precrime team can see snatches of the precogs’ thoughts, and use these to piece together where and when a future murder will occur. All they then have to do is swoop in and arrest the pre-perpetrator before they’ve committed the crime. And, because the precogs’ predictions are trusted, those arrested are sentenced and incarcerated without trial. This incarceration involves being fitted with a “halo”—a neural device that plunges the wearer helplessly into their own incapacitating inner world, although whether this is a personal heaven or hell we don’t know.
As the movie opens, we’re led to believe that this breakthrough in crime prevention is a major step forward for society. Murder’s a thing of the past in the country’s capital, its citizens feel safer, and those with murderous tendencies are locked away before they can do any harm. That is, until Chief Anderton is tagged as a pre-perp by the precogs.
Not surprisingly, Anderton doesn’t believe them. He knows he isn’t a murderer, and so he sets out to discover where the flaw in the system is. And, in doing so, he begins to uncover evidence that there’s something rotten in the very program he’s been championing. On his journey, he learns that the precogs are not, as is widely claimed, infallible. Sometimes one of them sees a different sequence of events in the future, a minority report, that is conveniently scrubbed from the records in favor of the majority perspective.
Believing that his minority report—the account that shows he’s innocent of a future murder—is still buried in the mind of the most powerful precog, Agatha (played by Samantha Morton), he breaks into Precrime and abducts her. In order to extract the presumed minority report she’s carrying, he takes her to a seedy pleasure joint that uses recreational brain-computer interfaces to have her mind “read.” And he discovers, to his horror, that there is no minority report; all three precogs saw him committing the same murder in the near future.
Anderton does, however, come across an anomaly: a minority report embedded in Agatha’s memory of a murder that is connected with an earlier inconsistency he discovered in the Precrime records.
Still convinced that he’s not a murderer, Anderton sets about tracking down his alleged victim in order to prove his innocence, taking Agatha with him.32 He traces the victim to a hotel, and on entering his room, Anderton discovers the bed littered with photos of the man with young children, including his son. Suddenly it all fits into place. The trail has led Anderton to the one person he would kill without hesitation if he got the chance. Yet, even as Anderton draws his gun on his son’s abductor, Agatha pleads with him to reconsider. Despite her precognition, she tries to convince him that that the future isn’t set, and that he has the ability to change it. And so Anderton overcomes his desire for revenge and lowers his weapon.
It turns out Anderton was being set up. The victim—who wasn’t Anderton’s son’s abductor—was promised a substantial payout for his family if he convinced Anderton to kill him. When Anderton refuses, the victim grabs the gun in Anderton’s hand, presses it against himself, and pulls the trigger. As predicted, Anderton is identified as the killer, and is arrested, fitted with a halo, and put away.
With Anderton’s arrest, though, a darker undercurrent of events begins to emerge around the precog program. It turns out that Lamar Burgess, the program’s creator, has a secret that Anderton was in danger of discovering—an inconvenient truth that, to Lamar, stood in the way of what he believed was a greater social good. And so, to protect himself and the program, Lamar finds a way to use the precogs to silence Anderton.
As the hidden story behind the precog program is revealed, we discover that Agatha was born to a junkie mother, and suffered from being a terminally ill addict from birth. Agatha and other addict-babies became part of an ethically dubious experimental program using advanced genetic engineering to search for a cure. In this program, it’s discovered that, in Agatha’s case, a side effect of the experiments is an uncanny ability to predict future murders. Given their serendipitous powers, Agatha and two other subjects were sedated, sequestered away, wired up, and plugged into to what was to become the precog program. But Agatha’s mother cleaned herself up and demanded her daughter back, threatening the very core of this emerging technology.
Lamar couldn’t allow Agatha’s mother to threaten his plans, so he arranged an intricate ruse to dispose of her. Knowing that if he attempted to murder her, the precogs would predict it, Lamar paid a contract killer to murder Agatha’s mother. As anticipated, this was predicted and prevented by Precrime. But as soon as the killer-to-be had been hauled off, Lamar re-enacted the planned murder, this time succeeding.
