Federal regulation for face recognition technology?

Microsoft wants regulation of facial recognition technology to limit ‘abuse’ (CNN)

“Facial recognition — a computer’s ability to identify or verify people’s faces from a photo or through a camera — has been developing rapidly. Apple (AAPL), Google (GOOG), Amazon and Microsoft are among the big tech companies developing and selling such systems. The technology is being used across a range of industries, from private businesses like hotels and casinos, to social media and law enforcement.

Supporters say facial recognition software improves safety for companies and customers and can help police track police down criminals or find missing children. Civil rights groups warn it can infringe on privacy and allow for illegal surveillance and monitoring. There is also room for error, they argue, since the still-emerging technology can result in false identifications.”

The details of any such federal regulation will matter a lot. I believe three states have laws regulating face recognition technology today: Illinois, Texas, Washington. Illinois is reportedly considering revisions to its Biometric Privacy Law (BIPA) to limit its scope.

The US Congress will need to decide whether to continue to leave regulation of biometric systems to the States or that it’s time for federal action. We’ll definitely bee keeping a close eye on this.

Facial Recognition quickly ID’s mass shooting suspect

Capital Gazette shooting suspect was identified using face recognition technology (MIT Technology Review)

“After a man killed five members of the paper’s staff last week, authorities quickly apprehended a suspect. He did not have an ID on him, refused to cooperate with police, and couldn’t easily be recognized via his fingerprints, so they turned to face recognition software.”

India adding facial recognition to UID August 1

UIDAI delays introduction of face recognition facility for Aadhaar till August 1 (Hindustan Times)

“The authority in charge of the national identity system had earlier this year announced that it will include face recognition alongside iris or fingerprint scan as a means of verifying users, helping those who face issues in biometric authentication or have worn-out fingerprints…

It is aimed at helping people who face difficulty in biometric authentication due to old age, hardwork or worn-out fingerprints, to authenticate their identity for accessing services, benefits and subsidies.”

It has been a while since we last called attention to India’s UIDAI. Nevertheless, it is very exciting that India is adding facial recognition to its UID toolkit.

A few years ago we posted that in Odisha, a state in eastern India (2014 pop. 43.73 million), there were potentially 1 million true “errors,” or failed enrollments that are potentially valid and are described as those submitted on behalf of “very old people and children (between five to 10 years), whose finger prints and iris scans were not registered properly.”

Moreover, As of May 2015, across India, around 618,000 (0.07%) of UID numbers had been issued with biometric exceptions where UID numbers were issued to individuals who simply could not be enrolled using fingerprint or iris technology.

Adding facial recognition to the UID ecosystem should help bring more people into the system and reduce matching costs for all sorts of verification transactions for everyone due to the ubiquity of mobile cameras versus fingerprint and iris hardware.

Facial recognition seems to have a lot of market momentum at the moment, and because of the sheer size and scope of India’s UID efforts, everything they do produces a trove of data on large-scale biometric deployments.

Face, iris gaining ground in authentication applications

The future of biometric modalities in consumer electronics (Help Net Security)

“ABI Research posits that as ASPs for iris modules drop, and the once timid face recognition is continuously honed with more sophisticated machine learning algorithms, they will both slowly start to eat away at fingerprint implementations.”

There’s a lot of good information in the linked article. Fingerprint technology is still the most ubiquitous biometric technology worldwide and it will be for some time. Biometrics will ultimately be an all-of-the-above industry where the application determines the biometric modality/modalities brought to bear.

Orlando: Face recognition for biometric entry/exit

Facial recognition to identify all international passengers at Orlando airport (Business Traveller)

“Instead of handling paper documents, boarding passengers will queue in turnstile-like lanes, stepping onto yellow footprints and looking into a camera to have their face scanned. The scan will then be compared to images obtained from passports or other travel documents to confirm identity.”

The aspect of this program dealing with facial recognition for departing passengers is especially interesting. Airline gate agents probably aren’t trained to detect identity fraud to the degree that customs agents are. Their priority is to board the aircraft as efficiently as possible.

Recording the biometric transaction will also begin to provide rigorous data that may also inform efforts to meet the repeated US Congress requirements for biometric exit technology.

Much more information with pictures and video is available at the Orlando Sentinel.

