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Facial Recognition Technology Will Change Your Life

Any celebrity can tell you that fame comes at a price. If millions of people know who you are and recognize your facial features, you can attract an awful lot of unwanted attention.

You may be thinking: “So? I’m not a celebrity, so this has nothing to do with me.”

Don’t be so sure about this. With recent advances in facial recognition tools, you too may suffer this aspect of fame. Yes, when you’re out of your house, complete strangers could recognize you and track your every move.

Much of this you bring on yourself. Consider, for example, your use of social media. You post what you eat, what TV shows you watch, where you meet your friends for drinks, and even what your pets are doing. All this personal information you post on platforms such as Facebook and Instagram means anyone who cares to look can easily find you with a browser search.

9/11 terrorists caught testing airport security months before attacks
Mohammed Atta (right) and Abdulaziz Alomari at a security checkpoint in Portland International Airport
September 10, 2001


As if this doesn’t leave you exposed enough, small, easily concealable cameras are nearly everywhere. Add a few minor tweaks to facial recognition technology which, when it becomes just a little cheaper and more readily available, will enable nearly anyone to follow nearly anyone else in real time.

Your privacy, then, could soon become extinct. Everything you do away from home- and when you do it- will be accessible to the world at large..

Related image
Tom Cruise as John Anderton in Minority Report sees a video ad that has been customized for him, and that calls him by name.

How did we get here?

Take a close look at the photo above. Here you see Mohammed Atta and Abdulaziz Alomari, two of the most import conspirators in the 9/11 terrorist attacks, passing through an airport security checkpoint. The next day, Atta and Alomari would hijack Flight 111 from Boston and fly it into the North Tower of the World Trade Center. They and their co-conspirators would murder 2,977 people.

To counter-terrorism professionals, this is one of the most disturbing of all 9/11-related images. It disturbs not for what it displays, but what it implies.

The photo demonstrates that law enforcement and intelligence professionals had the information to prevent the 9/11 atrocities. Atta and Alomari had been testing airport security systems for months, and were on federal watch lists. But airport cops couldn’t recognize and stop the pair, lacking the necessary facial recognition tools and image database.

Law enforcement and intelligence adopt FR

Following the 9/11 atrocity, the U.S government strove to make up for lost time. Security experts wanted advanced facial recognition tools- and fast. Electronics firms were happy to meet the new demand, and continually refined their cameras and algorithms to capture ever greater detail, nuance, and accuracy. Software engineers developed machine learning apps that could sift through gigantic image databases almost instantaneously, eliding over irrelevant photos.

Now the technology is nearly perfect. Chinese police recently used facial recognition tools to find a suspect in a dense crowd of 50,000 concert attendees. The PRC also uses the tools to catch jaywalkers and send them instant fine notifications.

Amazon, one of the leaders in the field, sells a real-time facial recognition system, called REKOGNITION, to police departments all over the U.S.

Commercial uses multiply

September 12, 2017 is another signature date in the history of facial recognition. On that date, Apple unveiled the iPhone X. Previous face-scanning phones could be spoofed easily with masks or video. The iPhone X could not. It was the first phone with a truly safe face-scanning security portal.

The success of the iPhone X has opened up other possible uses:

  • Automated tagging of individuals on Facebook and Instagram
  • Recognition of, and automatic adjustment of seat and steering wheel placement for, each authorized driver of a car driven by several people
  • Flagging of frequent hotel guests immediately on their entry into the lobby, so they can bypass the usual desk check-in, and their room doors will open automatically as they approach
  • Streamlining of airport security checks… Your face will be your boarding pass.
  • More convenient shopping… At an FR-enabled retail store, you simply walk in, pick up the goods you want to buy, and walk out. You never have to produce cash or swipe a card. The store automatically deducts the price of your purchases from your credit card.
  • Highly personalized advertising… As you pass a billboard, a kiosk, or a mall sign, it will display ads tailored to your known interests, and may even call you by name.

Don’t call any of this far-fetched. Some of these applications have been implemented already. Others are on the way, and will reach consumer markets shortly.

Can facial recognition threaten your privacy or safety?

FR Technology brings many benefits, but there may be a few drawbacks in it. It could become a serious threat to your privacy, or even your career or your safety.

In a future post, we will explore the dangers of FR technology in detail.

For the best deals in internet service, contact Satellite Country. We can help.

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Will Your Next Driver’s License Be Digital?

Your current driver’s license is a plastic card. Every previous license was a plastic card. So far as you know, your driver’s licenses will always be plastic cards that you’ll carry in your wallet or purse. They couldn’t take any other form, could they?