Because Lamar’s act was so close to the attempted murder, images of his actions from the precogs were assumed to be part of the thwarted killing. And because Agatha’s precognition wasn’t quite in step with the two other precogs, it was treated as a minority report. In this way, using the system he’d created to bring an end to murder, Lamar pulled off the perfect murder—or so he thought. But as Anderton got closer to realizing that Lamar had staged Agatha’s mother’s murder, Lamar realized that, in order to protect Precrime, he also needed to be eliminated. And he would have succeeded, had Anderton’s estranged partner not put two and two together, and freed Anderton from his halo-induced purgatory.
Things come to a head in the movie as Anderton publicly broadcasts Agatha’s minority report of Lamar killing her mother. In doing so, he presents Lamar with a seemingly-impossible choice: kill Anderton (as the precogs are predicting) and validate the program, but be put away for life in the process; or don’t kill him, and in doing so, demonstrate a fatal flaw in the program that will result in it being terminated.
In the end, Burgess opts for a third option and kills himself. In doing so, he saves Anderton, but still reveals a flaw in the system that had predicted Anderton’s murder at his hand. As a result, Precrime is dismantled, and the precogs are allowed to live as full a life as is possible.
Minority Report is a fast-paced, crowd-pleasing, action sci-fi thriller of the caliber you’d expect from its director Stephen Spielberg. But it also raises tough questions around preemptive action based on predictive criminal behavior, as well as predestination, human dignity, and the dangers of being sucked in by seemingly beneficial technologies. It presents us with a world where technology has seemingly made people’s lives safer, but at a terrible cost that isn’t immediately obvious. And it shines a searing spotlight on the question of “should we” when faced with a seductive technology that ultimately threatens to place society in moral jeopardy.
The “Science” of Predicting Bad Behavior
In March 2017, the British newspaper The Guardian ran an online story with the headline “Brain scans can spot criminals, scientists say.”33 Unlike in Minority Report, the scanning was carried out using a hefty functional magnetic resonance imaging (fMRI) machine, rather than genetically altered precogs. But the story seemed to suggest that scientists were getting closer to spotting criminal intent before a crime had been committed, using sophisticated real-time brain imaging.
In this case, the headline vastly overstepped the mark. The original research used fMRI to see if brain activity could be used to distinguish knowingly criminal behavior from merely reckless behavior.34 It did this by setting up a somewhat complex situation, where volunteers were asked to take a suitcase containing something valuable through a security checkpoint while undergoing a brain scan. But to make things more interesting (and scientifically useful), their actions and choices came with financial rewards and consequences.
Each participant was first given $6,000 in “play money.” They were then presented with one to five suitcases, just one of which contained the thing of value. If they decided not to carry anything through the checkpoint, they lost $1,500. If they decided to carry a suitcase, it cost them $500. And if they dithered about it, they were docked $2,500.
Having selected a suitcase, if they chose the one with the valuable stuff inside and they weren’t searched by security, they got an additional $2,500—jackpot! But if they were searched and found to be carrying, they were fined $3,500, leaving them with a mere $2,000. On the other hand, if they weren’t carrying, they suffered no penalties, whether they were searched or not.
The point of this rather elaborate setup was that there were financial gains (at least with the fake money being used) involved with the choices made, and the implication that carrying a suitcase stuffed with valuable goods was dangerous (you could be fined if discovered carrying), but financially lucrative if you got away with it.
To mix things up further, some participants only had the choice of carrying the loaded suitcase (thus possibly getting $8,000), or declining to take part in such a dodgy deal and walking away with just $2,000. The participants who took a chance here were knowingly participating in questionable behavior. For the rest, it was a lottery whether they picked the loaded suitcase or not, meaning that their actions veered toward being more reckless, and less intentional. By simultaneously studying behavior and brain activity, the researchers were able to predict what state the participants were in—whether they were intentionally setting out to engage in behavior that maybe wasn’t legitimate, or whether they were just feeling reckless.
