Fooling Face Recognition with Infrared Light
Yet another development in the arms race between facial recognition systems and facial-recognition-system foolers.
BoingBoing post.
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Yet another development in the arms race between facial recognition systems and facial-recognition-system foolers.
BoingBoing post.
Two related stories:
PornHub is using machine learning algorithms to identify actors in different videos, so as to better index them. People are worried that it can really identify them, by linking their stage names to their real names.
Facebook somehow managed to link a sex worker’s clients under her fake name to her real profile.
Sometimes people have legitimate reasons for having two identities. That is becoming harder and harder.
This is a good interview with Apple’s SVP of Software Engineering about FaceID.
Honestly, I don’t know what to think. I am confident that Apple is not collecting a photo database, but not optimistic that it can’t be hacked with fake faces. I dislike the fact that the police can point the phone at someone and have it automatically unlock. So this is important:
I also quizzed Federighi about the exact way you “quick disabled” Face ID in tricky scenarios—like being stopped by police, or being asked by a thief to hand over your device.
“On older phones the sequence was to click 5 times [on the power button], but on newer phones like iPhone 8 and iPhone X, if you grip the side buttons on either side and hold them a little while—we’ll take you to the power down [screen]. But that also has the effect of disabling Face ID,” says Federighi. “So, if you were in a case where the thief was asking to hand over your phone—you can just reach into your pocket, squeeze it, and it will disable Face ID. It will do the same thing on iPhone 8 to disable Touch ID.”
That squeeze can be of either volume button plus the power button. This, in my opinion, is an even better solution than the “5 clicks” because it’s less obtrusive. When you do this, it defaults back to your passcode.
More:
It’s worth noting a few additional details here:
- If you haven’t used Face ID in 48 hours, or if you’ve just rebooted, it will ask for a passcode.
- If there are 5 failed attempts to Face ID, it will default back to passcode. (Federighi has confirmed that this is what happened in the demo onstage when he was asked for a passcode—it tried to read the people setting the phones up on the podium.)
- Developers do not have access to raw sensor data from the Face ID array. Instead, they’re given a depth map they can use for applications like the Snap face filters shown onstage. This can also be used in ARKit applications.
- You’ll also get a passcode request if you haven’t unlocked the phone using a passcode or at all in 6.5 days and if Face ID hasn’t unlocked it in 4 hours.
Also be prepared for your phone to immediately lock every time your sleep/wake button is pressed or it goes to sleep on its own. This is just like Touch ID.
Federighi also noted on our call that Apple would be releasing a security white paper on Face ID closer to the release of the iPhone X. So if you’re a researcher or security wonk looking for more, he says it will have “extreme levels of detail” about the security of the system.
Here’s more about fooling it with fake faces:
Facial recognition has long been notoriously easy to defeat. In 2009, for instance, security researchers showed that they could fool face-based login systems for a variety of laptops with nothing more than a printed photo of the laptop’s owner held in front of its camera. In 2015, Popular Science writer Dan Moren beat an Alibaba facial recognition system just by using a video that included himself blinking.
Hacking FaceID, though, won’t be nearly that simple. The new iPhone uses an infrared system Apple calls TrueDepth to project a grid of 30,000 invisible light dots onto the user’s face. An infrared camera then captures the distortion of that grid as the user rotates his or her head to map the face’s 3-D shape—a trick similar to the kind now used to capture actors’ faces to morph them into animated and digitally enhanced characters.
It’ll be harder, but I have no doubt that it will be done.
More speculation.
I am not planning on enabling it just yet.
This is some interesting research. You can fool facial recognition systems by wearing glasses printed with elements of other people’s faces.
Mahmood Sharif, Sruti Bhagavatula, Lujo Bauer, and Michael K. Reiter, “Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition“:
ABSTRACT: Machine learning is enabling a myriad innovations, including new algorithms for cancer diagnosis and self-driving cars. The broad use of machine learning makes it important to understand the extent to which machine-learning algorithms are subject to attack, particularly when used in applications where physical security or safety is at risk. In this paper, we focus on facial biometric systems, which are widely used in surveillance and access control. We define and investigate a novel class of attacks: attacks that are physically realizable and inconspicuous, and allow an attacker to evade recognition or impersonate another individual. We develop a systematic method to automatically generate such attacks, which are realized through printing a pair of eyeglass frames. When worn by the attacker whose image is supplied to a state-of-the-art face-recognition algorithm, the eyeglasses allow her to evade being recognized or to impersonate another individual. Our investigation focuses on white-box face-recognition systems, but we also demonstrate how similar techniques can be used in black-box scenarios, as well as to avoid face detection.
