Automated surveillance allows governments (and others) to data mine the physical world, yet little attention has been paid to the ethics of perpetual recording.
Hello, human, I'm here to see you (MGM).
Over the past decade, video surveillance has exploded. In many cities, we might as well have drones hovering overhead, given how closely we're being watched, perpetually, by the thousands of cameras perched on buildings. So far, people's inability to watch the millions of hours of video had limited its uses. But video is data and computers are being set to work mining that information on behalf of governments and anyone else who can afford the software. And this kind of automated surveillance is only going to get more sophisticated as a result of new technologies like iris scanners and gait analysis.
Yet little thought has been given to the ethics of perpetually recording vast swaths of the world. What, exactly, are we getting ourselves into?
The New Aesthetic isn't just a cool art project; machines really are watching us, and they have their own way of seeing; they make mistakes that humans don't. Before automated surveillance reaches a critical mass, we are going to have to think carefully about whether we think its security benefits are worth the human costs it imposes. The ethical issues go beyond just video; think about data surveillance, about algorithms that can mine your financial history or your internet searches for patterns that could suggest you're an aspiring terrorist. You'd want to be sure that a technology like that was accurate.
Fortunately, our British friends are slightly ahead of the curve when it comes to thinking through the dilemmas posed by ubiquitous electronic surveillance. As a result of an interesting and contingent set of historical circumstances, the British now live under the watchful eye of a massive video surveillance system. British philosophers are starting to gaze back at the CCTV cameras watching them, and they're starting to demand that those cameras justify their existence. In a new paper called The Unblinking Eye: The Ethics of Automating Surveillance, philosopher Kevin Macnish argues that the political and cultural costs of excessive surveillance could be so great that we ought to be as hesitant about using it as as we are about warfare. That is to say, we ought to limit automated surveillance to those circumstances where we know it to be extremely effective. I spoke to Macnish about his theory, and about how technology is changing surveillance, for better and for worse.
I was thinking the other day that it's curious that CCTV should have bloomed in Britain, whose population we think of as being less security-crazed than the population of the United States. British is more urban than America, but it can't just be that, can it?
Macnish: One interesting historical point, and I don't think this clarifies the whole thing but it helps, is that most other western countries have a recent history of some form of dictatorship, the US exempted. Most of the Europe was under a dictator or occupied by a dictatorship within the living memory, and so I think there is an awareness there about the dangers of government. It's possible that Britain might be a little bit more laissez-fare about surveillance because we haven't had that level of autocratic control since the 17th century. I think in America, while the history is a little bit different, you have a very strong social consciousness about separation of powers within the state, and between the state and the people. I think there is a general suspicion of the state in America, which we often just don't have in the U.K.
Then you have to couple that with some very powerful images. In 1993 there was an infamous case of a 2 year-old named James Bulger who was kidnapped by two other children who were themselves about 10 or 11. They kidnapped him and then killed him in a very horrible way that mimicked a murder from one of the Child's Play films, which led to a massive reaction against horror films and whatever else. At the time there was a CCTV image taken of the two boys picking up this toddler and walking off with him, while holding his hand. Ironically, the CCTV didn't actually help with solving the case. The police had already heard about the case of these two boys and were already investigating them, but the image came across on our TV screens and came into our newspapers and it was really powerful. That helped to favor people towards CCTV here. It hadn't been thoroughly researched at the time and it was sort of suspected at a common sense level that it would help deter crime, and that it would detect and catch criminals, and that it would be able to help to find lost children. So, the government poured hundreds and millions of pounds into CCTV cameras all around the country and then retailers and businesses bought CCTV cameras for their own security---it just took off. As a sociological study, it's fascinating. A lot of my American friends that come here feel really freaked out by the amount of cameras we have, and with good reason.
What is automated surveillance? Where and how is it most commonly used? I know the Chinese have been developing a kind of gait analysis, a way to identify people on video based on the length and speed of their stride. In what other ways is this technology gathering steam?
Macnish: There are things like iris recognition, there are areas where people are looking at parts of the face for identification purposes; there are all of these ways that you can now automate the recognition of individuals, or the intentions of individuals. You have a ton of research on these capabilities, in the U.S. and China, especially, and as a result these techniques are catching on in a way that they weren't five or ten years ago, when we didn't yet have the technology to implement them. We've had the artificial intelligence capabilities for a while---since the late 70's we've been able to write programs that could recognize when a bag had been left by a particular person in a public place. But we didn't have the camera technology or processing technology to roll it out.