The long and short of this was that the study suggested brain activity could be used to indicate criminal intent, and this is what threw headline writers into a clickbait frenzy. But the research was far from conclusive. In fact, the authors explicitly stated that “it would be absurd to suggest, in light of our results, that the task of assessing the mental state of a defendant could or should, even in principle, be reduced to the classification of brain data.” They also pointed out that, even if these results could be used to predict the mental state of a person while committing a crime, they’d have to be inside an fMRI scanner at the time, which would be tricky.
Despite the impracticality of using this research to assess the mental state of people during the act of committing a crime, media stories around the study tapped into a deep-seated fascination with predicting criminal tendencies or intent—much as Veris Prime’s Truth Index does. Yet this is not a new fascination, and neither is the use of science to justify its indulgence.
In the seventeenth century, a very different “science” of predicting criminal tendencies was all the rage: phrenology. Phrenology was an attempt to predict someone’s character and behavior by the shape of their skull. As understanding around how the brain works developed, the practice became increasingly discredited. Sadly, though, it laid a foundation for assumptions that traits which appear to be common to people of “poor character” are also predictive of their behavior—a classic case of correlation erroneously being confused with causation. And it foreshadowed research that continues to this day to connect what someone looks like with how they might act.
Despite its roots in pseudoscience, the ideas coming out of phrenology were picked up by the nineteenth-century criminologist Cesare Lombroso. Lombroso was convinced that physical traits such as jaw size, forehead slope, and ear size were associated with criminal tendencies. His theory was that these and other traits were throwbacks to earlier evolutionary ancestors, and that they indicated an innate tendency toward criminal behavior.
It’s not hard to see how attractive these ideas might have been to some, as they suggested criminals could be identified and dealt with before breaking the law. With hindsight, it’s easy to see how misguided and malevolent they were, but at the time, many people bought into them. It would be nice to think that this way of thinking about criminal tendencies was a short and salutary aberration in humanity’s history. Sadly, though, it paved the way to even more divisive forms of pseudoscience-based discrimination, including eugenics.
In the 1900s, discrimination that was purportedly based on scientific evidence shifted toward the idea that the quality or “worth” of a person is based on their genetic heritage. The “science” of eugenics—and sadly this is something that many scientists at the time supported—suggested that our genetic heritage determines everything about us, including our moral character and our social acceptability. It was a deeply flawed concept that, nevertheless, came with the same seductive idea that, if we know what makes people “bad,” we can remove them from society before they cause a problem. What is heartbreaking is that these ideas coming from academics and scientists gained political momentum, and ultimately became part of the justification for the murder of six million Jews, and many others besides, in the Holocaust.
These days, I’d like to think we’re more enlightened, and that we don’t fall prey so easily to using scientific flights of fancy to justify how we treat others. Unfortunately, this doesn’t seem to be the case.
In 2011, three researchers published a paper suggesting that you can tell a criminal from someone who isn’t (and, presumably by inference, someone who is likely to engage in criminal activities) by what they look like.35 In the study, thirty-six students in a psychology class (thirty-three women and three men) were shown mug shots of thirty-two Caucasian males. They were told that some were criminals, and they were asked to assess—from the photos alone—whether each person had committed a crime; whether they’d committed a violent crime; if it was a violent crime, whether it was rape or assault; and if it was non-violent, whether it was arson or a drug offense.
Within the limitations of the study, the participants were more likely to correctly identify criminals than incorrectly identify them from the photos. Not surprisingly, perhaps, this led to a slew of headlines along the lines of “Criminals Look Different From Non-criminals” (this one from a blog post on Psychology Today36). But despite this, the results of the study are hard to interpret with any degree of certainty. It’s not clear what biases may have been introduced, for instance, by having the photos evaluated by a mainly female group of psychology students, or by only using photos of white males, or even whether there was something associated with how the photos were selected and presented, and how the questions were asked, that influenced the results.