ID checks were a common response to the terrorist attacks of 9/11, but they’ll soon be obsolete. You won’t have to show your ID, because you’ll be identified automatically. A security camera will capture your face, and it’ll be matched with your name and a whole lot of other information besides. Welcome to the world of automatic facial recognition. Those who have access to databases of identified photos will have the power to identify us. Yes, it’ll enable some amazing personalized services; but it’ll also enable whole new levels of surveillance. The underlying technologies are being developed today, and there are currently no rules limiting their use.
Walk into a store, and the salesclerks will know your name. The store’s cameras and computers will have figured out your identity, and looked you up in both their store database and a commercial marketing database they’ve subscribed to. They’ll know your name, salary, interests, what sort of sales pitches you’re most vulnerable to, and how profitable a customer you are. Maybe they’ll have read a profile based on your tweets and know what sort of mood you’re in. Maybe they’ll know your political affiliation or sexual identity, both predictable by your social media activity. And they’re going to engage with you accordingly, perhaps by making sure you’re well taken care of or possibly by trying to make you so uncomfortable that you’ll leave.
Walk by a policeman, and she will know your name, address, criminal record, and with whom you routinely are seen. The potential for discrimination is enormous, especially in low-income communities where people are routinely harassed for things like unpaid parking tickets and other minor violations. And in a country where people are arrested for their political views, the use of this technology quickly turns into a nightmare scenario.
The critical technology here is computer face recognition. Traditionally it has been pretty poor, but it’s slowly improving. A computer is now as good as a person. Already Google’s algorithms can accurately match child and adult photos of the same person, and Facebook has an algorithm that works by recognizing hair style, body shape, and body language - and works even when it can’t see faces. And while we humans are pretty much as good at this as we’re ever going to get, computers will continue to improve. Over the next years, they’ll continue to get more accurate, making better matches using even worse photos.
Matching photos with names also requires a database of identified photos, and we have plenty of those too. Driver’s license databases are a gold mine: all shot face forward, in good focus and even light, with accurate identity information attached to each photo. The enormous photo collections of social media and photo archiving sites are another. They contain photos of us from all sorts of angles and in all sorts of lighting conditions, and we helpfully do the identifying step for the companies by tagging ourselves and our friends. Maybe this data will appear on handheld screens. Maybe it’ll be automatically displayed on computer-enhanced glasses. Imagine salesclerks —or politicians —being able to scan a room and instantly see wealthy customers highlighted in green, or policemen seeing people with criminal records highlighted in red.
Science fiction writers have been exploring this future in both books and movies for decades. Ads followed people from billboard to billboard in the movie Minority Report. In John Scalzi’s recent novel Lock In, characters scan each other like the salesclerks I described above.
This is no longer fiction. High-tech billboards can target ads based on the gender of who’s standing in front of them. In 2011, researchers at Carnegie Mellon pointed a camera at a public area on campus and were able to match live video footage with a public database of tagged photos in real time. Already government and commercial authorities have set up facial recognition systems to identify and monitor people at sporting events, music festivals, and even churches. The Dubai police are working on integrating facial recognition into Google Glass, and more US local police forces are using the technology.
Facebook, Google, Twitter, and other companies with large databases of tagged photos know how valuable their archives are. They see all kinds of services powered by their technologies services they can sell to businesses like the stores you walk into and the governments you might interact with.
Other companies will spring up whose business models depend on capturing our images in public and selling them to whoever has use for them. If you think this is farfetched, consider a related technology that’s already far down that path: license-plate capture.
Today in the US there’s a massive but invisible industry that records the movements of cars around the country. Cameras mounted on cars and tow trucks capture license places along with date/time/location information, and companies use that data to find cars that are scheduled for repossession. One company, Vigilant Solutions, claims to collect 70 million scans in the US every month. The companies that engage in this business routinely share that data with the police, giving the police a steady stream of surveillance information on innocent people that they could not legally collect on their own. And the companies are already looking for other profit streams, selling that surveillance data to anyone else who thinks they have a need for it.