Now you have digital cameras, and increased storage and processing capacity, and so you're starting to see these really startling things happening in automated surveillance.
What advantages does automated surveillance have over traditional, human-directed surveillance?
Macnish: The problem with human surveillance is the humans. People get bored; they look away. In many operation centers there will be one person monitoring as many as 50 cameras, and that's not a recipe for accuracy. Science has demonstrated that it's possible for a person to be watching one screen and miss what's happening on it, and so you can imagine watching a busy scene in a mall, and there are 20 people in it, or a field of 50 different screens---you're not going to be able to see what every single person does. You might very well miss the person who puts their bag down and walks off, and that bag might be the one containing the bomb. If you can automate that process, then, in theory, you're removing the weakest link in the chain and you're saving a human being a lot of effort. The other problem with us humans is that we tend to be subject to prejudices. As a result we may focus our attention on people we find attractive, or on people we think are more likely to be terrorists or more likely to be up to no good, and in the mean time we might miss the target we're supposed to be looking for. And this doesn't just happen with terrorists, it can happen with shoplifters too.
On the other hand, we humans have common sense, which is something that computers lack and will probably always lack. For instance, there are computer surveillance programs designed to recognize a person bending down next to a car for a certain period of time, because this is behavior associated with stealing cars. At the moment the processing capacity is such that a computer can recognize a person bending down by a car and staying bent by a car for five seconds, at which point it will send an alert. Now, if a human is watching a person bending down next to a car, they will look to see if they're bending down to pet their dog, or to tie a shoelace, or because they've dropped their keys. The computer isn't going to know that.
In your paper, you describe the way that cultural differences often dictate the way that people move through crowds. For instance, in Saudi Arabia, people walk much slower than they do in London. Another example: in some cultures, people require less personal space than in others. Why are those differences problematic for automated surveillance?
Macnish: The particular automated surveillance I was looking at was designed to measure the distance between people to determine whether or not they were walking together. The theory behind it was that if you and I are walking together through a train station and I put my bag down next to you so that I could go off and get a newspaper or something like that, then clearly the bag is not unattended. This is one of those cases where a human being would instantly recognize that we are walking together and that we are friends, and that the bag isn't a danger, but the computer wouldn't recognize that we were friends. Instead the computer would see an unattended bag and it would send out an alert, and so when I come back from getting my coffee, or my newspaper, I might find you swarmed by security guards, guns drawn. The programmers behind this project were trying to write software that could determine whether two people walking in public are associated with each other in some way, and the way that they did this was to use an algorithm called a "social force model," which looks at how closely people are walking together, how far apart they are, how they interact with nearby objects, and how people walking towards them react to them. Those data points, together, can give you a determination of whether or not people are associated in some way. But problems appear when you consider that different cultural groups have different norms and habits, and that the social and spatial parameters of middle class white guys in the west might be totally different from the social and spatial parameters of two Indian women. There are all these subtle aspects and differences in the way that people from different cultures interact, and there is very little data on how people of different cultures, different sexes, and different ages, walk and act in public. Most of our data is drawn from western middle-class scenarios, things like universities or whatever. It's not the deliberate prejudice that you might see with a camera operator, who might focus on Somalis or Arabs, or some other particular group, but its effects can be just as bad.
Your paper argues for a theory of efficacy, when it comes to surveillance. You seem to say that this can only be ethical if we do it very well.
Macnish: Yes, but it goes deeper than that. My overall project is to argue that the questions that are typically raised in the Just War tradition are the questions that we should be asking about surveillance, in order to see whether or not it (surveillance) is justified. One way of doing that is to question these technologies' chances of success. In Just War theory we have this notion that a war is unethical if you are unlikely to succeed when you enter into it, because it means sending soldiers to die in vain. That was the perspective that I was coming from with the argument about efficacy---if there isn't a considerable chance of success then we shouldn't be pursuing these techniques.
But that rationale, Just War theory, is specific to war and it's specific to war for a very important reason. If we embark on ineffective wars, we run into disastrous consequences with enormous human costs. It's not clear that surveillance ought to have a precautionary principle as strong as the one governing warfare. Why do you think that it should?