The results did seem to indicate that, overall, the students were successful in identifying photos of convicted criminals in this particular context. But the study was so small, and so narrowly defined, that it’s hard to draw any clear conclusions from it. However, there is a larger issue at stake with this and similar studies, and this is the ethical issue with carrying out and publicizing the results of such research in the first place. Here, the very appropriateness of asking if we can predict criminal behavior brings us back to the earlier study on intent versus reckless behavior, and to the underlying premise in Minority Report.
The assumption that someone’s behavioral tendencies can be predicted from no more than what they look like, or how their brain functions, is a slippery slope. It assumes—dangerously so—that behavior is governed by genetic heritage and upbringing. But it also opens the door to a better-safe-than-sorry attitude to law and order that considers it better to restrain someone who might demonstrate socially undesirable behavior than to presume them innocent until proven guilty. And it’s an attitude that takes us down a path where we assume that other people do not have agency over their destiny. There is an implicit assumption here that how we behave can be separated out into “good” and “bad,” and that there is consensus on what constitutes these. But this is a deeply flawed assumption.
What the behavioral research above is actually looking at is someone’s tendency to break or bend agreed-on rules of socially acceptable conduct, as these are codified in law. These laws are not an absolute indicator of good or bad behavior. Rather, they are a result of how we operate collectively as a social species. In technical terms, they establish normative expectations of behavior, which simply means that most people comply with them, irrespective of whether they have moral or ethical value. For instance, in most cultures, it’s accepted that killing someone should be punished, unless it’s in the context of a legally sanctioned war or execution (although many societies would still consider this morally reprehensible). This is a deeply embedded norm, and most people would consider it to be a good guide of appropriate behavior. The same cannot be said of “norms” surrounding homosexual acts, though, which were illegal in the United Kingdom until 1967, and are still illegal in some countries around the world, or others surrounding LGBTQ rights, or even women’s rights.
When social norms are embedded within criminal law, it may be possible to use physical features or other means to identify “criminals” or those likely to be involved in “criminal” behavior. But are we as a society really prepared to take preemptive action against people who we arbitrarily label as “bad”? I sincerely hope not. And here we get to the crux of the ethical and moral challenges around predicting criminal intent. Even if we can predict tendencies from images alone—and I am highly skeptical that we can gain anything of value here that isn’t heavily influenced by researcher bias and social norms—should we? Is it really appropriate to be asking if we can predict, simply from how someone looks, whether they are likely to behave in a way that we think is appropriate or not? And is it ethical to generate data that could be used to discriminate against people based on their appearance?
Using facial features to predict tendencies puts us way down the slippery slope toward discriminating against people because they are different from us. Thankfully, this is an idea that many would dismiss as inappropriate these days. But, worryingly, our interest in relating brain activity to behavioral traits—the high-tech version of “looks like a criminal”—puts us on the same slippery slope.
Criminal Brain Scans
Unlike photos, functional Magnetic Resonance Imaging allows researchers to directly monitor brain activity, and to do it in real time. It works by monitoring blood flow to different parts of the brain, and using this to pinpoint which parts of someone’s brain are active at any one point in time.
One of the beauties of fMRI is that it can map out brain activity as people are thinking about and processing the world around them. For instance, it can show which parts of a subject’s brain are triggered if they’re shown a photo of a donut, if they are happy, or sad, or angry, or what their brain activity looks like if they’re given the opportunity to take a risk.
fMRI has opened up a fascinating window into how we think about and respond to our surroundings, and in some cases, what we think. And it’s led to some startling revelations. We now know, for instance, that we often unconsciously decide what we’re going to do several seconds before we’re actually aware of making a decision.37 Recent research has even indicated that high-resolution fMRI scans on primates can be used to decode what the animals are seeing.38 The researchers were, quite literally, reading these primates’ minds.