This could easily happen with face recognition. Finding bail jumpers could even be the initial driving force, just as finding cars to repossess was for license plate capture.
Already the FBI has a database of 52 million faces, and describes its integration of facial recognition software with that database as “fully operational.” In 2014, FBI Director James Comey told Congress that the database would not include photos of ordinary citizens, although the FBI’s own documents indicate otherwise. And just last month, we learned that the FBI is looking to buy a system that will collect facial images of anyone an officer stops on the street.
In 2013, Facebook had a quarter of a trillion user photos in its database. There’s currently a class-action lawsuit in Illinois alleging that the company has over a billion “face templates” of people, collected without their knowledge or consent.
Last year, the US Department of Commerce tried to prevail upon industry representatives and privacy organizations to write a voluntary code of conduct for companies using facial recognition technologies. After 16 months of negotiations, all of the consumer-focused privacy organizations pulled out of the process because industry representatives were unable to agree on any limitations on something as basic as nonconsensual facial recognition.
When we talk about surveillance, we tend to concentrate on the problems of data collection: CCTV cameras, tagged photos, purchasing habits, our writings on sites like Facebook and Twitter. We think much less about data analysis. But effective and pervasive surveillance is just as much about analysis. It’s sustained by a combination of cheap and ubiquitous cameras, tagged photo databases, commercial databases of our actions that reveal our habits and personalities, and —most of all —fast and accurate face recognition software.
Don’t expect to have access to this technology for yourself anytime soon. This is not facial recognition for all. It’s just for those who can either demand or pay for access to the required technologies —most importantly, the tagged photo databases. And while we can easily imagine how this might be misused in a totalitarian country, there are dangers in free societies as well. Without meaningful regulation, we’re moving into a world where governments and corporations will be able to identify people both in real time and backwards in time, remotely and in secret, without consent or recourse.
Despite protests from industry, we need to regulate this budding industry. We need limitations on how our images can be collected without our knowledge or consent, and on how they can be used. The technologies aren’t going away, and we can’t uninvent these capabilities. But we can ensure that they’re used ethically and responsibly, and not just as a mechanism to increase police and corporate power over us.
This essay previously appeared on Forbes.com.
New research can identify a person by reading their thermal signature in complete darkness and then matching it with ordinary photographs.
Research paper:
Abstract: Cross modal face matching between the thermal and visible spectrum is a much desired capability for night-time surveillance and security applications. Due to a very large modality gap, thermal-to-visible face recognition is one of the most challenging face matching problem. In this paper, we present an approach to bridge this modality gap by a significant margin. Our approach captures the highly non-linear relationship be- tween the two modalities by using a deep neural network. Our model attempts to learn a non-linear mapping from visible to thermal spectrum while preserving the identity in- formation. We show substantive performance improvement on a difficult thermal-visible face dataset. The presented approach improves the state-of-the-art by more than 10% in terms of Rank-1 identification and bridge the drop in performance due to the modality gap by more than 40%.
Facebook has developed a face-recognition system that works almost as well as the human brain:
Asked whether two unfamiliar photos of faces show the same person, a human being will get it right 97.53 percent of the time. New software developed by researchers at Facebook can score 97.25 percent on the same challenge, regardless of variations in lighting or whether the person in the picture is directly facing the camera.
Human brains are optimized for facial recognition, which makes this even more impressive.
This kind of technology will change video surveillance. Right now, it’s general, and identifying people is largely a forensic activity. This will make cameras part of an automated process for identifying people.
We’re in the middle of an epic battle for power in cyberspace. On one side are the traditional, organized, institutional powers such as governments and large multinational corporations. On the other are the distributed and nimble: grassroots movements, dissident groups, hackers, and criminals. Initially, the Internet empowered the second side. It gave them a place to coordinate and communicate efficiently, and made them seem unbeatable. But now, the more traditional institutional powers are winning, and winning big. How these two sides fare in the long term, and the fate of the rest of us who don’t fall into either group, is an open question—and one vitally important to the future of the Internet.