Macnish: You have to look at the counterfactual; if we have arbitrary surveillance, which you could argue is what we have in the UK where we have virtually no regulation of CCTV cameras, there is an extent to which you start to wonder why we're being surveilled? Why are we being watched? And the surveillance can have quite an impact on society, it can shape society in ways that that we may not want. If you notice all of this surveillance, and you also notice that it's ineffective, you start to wonder if there's an ulterior motive for it. Heavy surveillance, of which CCTV is only one variety, can create a lot of fear in a population: it creates a sense of vulnerability, a fear of being open to blackmail or other forms of manipulation as a result of what's being recorded by surveillance, and these can, together, create what are typically called chilling effects, where people cease to engage in democratic speech or democratic traditions because they're concerned about what might be discovered about them or said about them. For instance, you might think twice about attending a political demonstration or political meeting if you know you're going to be watched. In the UK, there is a special police unit called FIT (Foreign Intelligence Team) that watches demonstrations, looking for certain trouble makers within political demonstrations---that might dissuade people from going to demonstrate. There is now a response protest group called FIT Watch that is going out to watch the FIT officers who are watching the demonstrators to try meliorate this problem, which is viewed as potentially damaging democratic engagement.
On balance, what about Britain's CCTV System? How does it score in your efficacy framework?
I think it probably fails on most counts. I was thinking about this last night. I've been kind of getting into probes and automated warfare more recently. Boeing is currently working on a drone that can stay in the air for five years without refueling. One that can stay up for 4 days was just successfully tested a couple of days ago. Think about a drone flying above you for five years. If you're in occupied Afghanistan, that is going to be very, very intimidating, and it would be just as intimidating if that were happening in our own country, if there were surveillance drones constantly flying above us. That could feel very intimidating.
Ultimately, there is very little difference between a drone flying above a city and the sort of CCTV surveillance that we have here all the time. It's just one is more out of the ordinary because we're kind of used to it.
You argue that in some ways automated surveillance is less likely to trigger privacy concerns than manual surveillance. Why is that?
Macnish: Say you are taking a shower and a person walks in while you're in the bathroom. You might feel an invasion of privacy, especially if you don't know that person. If a dog walks in, are you going to feel an invasion of privacy? Probably not. I mean there might be some sense of "hey, I don't want this dog looking at me," but it's only a dog. It might be that being watched by a computer is like being watched by the dog; you aren't entirely comfortable with it, but it's better than a human being, a stranger. Now, if it recorded the images it saw and then allowed a human to see those images, then, yes, that would be an invasion of privacy. If it had some automated process where as a result instead of seeing what you do in private, it took some action, that would likewise be an invasion of privacy. But yes, one benefit of automated surveillance is that it can take the human out of the equation, and that can be a net positive for privacy under certain circumstances.
In your paper you argue for a middle ground between manual surveillance and automated surveillance. What does that ideal middle ground look like in the context of something like the CCTV system in the UK?
Macnish: One reason that I argue for a middle ground goes back to the fact that computers don't have much common sense, which can lead to false positives, as we saw with the unattended bag or the person who drops their keys in a parking garage. A computer could be very helpful for filtering out some obvious false positives, but ideally a human should come in to look at what's left. A computer can provide a good filtering mechanism, for purposes of privacy. For instance, a computer could blur out people's faces, or their entire bodies so that a human operator sees only the action in question. At that point, if the action is still deemed suspicious, the operator can specifically request that the image be un-blurred so he can see who the person is and see how he needs to respond to them.
In the context of automated surveillance, does privatization worry you?
Macnish: That's a really interesting question. I think the privatization of creating the software and the hardware in and of itself doesn't bother necessarily me; what concerns me more is the privatization of the operation of the surveillance. So, privatizing the people who are watching the cameras, privatizing what is done with the information from the cameras---when private companies hold that sort of information, especially if they're not regulated, there are all sorts of abuses that could flow from that. There's a second thing that might be worth saying about that as well, and it ties back in with the Arab Spring. After Mubarak fell, when we went into his secret police headquarters, we found all sorts of British, French and American spying equipment, which people like Boeing and whoever else sold to the Libyans and Egyptians knowing very well what would happen with it. Of course there are companies right now that are either still doing, or recently stopped doing the same, for Syria. I think that's a legitimate concern as well.
Video surveillance like CCTV surveillance is only one kind of automated surveillance; automated data surveillance is another. I'm thinking about intelligence organizations looking for patterns in millions of financial transactions and internet searches. Are there overlaps in the ethical issues presented by data surveillance and camera surveillance?
Macnish: Definitely. The same questions that we're asking about CCTV should be asked about data surveillance. Potentially I think that could be very concerning. And that's not just true of intelligence organizations, but of commercial organizations as well. The New York Times recently ran an article about Target and the lengths it would go to know that a 16 year old girl was pregnant---so much so that they knew before her dad did. Those are the kinds of questions commercial organizations are looking to answer. And you have to ask what they do with that information---are they offering better deals to the sort of customers they would rather have as their clientele? Are they trying to put people off who they would rather not have as their clientele? For instance, frequent fliers get all sorts of deals on their flights because they get frequent fliers that spend a lot of money on the airline. Are you creating a situation where the rich, successful people are the ones that get offered better deals to fly on the planes, whereas poorer people don't get those same offers. The questions raised by big data are very interesting. It's actually a very rich area for research; we haven't even scratched the surface of it.