Facing the future

In a post at Biometrics Update, Ever AI CEO Doug Aley makes the case that facial recognition technology is ready to reduce friction in identity authentication across a range of industries. It’s well worth reading in its entirety.

Is face recognition ready to make its mark? (Biometric Update)

“For as hard as the industry has tried, consider all of the potential security exposures that still exist. Four-digit ATM pin codes. Patient identities verified by Social Security numbers. Lost or stolen physical corporate ID badges. Just the other day, in creating a security profile someone asked me for my mother’s maiden name.

Face recognition technologies are poised to re-write the rules of how transactions and identities are secured. But are we ready?”

We’re ready. The challenge for organizations seeking to adopt facial recognition to improve services is integrating the technology with existing processes and data structures. Our FaceTrac/IdentiTrac platform provides both the facial recognition technology and the integration with existing databases and applications.

Facial Recognition System Helps Trace 3,000 Missing Children In 4 Days

The identities of the missing children have been established and efforts are on to help them reunite with their families. (NDTV – India)

“New Delhi: Nearly 3,000 missing children have been traced in four days, thanks to the facial recognition system (FRS) software that the Delhi Police is using on a trial basis to track down such children.

The identities of the missing children have been established and efforts are on to help them reunite with their families.

The Ministry of Women and Child Development (MWCD), in an affidavit to the high court, said that the Delhi Police, on a trial basis, used the FRS on 45,000 children living in different children’s homes. Of them, 2,930 children could be recognised between April 6 and April 10.”

A heartwarming story with a dose of local politics.

Amazon files mobile face recognition patent for payments

Amazon will soon accept mobile payments using selfies instead of passwords (Silicon Republic)

Amazon has filed a patent application for technology that will allow users to authenticate a payment using a photo or video in a seamless way that doesn’t necessarily require passwords.

“The user is identified using image information which is processed utilising facial recognition. The device verifies that the image information corresponds to a living human using one or more human-verification processes,” the patent reads.

Illinois: Google faces face-rec lawsuit

Google Gets Sued Over Face Recognition, Joining Facebook And Shutterfly In Battle Over Biometric Privacy In Illinois (IBTimes)

In the latest scuffle over biometric data collection in Illinois, Google Inc. this week was hit with a lawsuit over its face-recognition technology, making Google the latest tech giant to be accused of violating an unusual state privacy law that restricts the collection and storage of so-called faceprints. Illinois and Texas are the only two states that regulate how private companies may use biometric data, and Illinois is the only state that authorizes statutory damages for violations.

Face recognition in retail

Walmart’s Use of Sci-fi Tech To Spot Shoplifters Raises Privacy Questions (Fortune)

The only company that acknowledged using the software was Walmart. According to a spokesperson, the retailer tested facial recognition software in stores across several states for several months, but then discontinued the practice earlier this year.

“We were looking for a concrete business rationale … It didn’t have the ROI,” or return on investment, the spokesperson says.

Retailers and biometrics companies have been working together for years trying to figure out how to apply face recognition to the problem of shoplifting. As expected in a retail business, it all comes down to Return on Investment (ROI).

First, here’s what modern shoplifting looks like. It isn’t just teenagers pocketing lip-sticks and candy bars.

Police bust ‘amazing’ $15,000-a-day shoplifting ring (USA Today)

HAZEL PARK, Mich. — Police say a 7,600-square-foot warehouse served as the business hub for a sophisticated, multimillion-dollar theft ring that stole items from southeastern Michigan retailers and resold them on the Internet.

Veteran investigators said the shoplifting ring, which swiped as much as $15,000 a day in over-the-counter drugs and other goods from area stores, is the largest they have ever seen.

Oakland County Sheriff Michael Bouchard called the illegal business “amazing in size and scope” and one that likely operated for years before drug investigators spotted it last month.

The ring operators stored stolen items in the warehouse and sold them on the Internet through eBay, Amazon.com and other sites, investigators said.

Read the whole thing. Criminal organizations like these cause huge losses to retailers, higher prices to consumers, and increased production of dangerous street drugs. More and more, shoplifting is an organized crime problem, and everyone who isn’t in on the scam pays the price in one way or another.

Privacy issues associated with facial recognition in businesses open to the public get a lot of well-deserved attention. Clearly, facial recognition technology could be deployed in businesses open to the public in ways that are injurious to a reasonable person’s expectation of privacy. Brainstorming those ways, however, takes us pretty far away from the ROI calculation that is motivating retail outlets to seek out technologies that can help them reduce losses due to theft.