In the Internet’s early days, there was a lot of talk about its “natural laws”—how it would upend traditional power blocks, empower the masses, and spread freedom throughout the world. The international nature of the Internet circumvented national laws. Anonymity was easy. Censorship was impossible. Police were clueless about cybercrime. And bigger changes seemed inevitable. Digital cash would undermine national sovereignty. Citizen journalism would topple traditional media, corporate PR, and political parties. Easy digital copying would destroy the traditional movie and music industries. Web marketing would allow even the smallest companies to compete against corporate giants. It really would be a new world order.
This was a utopian vision, but some of it did come to pass. Internet marketing has transformed commerce. The entertainment industries have been transformed by things like MySpace and YouTube, and are now more open to outsiders. Mass media has changed dramatically, and some of the most influential people in the media have come from the blogging world. There are new ways to organize politically and run elections. Crowdfunding has made tens of thousands of projects possible to finance, and crowdsourcing made more types of projects possible. Facebook and Twitter really did help topple governments.
But that is just one side of the Internet’s disruptive character. The Internet has emboldened traditional power as well.
On the corporate side, power is consolidating, a result of two current trends in computing. First, the rise of cloud computing means that we no longer have control of our data. Our e-mail, photos, calendars, address books, messages, and documents are on servers belonging to Google, Apple, Microsoft, Facebook, and so on. And second, we are increasingly accessing our data using devices that we have much less control over: iPhones, iPads, Android phones, Kindles, ChromeBooks, and so on. Unlike traditional operating systems, those devices are controlled much more tightly by the vendors, who limit what software can run, what they can do, how they’re updated, and so on. Even Windows 8 and Apple’s Mountain Lion operating system are heading in the direction of more vendor control.
I have previously characterized this model of computing as “feudal.” Users pledge their allegiance to more powerful companies who, in turn, promise to protect them from both sysadmin duties and security threats. It’s a metaphor that’s rich in history and in fiction, and a model that’s increasingly permeating computing today.
Medieval feudalism was a hierarchical political system, with obligations in both directions. Lords offered protection, and vassals offered service. The lord-peasant relationship was similar, with a much greater power differential. It was a response to a dangerous world.
Feudal security consolidates power in the hands of the few. Internet companies, like lords before them, act in their own self-interest. They use their relationship with us to increase their profits, sometimes at our expense. They act arbitrarily. They make mistakes. They’re deliberately—and incidentally—changing social norms. Medieval feudalism gave the lords vast powers over the landless peasants; we’re seeing the same thing on the Internet.
It’s not all bad, of course. We, especially those of us who are not technical, like the convenience, redundancy, portability, automation, and shareability of vendor-managed devices. We like cloud backup. We like automatic updates. We like not having to deal with security ourselves. We like that Facebook just works—from any device, anywhere.
Government power is also increasing on the Internet. There is more government surveillance than ever before. There is more government censorship than ever before. There is more government propaganda, and an increasing number of governments are controlling what their users can and cannot do on the Internet. Totalitarian governments are embracing a growing “cyber sovereignty” movement to further consolidate their power. And the cyberwar arms race is on, pumping an enormous amount of money into cyber-weapons and consolidated cyber-defenses, further increasing government power.
In many cases, the interests of corporate and government powers are aligning. Both corporations and governments benefit from ubiquitous surveillance, and the NSA is using Google, Facebook, Verizon, and others to get access to data it couldn’t otherwise. The entertainment industry is looking to governments to enforce its antiquated business models. Commercial security equipment from companies like BlueCoat and Sophos is being used by oppressive governments to surveil and censor their citizens. The same facial recognition technology that Disney uses in its theme parks can also identify protesters in China and Occupy Wall Street activists in New York. Think of it as a public/private surveillance partnership.
What happened? How, in those early Internet years, did we get the future so wrong?
The truth is that technology magnifies power in general, but rates of adoption are different. The unorganized, the distributed, the marginal, the dissidents, the powerless, the criminal: they can make use of new technologies very quickly. And when those groups discovered the Internet, suddenly they had power. But later, when the already-powerful big institutions finally figured out how to harness the Internet, they had more power to magnify. That’s the difference: the distributed were more nimble and were faster to make use of their new power, while the institutional were slower but were able to use their power more effectively.