This is quite incredible science. And not surprisingly, it’s leading to a revolution in understanding how our brains operate. This includes developing a better understanding of how certain brain behaviors can lead to debilitating medical conditions. It’s also leading to a deeper understanding of how the mechanics of our brain determine who we are, and how we behave.
That said, there’s still considerable skepticism around how effective a tool fMRI is and how robust some of its findings are. It’s also fair to say that some of these findings challenge deeply held beliefs about many of the things we hold dear, including the nature of free will, moral choice, kindness, compassion, and empathy. These are all aspects of ourselves that help define who we are as a person. Yet, with the advent of fMRI and other neuroscience-based tools, it sometimes feels like we’re teetering on the precipice of realizing that who we think we are—our sense of self, or our “soul” if you like—is merely an illusion of our biology.
This in itself raises questions over the degree to which neuroscience is racing ahead of our ability to cope with what it reveals. Yet the reality is that this science is progressing at breakneck speed, and that fMRI is allowing us to dive ever deeper behind our outward selves—our facial features and our easily observed behaviors—and into the very fabric of the organ that plays such a role in defining us. And, just like phrenology and eugenics before it, it’s opening up the temptation to interpret how our brains operate as a way to predict what sort of person we are, and what we might do.
In 2010, researchers provided a group of subjects with advice on the importance of using sunscreen every day. At the same time, the subjects’ brain activity was monitored using fMRI. It’s just one of many studies that are increasingly trying to use real-time brain activity monitoring to predict behavior.
In the sunscreen study, the subjects were asked how likely they were to take the advice they were given. A week later, researchers checked in with them to see how they’d done. Using the fMRI scans, the researchers were able to predict which subjects were going to use sunscreen and which were not. But more importantly, using the scans, the researchers discovered they were better at predicting how the subjects would behave than they themselves were. In other words, the researchers knew their subjects’ minds better than they did.39
Research like this suggests that our behavior is determined by measurable biological traits as much as by our free will, and it’s pushing the boundaries of how we understand ourselves and how we behave, both as individuals and as a society. And, while science will never enable us to predict the future in the same way as Minority Report’s precogs, it’s not too much of a stretch to imagine that fMRI and similar techniques may one day be used to predict the likelihood of someone engaging in antisocial and morally questionable behavior.
But even if predicting behavior based on what we can measure is potentially possible, is this a responsible direction to be heading in?
The problem is, just as with research that tries to tie facial features, head shape, or genetic heritage to a propensity to engage in criminal behavior, fMRI research is equally susceptible to human biases. It’s not so much that we can collect data on brain activity that’s problematic; it’s how we decide what data to collect, and how we end up interpreting and using it, that’s the issue.
A large part of the challenge here is understanding what the motivation is behind the research questions being asked, and what subtle underlying assumptions are nudging a complex series of scientific decisions toward results that seem to support these assumptions.
Here, there’s a danger of being caught up in the misapprehension that the scientific method is pure and unbiased, and that it’s solely about the pursuit of truth. To be sure, science is indeed one of the best tools we have to understand the reality of how the world around us and within us works. And it is self-correcting—ultimately, errors in scientific thinking cannot stand up to the scrutiny the scientific method exposes them to. Yet this self-correcting nature of science takes time, sometimes decades or centuries. And until it self-corrects, science is deeply susceptible to human foibles, as phrenology, eugenics, and other misguided ideas have all too disturbingly shown.