The Islamic State is no mere collection of psychopaths. It is a religious group with carefully considered beliefs, among them that it is a key agent of the coming apocalypse. Here’s what that means for its strategy—and for how to stop it.
What is the Islamic State?
Where did it come from, and what are its intentions? The simplicity of these questions can be deceiving, and few Western leaders seem to know the answers. In December, The New York Times published confidential comments by Major General Michael K. Nagata, the Special Operations commander for the United States in the Middle East, admitting that he had hardly begun figuring out the Islamic State’s appeal. “We have not defeated the idea,” he said. “We do not even understand the idea.” In the past year, President Obama has referred to the Islamic State, variously, as “not Islamic” and as al-Qaeda’s “jayvee team,” statements that reflected confusion about the group, and may have contributed to significant strategic errors.
Without the financial support that many white families can provide, minority young people have to continually make sacrifices that set them back.
He died on a Saturday.
My mother and I had planned to pick my dad up from the hospital for a trip to the park. He loved to sit and watch families stroll by as we chatted about oak trees, Kona coffee, and the mysteries of God. This time, the park would miss him.
His skin, smooth and brown like the outside of an avocado seed, glistened with sweat as he struggled to take his last breaths.
In that next year, I graduated from grad school, got a new job, and looked forward to saving for a down payment on my first home, a dream I had always had, but found lofty. I pulled up a blank spreadsheet and made a line item called “House Fund.”
Places like St. Louis and New York City were once similarly prosperous. Then, 30 years ago, the United States turned its back on the policies that had been encouraging parity.
Despite all the attention focused these days on the fortunes of the “1 percent,” debates over inequality still tend to ignore one of its most politically destabilizing and economically destructive forms. This is the growing, and historically unprecedented, economic divide that has emerged in recent decades among the different regions of the United States.
Until the early 1980s, a long-running feature of American history was the gradual convergence of income across regions. The trend goes back to at least the 1840s, but grew particularly strong during the middle decades of the 20th century. This was, in part, a result of the South catching up with the North in its economic development. As late as 1940, per-capita income in Mississippi, for example, was still less than one-quarter that of Connecticut. Over the next 40 years, Mississippians saw their incomes rise much faster than did residents of Connecticut, until by 1980 the gap in income had shrunk to 58 percent.
The sport is becoming an enterprise where underprivileged young men risk their health for the financial benefit of the wealthy.
Football can be a force for good. The University of Missouri’s football team proved it earlier this month when student athletes took a facet of campus life that’s often decried—the cultural and economic dominance of college football—and turned it into a powerful leverage point in the pursuit of social justice. Football can build a sense of community for players and fans alike, and serve as a welcome escape from the pressures of ordinary life. The sport cuts across distinctions of race, class, geography, and religion in a way few other U.S. institutions do, and everyone who participates reaps the benefits.
But not everyone—particularly at the amateur level—takes on an equal share of the risk. College football in particular seems headed toward a future in which it’s consumed by people born into privilege while the sport consumes people born without it. In a 2010 piece in The Awl, Cord Jefferson wrote, “Where some see the Super Bowl, I see young black men risking their bodies, minds, and futures for the joy and wealth of old white men.” This vision sounds dystopian but is quickly becoming an undeniable reality, given new statistics about how education affects awareness about brain-injury risk, as well as the racial makeup of Division I rosters and coaching staffs. The future of college football indeed looks a lot like what Jefferson called “glorified servitude,” and even as information comes to light about the dangers and injustices of football, nothing is currently being done to steer the sport away from that path.
“Wanting and not wanting the same thing at the same time is a baseline condition of human consciousness.”
Gary Noesner is a former FBI hostage negotiator. For part of the 51-day standoff outside the Branch Davidian religious compound in Waco, Texas, in 1993, he was the strategic coordinator for negotiations with the compound’s leader, David Koresh. This siege ended in infamous tragedy: The FBI launched a tear-gas attack on the compound, which burned to the ground, killing 76 people inside. But before Noesner was rotated out of his position as the siege’s head negotiator, he and his team secured the release of 35 people.
