This blog post is the second in a series about facial recognition software in various forms of public and private means of transportation, as well as the greater public policy concerns of facial recognition tools. More posts about the relationship between transportation technology, FRS, and modern slavery will follow.

Volume II: Beginning to Think about Modern Slavery and Human Trafficking

This blog post is the next in our series about facial recognition software (FRS) in transportation technology. This time, we will begin considering whether facial recognition software can be a meaningful tool for combatting modern slavery and human trafficking. The two most pressing questions regarding this topic are: first, is FRS an impactful tool in combating slavery and trafficking and, second, what are the relevant slavery risks?

Before we begin to think about either of these questions, let’s think about what slavery and trafficking mean in the context of transportation technology. It is important to understand that there is disagreement among experts about the best working definitions of slavery and trafficking. The definitions we will use here are not absolute. When we use the term “modern slavery”, we are generally talking about the exploitation of humans for personal or financial gain using deceit, force, or abuse of a person’s vulnerability. Modern slavery could be in the production of our clothing, manufacturing of our cars, harvesting of our food, or in forced sex work, for example. Human trafficking, though often conflated with modern slavery, is defined by the United Nations as “transportation, transfer, harbouring or receipt of people through force, fraud or deception, with the aim of exploiting them for profit”.

Turning to the effectiveness of FRS, the short answer is that FRS has helped identify and rescue survivors of slavery and trafficking. There are tools such as Spotlight, which use image processing to scan missing persons’ photographs and search through databases of online sex ads. Spotlight is owned and operated by Thorn, which is an organization that seeks to use technology to promote safety. Thorn focuses primarily on combatting child sex trafficking and child pornography.

Spotlight has helped identify victims 60% faster than searches that do not include FRS and has identified over 17,000 missing children since 2016. The idea is that sex work is often advertised online, and Spotlight is able to match photographs of sex workers with photos in databases of missing persons to identify which ads include children. In the case of adults, such FRS services could identify people who may be participating against their will based on who has been reported missing.

Hypothetically, using FRS in different means of transportation could help identify missing persons more quickly because recognition could occur during transit rather than after a person has already been forced to perform labor or has been advertised for sex online. Additionally, as society moves towards automation, victims of modern slavery and human trafficking will have less and less contact with other humans during transportation who may have otherwise been able to identify a problem. Consequently, FRS could not only replace that safety net, but also do so more quickly and accurately. However, this hypothesis assumes many things about the technology, such as which database the FRS uses, how the images in that database are collected, the accuracy of the analysis, and the ability to intervene. 

Thorn has partnered with Amazon Rekognition to power Spotlight as it has become a tool for law enforcement agencies. Frankly, this partnership is the first consideration of our second question. Because the implementation of FRS in the transportation sector for this purpose is speculative at this point, it is important to consider the relevant risks to vulnerable communities.

This is where things get complicated. Amazon has a long history of serious allegations about abusing employees ranging from labor law violations at best to modern slavery at worst. These claims include factory and warehouse employees urinating in bottles during their shifts because they were discouraged (or even not permitted) to use the restroom. Reports also note at least one person dying of heat exhaustion and dehydration. 

Amazon’s alleged treatment of its employees is troubling because it creates a difficult dynamic; actors who have contributed positively to the fight against slavery and trafficking may also be participants in these egregious practices. Modern slavery and human trafficking are so prominent that an estimated 40 million people are currently enslaved, and almost every individual consumes goods or services produced by slave labor. Each of us has a slavery footprintbecause many companies upon which we rely have slavery somewhere in their supply chain. But what does all of this mean for the impact and risks associated with facial recognition in vehicles?

Truthfully, upticks in slavery have been deeply correlated with every major transportation innovation from roads to ships to rubber tiresVolkswagenPorscheGeneral MotorsMercedes-Bens, and BMW each capitalized on the Holocaust by producing wartime material for Nazi Germany or utilizing forced labor from concentration camps. These are concepts that will be explored further in later blogs. For now, the important question is what does the dark history of these companies have to do with using FRS in different modes of transportation?

Well, put simply, FRS in various modes of transportation could be a great tool to combat modern slavery and human trafficking, but there will be obstacles related to public opinion, the right to privacy, technology racism, agency rulemaking, and legislative drafting. Relatedly, the issue of unethical labor practices by technology and car companies may leave a poor taste in the mouths of consumers who could be left wondering if investing in FRS is simply a public relations stunt when thousands of workers have historically been exploited at the hands of the very same companies. 

For this reason, transparency will be important from both private companies as well as municipalities interested in implementing FRS in public transportation. It is also important to note that most of the aforementioned companies have not only become more transparent about their role in the Holocaust, but also paid reparations (see thisVolkswagen example). 

This point is important because by pointing out this complicated dynamic of entities that have facilitated and now want to combat slavery and trafficking, we are not embarking on a witch hunt to find hypocrites, but rather shedding light on the very complicated web of how modern slavery that has touched nearly every facet of society. Recognizing this relationship does not mean those entities cannot be part of the solution, but it does mean we must anticipate some standoffishness from the public, particularly affected communities, and should be used as something of a lesson about the potential role of the private sector in fostering a solution.

We will address potential legal avenues throughout this series, but one option is federal legislation. Federal human trafficking laws and regulations are nothing new in the United States and date back to The Mann Act of 1910 (which was problematic in its own right, but the beginning of this story nonetheless). The Victims of Trafficking and Violence Prevention Act (TVPA) has been reauthorized three times since it was originally passed in 2000, and was expanded upon in 2005 and 2008 in light of more available research, including technological advancements and the power of the internet era.