The privacy focus for facial recognition in retail spaces should be on what data is collected and what happens to it. In this case that means the photos and personal information that goes along with them. The easy part is that retail establishments have been collecting information on suspected shoplifters for a long time now and they already have policies about what they collect, when they collect it, and how long they retain it. The hard part is that new facial recognition technology makes sharing the information easier, securing it more difficult (and important!), and it requires new training for loss prevention staff about what, exactly, the technology is telling them.

That brings us back to the ROI. Obviously, using facial recognition to prevent a $15,000 organized crime heist helps the ROI calculation. Using facial recognition to interrupt a shopper based upon a “false positive” ID hurts the ROI calculation. So there’s at least a little bit of good news here for privacy: The ROI calculation that is so important to the business’s decision whether or not to use a facial recognition system does have a built-in way to account for at least some privacy concerns.

Positive review for Microsoft facial authentication on new hardware

Windows Hello facial logins on the new Surfaces are rather impressive (RAs Technica)

With Hello enabled, logging in to the machine is as simple as sitting down in front of it. The lock screen shows the Windows Hello “eye” looking around, and the detection is near-instantaneous. It takes longer for Windows to dismiss the lock screen and show the desktop than it does for it to recognize you in the first place. In fact, it’s so quick that a kind of delay had to be built in. If there were no delay, locking your PC with Windows+L (or the Start menu option) would be nigh impossible.

Australia funds national face recognition capability

Govt funds $18.5m Aussie facial recognition database (iTnews)

It will allow law enforcement agencies to share citizens’ facial images to identify unknown individuals and verify identities.

The ‘national facial biometric matching capability’ will match a facial photograph to images on passports, visas and driver’s licences, and will initially offer functionality to match the identities of known individuals. It will later be able to match unknown individuals, the AGD said last month.

It will be targeted towards identity theft, fraudulent identity documents and “other serious criminal activity”, AGD said.

Windows Hello face recognition not fooled by Australian twins

Microsoft’s facial recognition software does something amazing when it encounters twins (Business Insider)

Each set of twins set up an account for one and then the other attempted to log-in — and the software held. According to The Australian, there was not one instance of Windows Hello allowing the wrong twin access to the computer.

The headline to the contrary, notwithstanding, Microsoft’s facial recognition software pretty much does nothing when it encounters a legitimate user’s identical twin.

MasterCard announces two biometrics pilots

MasterCard puts faces and fingers under microscope (Mobile World Live)

MasterCard and First Tech Federal Credit Union, a US financial institution, will pilot the authentication of payments using facial and fingerprint recognition, in what they claim is a first for the country.

Separately, MasterCard is running another biometrics trial with International Card Services (ICS), the leading credit card provider in the Netherlands.

Kudos to Morpho

MorphoTrak Leads With Face Comparison Training (Financial Content)

MorphoTrak, a U.S. subsidiary of Morpho (Safran), announced today that it will offer vendor-independent training* in face comparison, filling an acknowledged gap in the field of computer-aided face recognition and facial identification. Automated face recognition systems are common in both law enforcement and civil applications, yet facial matching software can only present the reviewer with potential matches. It is up to the human reviewer to decide whether two facial images belong to the same individual.

*“Vendor-independent training” means that the techniques the course will teach work for all face examiners, no matter what face recognition software they are using.

Kudos to Morpho. Facial recognition is a powerful tool for well-trained users. This challenge is well known among those who have worked to place facial recognition capabilities into the hands of law enforcement and security professionals.

Computers don’t look at the world the way we do. Whether that’s a good thing or not depends on what you’re trying to accomplish. For facial recognition in a law enforcement context, it’s a good thing to have a radically different point of view applied to a challenge.

First, faces are probably the most meaningful objects in human existence. It’s not too much of an exaggeration to say that for millennia human survival has depended upon our abilities at one type of facial recognition: recognizing people you know. Sorting through hundreds of thousands of pictures of people we don’t know in order to match the two that are of the same person, however is not something we’re inherently good at.

Computers can do that in less than a second, then give the two pictures to a human which is very good at making the single comparison &#8212 if that person understands their role in the machine-human partnership well.

Training is the key.

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