Can a machine be used to observe a poker player’s facial expressions and predict a course of action using complex face recognition algorithms?
Companies such as Faception think so. This is an Israeli start-up with some very sophisticated facial recognition algorithms that are being applied in numerous industry verticals from security to public safety.
According to the company’s website,
“Faception can analyze faces from video streams (recorded and live), cameras, or online/offline databases, encode the faces in proprietary image descriptors and match an individual with various personality traits and types with a high level of accuracy.
We develop proprietary classifiers, each describing a certain personality type or trait such as an Extrovert, a person with High IQ, Professional Poker Player or a Terrorist.
Ultimately, we can score facial images on a set of classifiers and provide our clients with a better understanding of their customers, the people in front of them or in front of their cameras.”
Do you think it is ok for a company or government to use people’s faces as a way of tagging them with life-altering labels?
We have all read reports about Apple’s numerous acquisitions in the space of machine learning (Turi) , Artificial Intelligence and Facial recognition (Faceshift).
Contents
What is Apple up to when it comes to the application of Facial recognition?
As early as 2012, Apple started looking into the possible applications of facial recognition technology. One can get a sense of the developments by examining some of the patents published by Apple.
A patent filed in Q3 2012, Patent 20140050404 points to some of the thinking behind this application.
Digital images can be analyzed to identify certain features of interest in an image. For example, feature detectors may analyze an image to identify faces, people, pets, or other objects of interest.
The feature detectors identify certain regions of an image that exhibit properties of the feature that the detector is configured to identify. For example, a face detector may identify portions of an image having characteristic shapes, textures, or colors that are similar to the properties of known faces used to train the detector.
In 2013, Apple filed additional patents to improve the accuracy of its facial recognition algorithms. Much of the patents filed up until that point centered on processing images to define multiple characteristics.
In 2015, patent # 9189682, highlighted some of the thinking around application of this emerging technology.
According to the claim, Facial recognition algorithms may identify the faces of one or more people in a digital image.
Multiple types of communication may be available for the different people in the digital image.
An individual may have provided information for facial recognition of the individual to a service.
In Summary, the application’s objective was to identify contacts based on images and customize communication.
Some aspects of the application of these patents can be seen in the Memories feature in the new iOS 10. We haven’t yet seen any applications that center around facial recognition and associated communication.
The other application of facial recognition that Apple patented was centered on biometric identification. Instead of using the “Slide to Unlock” or “Raise to Wake” feature, the iPhone would scan your face and depending upon the image matching, would unlock the iPhone. This application was filed in 2011/2012 time frame.
If the possibility of using facial recognition as a means of unlocking a device has been around since 2011, why has Apple not implemented it in its iOS or OS X platforms?
Complex Privacy and Stakeholder Issues
Unlike Faception, the Israeli startup, Apple has many more stakeholders and has to take customer’s privacy into account. It is always trying to do a balancing act between features, security and privacy. If we have learnt anything in the recent past, it is that facial recognition and its applications are bound to stir up a lot of debate around privacy issues.
In this article from Fortune in May of this year, Jeff Roberts provided an excellent report of how the roll-out of facial recognition technology has been challenging and scary to a large degree.
“Australia is preparing a tool called “The Capability” that will give police the power to pick out faces from millions of photos, possibly including ones from Facebook.
Wal-Mart acknowledged to Fortune last year that it tested a trial program to screen for shoplifters (though later dropped it).”
As cool as facial recognition technology sounds, it will need to be balanced with Privacy and Security concerns before customers can adopt and use it in their daily lives.
In a world where headlines about hacking incidents have become ever so common, we wouldn’t want our private images to be “used” without our consent.
Video and images can always be manipulated. What is more terrifying is that facial expressions in videos can now be manipulated very easily with some simple facial recognition and mark-up software.
Below you can see a sample video of a company that specializes in facial image and expression manipulations.
https://youtu.be/Bb_EVB1rNBk
Apple’s Current Stance
This is probably one of the main reasons why Apple is treading carefully when it comes to using this technology in its platforms.
New to Photos on iOS is also the “People” album, housing all of a user’s images featuring people, grouped based on facial recognition. This new feature when showcased at the WWDC raised quite a few eyebrows.
Apple was however quick to clarify that all the new features in Photos are powered by the iPhone’s processor with all learning done on a device-by-device basis to ensure full privacy.
Apple made it clear that it does not see images or image metadata.
Despite this clarification, there were suggestions that Apple could be sued for using this feature since it could be interpreted as a violation of Biometric Information Privacy Act.
It was no coincidence that Apple brought in Aron Roth from UPENN, a famous security academic researcher to talk about Differential Privacy when it showcased some of the features at this year’s WWDC.
In Summary
Its still early and we are yet to see how new technologies such as Facial recognition get assimilated into how we use our electronic devices. Iris scanning feature in the Samsung Note 7 is just the tip of the iceberg when it comes to introducing recognition and biometric applications.
Systems on chips will need to become more scalable and powerful if most of the image processing is to occur on the local hardware in order to mitigate risks around privacy. A feature that is merely cool or has the latest technology adjective attached to it like AI or Facial Recognition need not be the most useful or welcomed feature from a customer’s perspective. It has to balance with other priorities from a stakeholder’s perspective.
Apple does walk the talk when it comes to customer’s privacy and security. We can all afford to wait a little longer for a cool technology if it has been vetted and thought through before it shows up on the next idevice.