Man in a car showing his drivers license on his phone

This is about to change. Some states are planning to digitize your driver identity so you can display it on a mobile tablet or phone. The new licenses will feature biometric data absent from your current license, such as fingerprints, iris scans, and facial recognition. Iowa will lead the way, issuing digital driver’s licenses in 2019. Delaware, Virginia, and Wyoming are conducting limited pilot studies of  digital license technology. Other states have also begin to study the matter.

How will the changes affect you?

Idemia, a company seeking new functions for augmented reality, developed Iowa’s digital license program. Its CEO says the new licenses will be “dynamically connected”. This means they will update driver information in real time, so if your license is suspended or you just reached your 21st birthday, your digital license will be updated to display the information.

If your device is stolen, the thief can’t open your license. Unlocking it requires your biometric data. At the very least, it will require PIN or fingerprint authentication. Without your PIN or biometric data, the thief will never get your personal information.

Your digital license data will be synced with your state’s DMV database. If a cop pulls you over, he can send a message to your phone simply by scanning your license plate. Your response confirms your identity. The signals “shake hands”. The cop can relax when he approaches your car, because he knows who you are. You in turn can be sure he’s not an imposter, because only a real cop could send a signal to your device.

When will you get your first digital driver’s license?

It will be several years, at least, before most states issue digital driver’s licenses. One great hurdle is lack of interoperability, or coordination between state DMV databases. Police in one state will need access to DMV data from another state.

Expect a national interoperability standard to be settled by the middle of the next decade. After this, your driver’s license will exist in cyberspace.

 

(For all news related to the internet, watch this space. For the most reliable internet connection, talk to us. We can help.)

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TRAINING YOUR COMPUTER- LIKE A DOG

To most of us, computer coding is an inscrutable art. Code writers are the high priests of the Information Age, a technical elite whose work is so far beyond our understanding it seems to be magic. They even speak a different language.

This may be changing. With recent advances in artificial intelligence, your next computer might not need written software or OS code. Instead, you can look forward to training the machine- like a dog.

Conventional programming is writing of detailed, step-by-step instructions. Any errors or omissions in the code will affect the computer’s functions– and errors cannot be corrected without rewriting the code. Operating system developers, most notably Microsoft, often have to issue downloadable “patches” to repair defective code. Some systems, such as Windows 8, are so bloated and error-prone that they are beyond salvage, and have to be withdrawn from the market. The coding protocol is unforgiving. “Garbage in; garbage out”, is an industry watchword for a reason. The computer cannot learn, and cannot correct its mistakes. It can do only what the code has taught it to do.

With machine learning, your computer won’t be coded with a comprehensive set of instructions. It will be trained, and you very likely will have a big hand in training it. As Edward Monaghan wrote for Wired, “If you want to teach a neural network to recognize a cat, you don’t tell it to look for whiskers, ears, fur, and eyes. You simply show it thousands… of photos of cats, and eventually it works things out. If it keeps misclassifying foxes as cats, you don’t rewrite the code. You just keep coaching it.”

Machine learning has been with us, in concept, for several decades. It has become practical only recently, though, with revolutionary advances in the development of neural networks, systems modeled on the complex array of neurons in the brain. Machine learning already shapes much of our online activity. Skype Translator translates speech into different languages in real time. The collision-avoidance systems in self-driving cars are neural networks. So is the facial identification feature in Google Photos. Facebook’s algorithm for adjusting user news feeds is a neural network. Even Google’s world-dominating search engine, long a monument to the power of the human coder, has begun to depend heavily on machine learning. In February, Google signaled its commitment to it by replacing the veteran chief of its search engine with John Giannandrea, one of the world’s leading experts in neural networks and artificial intelligence.

Giannandrea hit the ground running. He has devoted Herculean effort to training Google’s engineers in machine learning. “By building these learning systems”, he said last fall, “we don’t have to write these rules anymore.”

Our increased reliance on neural networks will bring radical changes in the role and status of the programmer. The code writer understood precisely how the computer functioned, since he wrote every line of its instructions. It could do nothing he hadn’t told it to do. With machine learning, though, he’s not entirely sure how it performs its assigned tasks. His relationship with it is no longer that of a god exercising absolute rule over his creation; it’s more like the relationship between parent and child, or a dog owner and his dog. Such relationships always entail a certain amount of mystery.

Your computer’s training will not end with your purchase of it. You will teach it what functions you want, how you want them carried out, even the quirks in your personality. It will get continually ‘smarter’ as it adapts to your feedback. You will be training your computer for its entire operating life.

Danny Hillis, writing for The Journal of Design and Science, said, “Instead of being masters of our creations, we have learned to bargain with them, cajoling and guiding them in the general direction of our goals. We have built our own jungle- and it has a life of its own.”

(Training your computer will require a reliable internet connection. Is yours adequate? If it isn’t, talk to us. We can help.)