Facial recognition technology can do a lot more than just unlock your phone or tablet. Due to technological advances in artificial neural networks and an increase in global competition over the past five years, facial recognition technology is poised to revolutionize numerous industries, including policing, medicine, and agriculture. NewtonX recently conducted a qual-quant-qual survey with executives and influencers in the facial recognition space, including leading academics in computer vision labs at MIT and Stanford, executives at facial recognition startups in Europe and the U.S., and technologists at leading technology companies including Microsoft. The insights gleaned from this survey and its accompanying qualitative interviews informed the data and insights in this article.
The top 3 industries poised for disruption by facial recognition technology
While facial recognition technology is often described alongside a host of 1984-esque fears (many of them very valid), it also has economic applications that don’t involve government spying or racially biased algorithms. One such application is agriculture, a field where facial recognition technology has the propensity to optimize cattle care and beef/dairy production.
That said, the NewtonX survey indicated that policing already is, and will continue to be, a primary use case for facial recognition technology. Much of the technology’s use in policing is intentionally somewhat clandestine in the U.S., but in China there are already over 200M public surveillance cameras that are integrated with other data (such as smartphone location services), resulting in an integrated human monitoring system. Here’s how the technology has advanced, is being used, and is projected to be used in the top three use cases for it:
Facial Recognition Tech in Policing
New York City, Los Angeles, and Chicago are among numerous major U.S. cities that have developed somewhat secretive facial recognition programs (many of them in conjunction with technology giants such as Microsoft). These programs include access to public cameras — even ones owned by private businesses — and real-time body camera facial recognition technology, which could potentially be used to determine the danger level of a suspect during a confrontation. Additionally, they allow law enforcement to tap into databases (think: Facebook) that automatically label images and match faces to images of suspects.
The market for law enforcement facial recognition tools is large: NYC’s system was built by Microsoft; Amazon has sold its Rekognition software to numerous government agencies including ICE and police departments in Florida and Oregon; and IBM’s Intelligent Video Analytics 2.0, offers a body camera surveillance feature that automatically labels people by tags including skin color/ethnicity (the company has not disclosed its clients).
Currently, there is very little legislation on ethical usage of facial recognition technology. This has made top political watchdogs including the ACLU wary of its use for law enforcement. However, until new laws are drafted and adopted, cities can use the technology with very little oversight — and top tech companies can create the technology for them to do so.
Facial Recognition Tech in Agriculture
Facial recognition for livestock, in particular cows, has proved far easier than facial recognition for humans — and also comes with fewer ethical concerns. After all, a cow doesn’t care if you spy on it. Additionally, cows don’t obfuscate their appearance in any way, unlike humans who wear clothing, hats, sunglasses, and makeup that can confuse an AI facial recognition camera.
Not only is facial recognition technology easier to implement for livestock, it’s also highly useful. Cows tend to hide any signs of weakness from potential predators (including humans), meaning that often by the time a human notices an injury or sickness in the cow, it has endured the problem for far too long. However, a combination of cameras, computer vision, and predictive imaging can allow humans to spot and rectify problems right at their genesis.
These problems can also include aggression and interpersonal issues. All mammals fight, and often isolating aggressive groups from non aggressive groups does nothing to solve the problem, as the aggressors will either attack each other or grow depressed in isolation. Fights and depression have economic consequences. Companies such as Dublin-based Cainthus, which has teamed up with agriculture giant Cargill, offer solutions to such problems based on predictive analytics and computer vision. As global agriculture becomes increasingly competitive, services such as these will make or break competition.
Facial Recognition Tech in Medicine
Israeli-founded FDNA recently published a peer reviewed paper outlining how “DeepGestalt” deep-learning technology, a facial recognition analysis approach that highlights the facial phenotypes of hundreds of diseases and genetic variations, can achieve 91% accuracy in identifying the correct diagnosis of over 200 different genetic syndromes — often outperforming clinicians. The tool can enable earlier diagnosis and subsequent treatment, and will be of particular value to those living in remote locations where access to care and diagnosis is limited.
Additionally, facial recognition technology will become increasingly valuable for patient identity verification and for patient monitoring (such as verifying that a patient takes his/her pill daily). It’s likely that as Amazon, Apple, and other tech giants move into the healthcare spaces, they will employ the same technologies they’ve already perfectd to streamline the patient experience.
Who Will Win the Facial Recognition Market?
Facial recognition technology is proliferating across numerous multi-billion-dollar industries. As the applications for these industries mature, tech giants such as Apple, Facebook, and Google will be able to apply the technology they developed for consumers to enterprise use cases.