This susceptibility to human bias is greatly amplified in areas where the scientific evidence we have at our disposal is far from certain, and where complex statistics are needed to tease out what we think is useful information from the surrounding noise. And this is very much the case with behavioral studies and fMRI research. Here, limited studies on small numbers of people that are carried out under constrained conditions can lead to data that seem to support new ideas. But we’re increasingly finding that many such studies aren’t reproducible, or that they are not as generalizable as we at first thought. As a result, even if a study does one day suggest that a brain scan can tell if you’re likely to steal the office paper clips, or murder your boss, the validity of the prediction is likely to be extremely suspect, and certainly not one that has any place in informing legal action—or any form of discriminatory action—before any crime has been committed.
Machine Learning-Based Precognition
Just as in Minority Report, the science and speculation around behavior prediction challenges our ideas of free will and justice. Is it just to restrict and restrain people based on what someone’s science predicts they might do? Probably not, because embedded in the “science” are value judgments about what sort of behavior is unwanted, and what sort of person might engage in such behavior. More than this, though, the notion of pre-justice challenges the very idea that we have some degree of control over our destiny. And this in turn raises deep questions about determinism versus free will. Can we, in principle, know enough to fully determine someone’s actions and behavior ahead of time, or is there sufficient uncertainty and unpredictability in the world to make free will and choice valid ideas?
In Chapter Two and Jurassic Park, we were introduced to the ideas of chaos and complexity, and these, it turns out, are just as relevant here. Even before we have the science pinned down, it’s likely that the complexities of the human mind, together with the incredibly broad and often unusual panoply of things we all experience, will make predicting what we do all but impossible. As with Mandelbrot’s fractal, we will undoubtedly be able to draw boundaries around more or less likely behaviors. But within these boundaries, even with the most exhaustive measurements and the most powerful computers, I doubt we will ever be able to predict with absolute certainty what someone will do in the future. There will always be an element of chance and choice that determines our actions.
Despite this, the idea that we can predict whether someone is going to behave in a way that we consider “good” or “bad” remains a seductive one, and one that is increasingly being fed by technologies that go beyond fMRI.
In 2016, two scientists released the results of a study in which they used machine learning to train an algorithm to identify criminals based on headshots alone.40 The study was highly contentious and resulted in a significant public and academic backlash, leading the paper’s authors to state in an addendum to the paper, “Our work is only intended for pure academic discussions; how it has become a media consumption is a total surprise to us.”41
Their work hit a nerve for many people because it seemed to reinforce the idea that criminal behavior is something that can be predicted from measurable physiological traits. But more than this, it suggested that a computer could be trained to read these traits and classify people as criminal or non-criminal, even before they’ve committed a crime.
The authors vehemently resisted suggestions that their work was biased or inappropriate, and took pains to point out that others were misinterpreting it. In fact, in their addendum, they point out, “Nowhere in our paper advocated the use of our method as a tool of law enforcement, nor did our discussions advance from correlation to causality.”
Nevertheless, in the original paper, they conclude: “After controlled for race, gender and age, the general law-biding [sic] public have facial appearances that vary in a significantly lesser degree than criminals.” It’s hard to interpret this as anything other than a conclusion that machines and artificial intelligence could be developed that distinguish between people who have criminal tendencies and those who do not.
Part of why this is deeply disturbing is that it taps into the issue of “algorithmic bias”—our ability to create artificial-intelligence-based apps and machines that reflect the unconscious (and sometimes conscious) biases of those who develop them. Because of this, there’s a very real possibility that an artificial judge and jury that relies only on what you look like will reflect the prejudices of its human instructors.
This research is also disturbing because it takes us out of the realm of people interpreting data that may or may not be linked to behavioral tendencies, and into the world of big data and autonomous machines. Here, we begin to enter a space where we have not only trained computers to do our thinking for us, but we no longer know how they’re thinking. In a worrying twist of irony, we are using our increasing understanding of how the human brain works to develop and train artificial brains that we are increasingly ignorant of the inner workings of.
In other words, if we’re not careful, in our rush to predict and preempt undesirable human behavior, we may end up creating machines that exhibit equally undesirable behavior, precisely because they are unpredictable.