So while the Syrian dissidents used Facebook to organize, the Syrian government used Facebook to identify dissidents to arrest.
All isn’t lost for distributed power, though. For institutional power, the Internet is a change in degree, but for distributed power, it’s a qualitative one. The Internet gives decentralized groups—for the first time—the ability to coordinate. This can have incredible ramifications, as we saw in the SOPA/PIPA debate, Gezi, Brazil, and the rising use of crowdfunding. It can invert power dynamics, even in the presence of surveillance, censorship, and use control. But aside from political coordination, the Internet allows for social coordination as well—to unite, for example, ethnic diasporas, gender minorities, sufferers of rare diseases, and people with obscure interests.
This isn’t static: Technological advances continue to provide advantage to the nimble. I discussed this trend in my book Liars and Outliers. If you think of security as an arms race between attackers and defenders, any technological advance gives one side or the other a temporary advantage. But most of the time, a new technology benefits the nimble first. They are not hindered by bureaucracy—and sometimes not by laws or ethics, either. They can evolve faster.
We saw it with the Internet. As soon as the Internet started being used for commerce, a new breed of cybercriminal emerged, immediately able to take advantage of the new technology. It took police a decade to catch up. And we saw it on social media, as political dissidents made use of its organizational powers before totalitarian regimes did.
This delay is what I call a “security gap.” It’s greater when there’s more technology, and in times of rapid technological change. Basically, if there are more innovations to exploit, there will be more damage resulting from society’s inability to keep up with exploiters of all of them. And since our world is one in which there’s more technology than ever before, and a faster rate of technological change than ever before, we should expect to see a greater security gap than ever before. In other words, there will be an increasing time period during which nimble distributed powers can make use of new technologies before slow institutional powers can make better use of those technologies.
This is the battle: quick vs. strong. To return to medieval metaphors, you can think of a nimble distributed power—whether marginal, dissident, or criminal—as Robin Hood; and ponderous institutional powers—both government and corporate—as the feudal lords.
So who wins? Which type of power dominates in the coming decades?
Right now, it looks like traditional power. Ubiquitous surveillance means that it’s easier for the government to identify dissidents than it is for the dissidents to remain anonymous. Data monitoring means easier for the Great Firewall of China to block data than it is for people to circumvent it. The way we all use the Internet makes it much easier for the NSA to spy on everyone than it is for anyone to maintain privacy. And even though it is easy to circumvent digital copy protection, most users still can’t do it.
The problem is that leveraging Internet power requires technical expertise. Those with sufficient ability will be able to stay ahead of institutional powers. Whether it’s setting up your own e-mail server, effectively using encryption and anonymity tools, or breaking copy protection, there will always be technologies that can evade institutional powers. This is why cybercrime is still pervasive, even as police savvy increases; why technically capable whistleblowers can do so much damage; and why organizations like Anonymous are still a viable social and political force. Assuming technology continues to advance—and there’s no reason to believe it won’t—there will always be a security gap in which technically advanced Robin Hoods can operate.
Most people, though, are stuck in the middle. These are people who don’t have the technical ability to evade large governments and corporations, avoid the criminal and hacker groups who prey on us, or join any resistance or dissident movements. These are the people who accept default configuration options, arbitrary terms of service, NSA-installed back doors, and the occasional complete loss of their data. These are the people who get increasingly isolated as government and corporate power align. In the feudal world, these are the hapless peasants. And it’s even worse when the feudal lords—or any powers—fight each other. As anyone watching Game of Thrones knows, peasants get trampled when powers fight: when Facebook, Google, Apple, and Amazon fight it out in the market; when the US, EU, China, and Russia fight it out in geopolitics; or when it’s the US vs. “the terrorists” or China vs. its dissidents.
The abuse will only get worse as technology continues to advance. In the battle between institutional power and distributed power, more technology means more damage. We’ve already seen this: Cybercriminals can rob more people more quickly than criminals who have to physically visit everyone they rob. Digital pirates can make more copies of more things much more quickly than their analog forebears. And we’ll see it in the future: 3D printers mean that the computer restriction debate will soon involves guns, not movies. Big data will mean that more companies will be able to identify and track you more easily. It’s the same problem as the “weapons of mass destruction” fear: terrorists with nuclear or biological weapons can do a lot more damage than terrorists with conventional explosives. And by the same token, terrorists with large-scale cyberweapons can potentially do more damage than terrorists with those same bombs.