Jamie Holmes, a Future Tense Fellow at New America, spoke to Noesner for his new book Nonsense: The Power of Not Knowing. “My experience suggests,” Noesner told Holmes, “that in the overwhelming majority of these cases, people are confused and ambivalent. Part of them wants to die, part of them wants to live. Part of them wants to surrender, part of them doesn’t want to surrender.” And good negotiators, Noesner says, are “people who can dwell fairly effectively in the areas of gray, in the uncertainties and ambiguities of life.”
Nuts-and-bolts Washington coverage has shifted to subscription-based publications, while the capitol’s traditional outlets have shrunk.
Back in 2009, I had a job with a Washington, D.C.-based newsletter called Water Policy Report. It wasn’t exactly a household name, but I was covering Congress, the federal courts, and the Environmental Protection Agency—a definite step up from the greased-pig-catching contests and crime-blotter stories I had chased at a community newspaper on Maryland’s Eastern Shore, my first job out of college.
One of my responsibilities at the newsletter was to check the Federal Register—the official portal that government agencies use to inform the public about regulatory actions. In December of that year I noticed an item that said that the Environmental Protection Agency had decided that existing pollution controls for offshore oil-drilling platforms in the Gulf of Mexico were adequate, and that there wasn’t enough pollution coming from those platforms to warrant further review or action.
Why are so many kids with bright prospects killing themselves in Palo Alto?
The air shrieks, and life stops. First, from far away, comes a high whine like angry insects swarming, and then a trampling, like a herd moving through. The kids on their bikes who pass by the Caltrain crossing are eager to get home from school, but they know the drill. Brake. Wait for the train to pass. Five cars, double-decker, tearing past at 50 miles an hour. Too fast to see the faces of the Silicon Valley commuters on board, only a long silver thing with black teeth. A Caltrain coming into a station slows, invites you in. But a Caltrain at a crossing registers more like an ambulance, warning you fiercely out of its way.
The kids wait until the passing train forces a gust you can feel on your skin. The alarms ring and the red lights flash for a few seconds more, just in case. Then the gate lifts up, signaling that it’s safe to cross. All at once life revives: a rush of bikes, skateboards, helmets, backpacks, basketball shorts, boisterous conversation. “Ew, how old is that gum?” “The quiz is next week, dipshit.” On the road, a minivan makes a left a little too fast—nothing ominous, just a mom late for pickup. The air is again still, like it usually is in spring in Palo Alto. A woodpecker does its work nearby. A bee goes in search of jasmine, stinging no one.
While some companies squeeze staff to make more money, a growing number are testing the theory that they can have both profits and happy workers.
NORWICH, Vt.–Call centers are not, typically, very happy places—especially around the holidays. Workers have quotas to make, and often sit in bleak cubicles, headsets on, plowing through calls from stressed shoppers, as they count down the minutes until lunch.
But the employees in this call center in Vermont are rosy-cheeked and—can it be?—smiling. They field calls about misplaced packages and gluten-free dough, while surrounded by orange and red Thanksgiving decorations and a wall lined with baking gear that they’re allowed to borrow. They still have quotas—10 calls per hour, per agent—but they know they won’t get fired if they spend 45 minutes talking to a woman with cancer about baking, as one agent recently did.
It was widely seen as a counter-argument to claims that poor people are "to blame" for bad decisions and a rebuke to policies that withhold money from the poorest families unless they behave in a certain way. After all, if being poor leads to bad decision-making (as opposed to the other way around), then giving cash should alleviate the cognitive burdens of poverty, all on its own.
Sometimes, science doesn't stick without a proper anecdote, and "Why I Make Terrible Decisions," a comment published on Gawker's Kinja platform by a person in poverty, is a devastating illustration of the Science study. I've bolded what I found the most moving, insightful portions, but it's a moving and insightful testimony all the way through.
A Chicago cop now faces murder charges—but will anyone hold his colleagues, his superiors, and elected officials accountable for their failures?
Thanks to clear video evidence, Chicago police officer Jason Van Dyke was charged this week with first-degree murder for shooting 17-year-old Laquan McDonald. Nevertheless, thousands of people took to the city’s streets on Friday in protest. And that is as it should be.
The needlessness of the killing is clear and unambiguous:
Yet that dash-cam footage was suppressed for more than a year by authorities citing an investigation. “There was no mystery, no dead-end leads to pursue, no ambiguity about who fired the shots,” Eric Zorn wrote in The Chicago Tribune. “Who was pursuing justice and the truth? What were they doing? Who were they talking to? With whom were they meeting? What were they trying to figure out for 400 days?”