Facial Recognition Software Facing Challenges And Seeing Some Success

Facial recognition systems are seeing pushback. The city of San Francisco has banned the use of face recognition software by city agencies; other cities are considering similar restrictions. An MIT scientist has challenged tech leaders after finding bias in image datasets; some have disputed the findings, but she is shining a light on permissions or lack of permissions around image collection practices. 

Image recognition research continues and is leading to some positive results.  A Pittsburgh company is achieving success with use of facial recognition to battle sex trafficking. AI researchers continue to improve recognition rates. 

Here is a snapshot update of a controversial area of AI today – facial recognition.

First, a success story: Marinus Analytics, a social impact startup in Pittsburgh, is using facial recognition technology to help authorities catch leaders of human trafficking rings. Early in 2012, Emily Kennedy wrote her undergraduate thesis at Carnegie Mellon University on the popularity of the Internet for human traffickers in the sex trade. In 2014, she co-founded Marinus to develop its technology and make it useful to authorities. 

As described in a recent account in the Pittsburgh Post-Gazette, the FBI in January took down a ring of sex trafficking operations in the US, Canada, and Australia. A federal grand jury in Oregon indicted six individuals alleged to have run an organization that illegally recruited women from China to engage in prosecution. The National Cyber-Forensics and Training Alliance of Oakland, which helps industry, academia and law enforcement mitigate cyber threats, assisted in the case. The FBI seized 500 web domains and shut them down.

Marinus Analytics claimed that it generated the original lead for this case with help from Traffic Jam, its facial recognition tool. The NCFTA did not confirm it but did note that working with the private sector can aid authorities. 

Marinus collected millions of publicly-available images from websites where prostitution services are advertised. These became the data points for its racial recognition platform using AI. The image of a missing person can be checked against the database for similarities or a match. The company says its Traffic Jam tool saves investigators time and has achieved an 88 percent success rate. 

Cara Jones, CEO of Marinus, stated, “The software connects and finds needles in the haystack. Through computer vision, we can connect content on these sites, based on the face or broader similarity in the background or foreground.”

The startup is funded by a grant of over $900,000 issued in 2017 from the National Science Foundation.  The grant supports Marinus in the development of its machine learning technology to provide law enforcement with real-time, easy to access information. The project is expected to end by Sept. 30 of this year. Marinus is cited as a case history on Amazon’s Recognition site.

Market Seen Nearing $10 Billion by 2022

The facial recognition market is expected to generate $9.6 billion in revenue by 2022, according to Allied Market Research, with growth exceeding 21% per year. Use in law enforcement is a primary driver, but facial recognition is also preferred over other biometric technologies such as voice recognition and fingerprint scanning, due to its non-contact process. 

The top three application areas for facial recognition are: law enforcement, health and marketing/retail. 

In the United States, half of states allow law enforcement to run searches against their databases of driver’s license and ID photos. The FBI has access to driver’s license photos of 18 states. Drones with cameras can be used to apply facial recognition to large areas during mass events.  

Facial recognition is tightly controlled in Europe and has had some success. In 2017, Gemalto supplied new automated control gates for Roissy Charles de Gaulle airport in Paris. The system was intended to evolve from fingerprint recognition to facial recognition. The man responsible for the 2016 Brussels terror attacks was said to be identified with FBI facial recognition software.