It’s a numbers game. Very broadly, because of the way humans behave as a species and as a society, every society is going to have a certain amount of crime. And there’s a particular crime rate society is willing to tolerate. With historically inefficient criminals, we were willing to live with some percentage of criminals in our society. As technology makes each individual criminal more powerful, the percentage we can tolerate decreases. Again, remember the “weapons of mass destruction” debate: As the amount of damage each individual terrorist can do increases, we need to do increasingly more to prevent even a single terrorist from succeeding.
The more destabilizing the technologies, the greater the rhetoric of fear, and the stronger institutional powers will get. This means increasingly repressive security measures, even if the security gap means that such measures become increasingly ineffective. And it will squeeze the peasants in the middle even more.
Without the protection of his own feudal lord, the peasant was subject to abuse both by criminals and other feudal lords. But both corporations and the government—and often the two in cahoots—are using their power to their own advantage, trampling on our rights in the process. And without the technical savvy to become Robin Hoods ourselves, we have no recourse but to submit to whatever the ruling institutional power wants.
So what happens as technology increases? Is a police state the only effective way to control distributed power and keep our society safe? Or do the fringe elements inevitably destroy society as technology increases their power? Probably neither doomsday scenario will come to pass, but figuring out a stable middle ground is hard. These questions are complicated, and dependent on future technological advances that we cannot predict. But they are primarily political questions, and any solutions will be political.
In the short term, we need more transparency and oversight. The more we know of what institutional powers are doing, the more we can trust that they are not abusing their authority. We have long known this to be true in government, but we have increasingly ignored it in our fear of terrorism and other modern threats. This is also true for corporate power. Unfortunately, market dynamics will not necessarily force corporations to be transparent; we need laws to do that. The same is true for decentralized power; transparency is how we’ll differentiate political dissidents from criminal organizations.
Oversight is also critically important, and is another long-understood mechanism for checking power. This can be a combination of things: courts that act as third-party advocates for the rule of law rather than rubber-stamp organizations, legislatures that understand the technologies and how they affect power balances, and vibrant public-sector press and watchdog groups that analyze and debate the actions of those wielding power.
Transparency and oversight give us the confidence to trust institutional powers to fight the bad side of distributed power, while still allowing the good side to flourish. For if we’re going to entrust our security to institutional powers, we need to know they will act in our interests and not abuse that power. Otherwise, democracy fails.
In the longer term, we need to work to reduce power differences. The key to all of this is access to data. On the Internet, data is power. To the extent the powerless have access to it, they gain in power. To the extent that the already powerful have access to it, they further consolidate their power. As we look to reducing power imbalances, we have to look at data: data privacy for individuals, mandatory disclosure laws for corporations, and open government laws.
Medieval feudalism evolved into a more balanced relationship in which lords had responsibilities as well as rights. Today’s Internet feudalism is both ad-hoc and one-sided. Those in power have a lot of rights, but increasingly few responsibilities or limits. We need to rebalance this relationship. In medieval Europe, the rise of the centralized state and the rule of law provided the stability that feudalism lacked. The Magna Carta first forced responsibilities on governments and put humans on the long road toward government by the people and for the people. In addition to re-reigning in government power, we need similar restrictions on corporate power: a new Magna Carta focused on the institutions that abuse power in the 21st century.
Today’s Internet is a fortuitous accident: a combination of an initial lack of commercial interests, government benign neglect, military requirements for survivability and resilience, and computer engineers building open systems that worked simply and easily.
We’re at the beginning of some critical debates about the future of the Internet: the proper role of law enforcement, the character of ubiquitous surveillance, the collection and retention of our entire life’s history, how automatic algorithms should judge us, government control over the Internet, cyberwar rules of engagement, national sovereignty on the Internet, limitations on the power of corporations over our data, the ramifications of information consumerism, and so on.