State and federal agencies could also regulate FRS as a tool to combat slavery and trafficking. Many federal agencies have invested in FRS studies for various purposes, including a Department of Transportation study on eye tracking to gauge the safety of commercial drivers, train conductors, and air traffic controllers. Interestingly, the Department of Transportation has also proudly led the Transportation Leaders Against Trafficking initiative for nearly a decade. The purpose of the initiative is to connect transportation and travel industry leaders to maximize the industry’s impact on trafficking through training, public outreach, funding, and pledges, meaning the relationship between executive agencies, legislatures, and industry is clear. All three are working to develop FRS, combat slavery and trafficking, and implement transportation technology; it is time for these seemingly unrelated initiatives to overlap.

This blog is merely here to introduce the complicated intersection between transportation technology, FRS, and modern slavery. Various perspectives and further analyses of the legal history and potential legal solutions will follow.

This blog post is the first in a series about facial recognition software in various forms of public and private means of transportation, as well as the greater public policy concerns of facial recognition tools.

Volume I: An Introduction

What is the point of facial recognition software in vehicles? For that matter, what is facial recognition software? We use it to unlock our iPhones and tag our loved ones in photos on social media, but facial recognition software can also serve a variety of functional purposes throughout society, such as identifying suspects of violent crime or survivors of modern slavery. One of the most sensational questions surrounding facial recognition software in vehicles is how we can protect individuals’ privacy.

Facial recognition software is a form of biometric security. It is used to determine people’s identity using their faces from photos, videos, or even real time. Put simply, a camera scans the face and, once the face is detected, the software begins to analyze the image. Analysis converts the image to data based on the person’s facial features; think of this as turning the face into a type of equation. The software then tries to find a match by comparing the face to images in a database.

Though the technology may make people uneasy, it is important to conceptualize that this technology has been public for a while. Mercedes-Benz first introduced the Mercedes-Benz User Experience (MBUX) at the beginning of 2018, which is considered one of the most comprehensive automaker-created infotainment centers to date. Among other features that enhance the driver experience, MBUX includes facial recognition that senses the driver’s fatigue or discomfort, in which case the system will change the music or climate control features to prevent falling asleep behind the wheel. 

MBUX also has a voice recognition feature called “Hey Mercedes”, which is very similar to the in-home listening devices such as Alexa and can help drivers dial a phone call or input a destination into the navigation system without removing their hands from the steering wheel. Jaguar Land Rover has been using facial recognition since 2019 to similarly read driver fatigue with the ultimate goal of implementing machine learning to track the driver’s alertness and patterns of discomfort. 

In addition to personal vehicles, facial recognition software may be used to monitor rideshare vehicles to offer a safer experience. Uber has already been using facial recognition to determine if drivers were wearing their masks throughout the pandemic. The Uber app previously used facial recognition to identify the driver before each ride began, and the mask verification was an extension of that feature. Experts have also talked extensively about the potential safety benefits of facial recognition on public transportation. Companies such as FaceFirst aim to use facial recognition on or around public transit to identify domestic terrorists, child abductors, missing persons, survivors of modern slavery and human trafficking, people on ‘Do Not Fly’ lists, and deter petty theft. 

All of this is to say that facial recognition software in vehicles may be used to create a safer and more comfortable transportation experience. But what are some potential concerns of facial recognition technology, and how do we reconcile those concerns with some of the potential benefits? 

It is impossible to explain the huge variety of concerns people have about introducing more facial recognition, but one major concern is data breaching. Clearview AI, for example, is a facial recognition software company that touts itself as “the world’s largest facial network”, which currently sells its product to law enforcement agencies to “generate high-quality investigative leads”. Last year, Clearview was breached by hackers who were able to obtain access to about 3 billion images (some of which were scraped from social media which is a distinct violation of most social media platforms’ terms of service). This instance has raised serious concerns about how individual’s photos are obtained, how the images are stored, and who has access to those images.

A second concern is racism. Tech racism is a very large topic that certainly deserves its own blog post. As an overview, it is important to note that facial surveillance is largely used by law enforcement agencies, which is already a dynamic loaded withracial bias. Joy Buolamwini and Timnit Gebru’s 2018 research concluded that facial recognition software misidentifies Black women approximately 35% of the time but only misidentified white men 0.8% of the time. A false match can result in a wrongful arrest, a wrongful conviction, or even violence. Moreover, facial recognition used by police rely on mugshots databases for identification, which exacerbates racist policing patterns of the past because Black people are the most likely to be arrested due to over-policing. Because Black people are disproportionately likely to have mugshots in existing databases, current facial recognition software being used by law enforcement is more likely to get a match for Black faces. Coupled with the fact that the software is less likely to correctly identify Black features, the disproportionately high number of Black mugshots in the databases ensures that Black people are matched more frequently with less accuracy. This could especially be a problem for instances of traffic stops and crowd control.

Finally, there are many unanswered constitutional questions about the right to privacy and freedom of assembly. A handful of police departments, including Pittsburg law enforcement, have used facial recognition software to scan crowds of protesters to identify who in the crowd has outstanding warrants and arrest them accordingly. On Last Week Tonight, John Oliver described this practice as “the most insidious way” to prevent people from exercising their First Amendment right to assemble freely. Moreover, there are countless privacy questions about facial recognition in public spaces, including rideshare services and public transit that remain unanswered. Ultimately, people may not want to be under surveillance when using public or private means of transportation for a variety of reasons, and public policy will have to reflect the balance to be had between intelligence and privacy.

The aforementioned uses and concerns are far too abundant to address in a single blog post. As such, this blog post will be the first in a series of pieces that consider the role of facial recognition software in transportation technology and how we can reconcile its incredible potential as a safety tool and the relevant civil rights issues. In this series, we will seek to parse out some of the nuances of facial recognition software in privately owned vehicles, rideshares, and public transportation to consider how to best implement the technology widely.