Big Brother, Meet Big Data
Despite being set in a technologically advanced future, one of the more intriguing aspects of Minority Report is that it falls back on human intuition when interpreting the precog data feed. In the opening sequences, Chief Anderton performs an impromptu “ballet” of preemptive deduction, as he turns up the music and weaves the disjointed images being fed through from the three precogs into a coherent narrative. This is a world where, perhaps ironically, given the assumption that human behavior is predictable, intuition and creativity still have an edge over machines.
Anderton’s professional skills tap into a deep belief that there’s more to the human mind than its simply being the biological equivalent of a digital computer—even a super-powerful one. As the movie opens, Anderton is responsible for fitting together a puzzle of fragmented information. And, as he aligns the pieces and fills the gaps, he draws connections between snippets of information that seem irrelevant or disjointed to the untrained eye, so much so that the skill he demonstrates lies in the sum total of his experiences as a living human being. This is adeptly illustrated as Anderton pins down the location of an impending murder by recognizing inconsistencies in two images that, he deduces, could only be due to a child riding an old-fashioned merry-go-round.
This small intuitive leap is deeply comforting to us as viewers. It confirms to that there’s something uniquely special about people, and it suggests that we are more than the sum of the chemicals, cells, and organs we’re made of. It also affirms a belief that we cannot simply be defined by what we look like, or by the electrical and chemical processes going on inside our head.
But are we right in this belief that we are more than the sum of our parts? What if we could be reduced to massive amounts of data that not only determine who we are, but how we will act and react in any given situation?
Questions like this would have been hypothetical, bordering the fantastical, not so long ago. Certainly, as a species, we’ve toyed with the idea for centuries that people are simply complex yet ultimately predictable biological machines (chaos theory not withstanding). But it’s only recently that we’ve had the computing power to start capturing every minutia of ourselves and the world around us and utilizing it in what’s increasingly called “big data.”
“Big data”—which when all’s said and done is just a fancy way of saying massive amounts of information that we can do stuff with—has its roots in human genome sequencing. Our genetic code has three billion discrete pieces of information, or base pairs, that help define us biologically. Compared to the storage capacity of early computers, this is a stupendously large amount of information, far more than could easily be handled by the computing systems of the 1970s and 1980s, or even the 1990s, when the initiative to decode the complete human genome really took off. But, as we began to understand the power of digital computing, scientists started to speculate that, if we could decode the human genome and store it in computer databases, we would have the key to the code of life.
With hindsight, they were wrong. As it turns out, decoding the human genome is just one small step toward understanding how we work. But this vision of identifying and cataloguing every piece of our genome caught hold, and in the late 1990s it led to one of the biggest sets of data ever created. It also spawned a whole new area of technology involving how we collect, store, analyze, and use massive amounts of data, and this is what is now known colloquially as Big Data.
As we’ve since discovered, the ability to store three billion base pairs of genetic code in computer databases barely puts us in the foothills of understanding human biology. The more we find out, the more complex we discover life is. But the idea that the natural world can be broken down into its constituent parts, uploaded into cyberspace, and played around with there remains a powerful one. And there’s still a belief held by some that, if we have a big enough computer memory and a powerful enough processor, we could in principle encode every aspect of the physical and biological world and reproduce it virtually.
This is the idea behind movies like The Matrix (which sadly didn’t make the cut for this book) where most people are unwittingly playing out their lives inside a computer simulation. It also underpins speculations that arise every now and again that we are all, in fact, living inside a computer simulation, but just don’t know it. There are even researchers working on the probability that this is indeed the case.42
This is an extreme scenario that comes out of our growing ability to collect, process, and manipulate unimaginable amounts of data. It’s also one that has some serious flaws, as our technology is rarely as powerful as our imaginations would like it to be. Yet the data revolution we’re currently living through is still poised to impact our lives in quite profound ways, including our privacy.