Data is the pollution problem of the information age. All computer processes produce it. It stays around. How we deal with it—how we reuse and recycle it, who has access to it, how we dispose of it, and what laws regulate it—is central to how the information age functions. And I believe that just as we look back at the early decades of the industrial age and wonder how society could ignore pollution in their rush to build an industrial world, our grandchildren will look back at us during these early decades of the information age and judge us on how we dealt with the rebalancing of power resulting from all this new data.
This won’t be an easy period for us as we try to work these issues out. Historically, no shift in power has ever been easy. Corporations have turned our personal data into an enormous revenue generator, and they’re not going to back down. Neither will governments, who have harnessed that same data for their own purposes. But we have a duty to tackle this problem.
I can’t tell you what the result will be. These are all complicated issues, and require meaningful debate, international cooperation, and innovative solutions. We need to decide on the proper balance between institutional and decentralized power, and how to build tools that amplify what is good in each while suppressing the bad.
This essay previously appeared in the Atlantic.
EDITED TO ADD (11/5): This essay has been translated into Danish.
Our government collects a lot of information about us. Tax records, legal records, license records, records of government services received—it’s all in databases that are increasingly linked and correlated. Still, there’s a lot of personal information the government can’t collect. Either they’re prohibited by law from asking without probable cause and a judicial order, or they simply have no cost-effective way to collect it. But the government has figured out how to get around the laws, and collect personal data that has been historically denied to them: ask corporate America for it.
It’s no secret that we’re monitored continuously on the Internet. Some of the company names you know, such as Google and Facebook. Others hide in the background as you move about the Internet. There are browser plugins that show you who is tracking you. One Atlantic editor found 105 companies tracking him during one 36-hour period. Add data from your cell phone (who you talk to, your location), your credit cards (what you buy, from whom you buy it), and the dozens of other times you interact with a computer daily, we live in a surveillance state beyond the dreams of Orwell.
It’s all corporate data, compiled and correlated, bought and sold. And increasingly, the government is doing the buying. Some of this is collected using National Security Letters (NSLs). These give the government the ability to demand an enormous amount of personal data about people for very speculative reasons, with neither probable cause nor judicial oversight. Data on these secretive orders is obviously scant, but we know that the FBI has issued hundreds of thousands of them in the past decade—for reasons that go far beyond terrorism.
NSLs aren’t the only way the government can get at corporate data. Sometimes they simply purchase it, just as any other company might. Sometimes they can get it for free, from corporations that want to stay on the government’s good side.
CISPA, a bill currently wending its way through Congress, codifies this sort of practice even further. If signed into law, CISPA will allow the government to collect all sorts of personal data from corporations, without any oversight at all, and will protect corporations from lawsuits based on their handing over that data. Without hyperbole, it’s been called the death of the 4th Amendment. Right now, it’s mainly the FBI and the NSA who are getting this data, but—all sorts of government agencies have administrative subpoena power.
Data on this scale has all sorts of applications. From finding tax cheaters by comparing data brokers’ estimates of income and net worth with what’s reported on tax returns, to compiling a list of gun owners from Web browsing habits, instant messaging conversations, and locations—did you have your iPhone turned on when you visited a gun store?—the possibilities are endless.
Government photograph databases form the basis of any police facial recognition system. They’re not very good today, but they’ll only get better. But the government no longer needs to collect photographs. Experiments demonstrate that the Facebook database of tagged photographs is surprisingly effective at identifying people. As more places follow Disney’s lead in fingerprinting people at its theme parks, the government will be able to use that to identify people as well.
In a few years, the whole notion of a government-issued ID will seem quaint. Among facial recognition, the unique signature from your smart phone, the RFID chips in your clothing and other items you own, and whatever new technologies that will broadcast your identity, no one will have to ask to see ID. When you walk into a store, they’ll already know who you are. When you interact with a policeman, she’ll already have your personal information displayed on her Internet-enabled glasses.
Soon, governments won’t have to bother collecting personal data. We’re willingly giving it to a vast network of for-profit data collectors, and they’re more than happy to pass it on to the government without our knowledge or consent.
This essay previously appeared on TheAtlantic.com.
EDITED TO ADD: This essay has been translated into French.
Sidebar photo of Bruce Schneier by Joe MacInnis.