When it comes to trading driver privacy for road safety, how far is too far? A reported 1.35 million people die in car crashes each year, and fleet leaders are constantly looking for ways to utilize technology to improve road safety.
Bart Conry, VP of Sales & Marketing at TiNik Inc., reports, “Not only will the development of telematics continue to provide opportunities for improved safety performance of drivers, but this field also includes increased training for fleet managers. Understanding both opportunities will add value to those who manage that data.”
But uses for AI in the fleet management field go beyond telematics and reporting. The artificial intelligence behind solutions such as Clearview AI, for instance, may provide fleet managers with an innovative method to resolve the issue of behind-the-wheel safety…but at what cost?
Could AI be the solution to driver safety?
A whopping 71.4% of all freight tonnage is moved on U.S. highways. As more consumers order goods online through e-commerce and mobile commerce, final mile delivery drivers have had to work longer hours with more rigorous delivery schedules — especially in cases where consumers are promised next-day delivery. Amazon delivery drivers, for instance, deliver upward of 250 packages a day and are often undertrained for their high-stress positions. The results of this, in some cases, are catastrophic.
Fortunately, advancements in artificial intelligence have begun to alter the fleet management industry by evolving how fleet leaders monitor driver engagement. Brad Jacobs, Director of Fleet Consulting at Merchants Fleet, says that at the present moment, AI and facial recognition are primarily impacting how companies look at and manage safety. “Examples like Subaru’s Eyesight Driver Assist Technology, which now comes standard on all Foresters, can identify driver fatigue and distraction, indicating how facial recognition can be used as a tool to reduce accidents. This has been the primary use we’ve seen for AI in the industry.”
Some of the risky driver behaviors that can be picked up and reported by AI-enabled dash cams (like the Subaru version mentioned above) include driver yawning, mobile phone usage, drinking or eating, talking to fellow passengers instead of watching the road, and more.
Canadian lawsuit raises concerns over citizen privacy
One can’t talk about AI-enabled facial recognition without discussing citizen privacy. Clearview AI is a video facial recognition platform that instantly connects a person’s image to their online presence. The platform was designed to be used by law enforcement and can tell agencies using the platform who a person is, where their images have appeared, and even who they spend time with. Clearview’s AI-based platform scrapes the web for more than 3.9 billion public images off of social media without citizen consent and could reach more than 160,000 by 2028. Clearview was quietly rolled out at law enforcement agencies in the U.S. and Canada before legislation was put in place to regulate its usage.
Canadian authorities recently launched an investigation into law enforcement agencies using Clearview, stating concerns over potential misuse of the service. How this investigation is resolved will directly influence laws regarding the implementation of AI and facial recognition in adjacent industries — including the fleet management field. It stands to reason that, similar to IoT citizen privacy acts (such as GDPR), regulations around facial recognition will continue to evolve as the technology becomes more widely adopted.
Bannu Hurtig, Senior Consultant at Mercury Associates Inc., reports, “Very similar to telematics and in-cab cameras, there will be privacy-related concerns/questions with the use of AI for facial recognition in fleet management or even other applications. Organizations wanting to use AI for facial recognition will need to be compliant with governing privacy regulations as well as having privacy policies which are communicated openly with employees.”
While dashboard-mounted, AI-enabled cameras enable fleet managers to monitor driver behavior closely, they’re also a risky investment in light of ongoing regulatory debates around citizen privacy. Fleet managers would be best advised to take a wait-and-watch approach for the time being before making substantial investments into dashboard reporting cameras.
Underexplored side effect of implementing facial recognition
Shifting legislation around AI and facial recognition is one concern for fleet managers considering adopting the technology. Another equally pertinent concern is driver sentiment. After all, there’s a trucker shortage. The American Trucking Association reports that in 2018, the trucking industry was short roughly 60,800 drivers, and if the current trend holds, the driver shortage will reach 160,000 by 2028. As shipping volumes increase due to the growth of e-commerce and mobile commerce, the need for drivers is stronger than ever.
However, could facial recognition technology be a deterrent to new driver onboarding in a time when many fleet organizations are actively struggling to recruit new hires? No broad-base poll has been done on driver sentiment regarding dashboard cams. Yet in a time when citizen privacy is a hot-button issue, it stands to reason that some fleet drivers would resent being filmed and monitored while they make their deliveries. Fleet managers who are interested in implementing dashboard cams may first want to assess whether rolling out the technology poses a significant obstacle to driver retention and recruitment and, if so, to offer compensation that’s competitive enough to offset employees’ resistance to the technology.
Technology such as Clearview AI has yet to be rolled out at scale in the fleet management industry. Brad Jacobs says that while dashboard cam uses such as confirming driver identity and theft prevention may be possible in the future, he has not seen them implemented thus far.
“Ultimately, AI and face recognition platforms are another step on the road toward autonomous vehicles,” Jacobs reports. “Autonomous vehicles will have a tremendous impact on how we think of managing fleets, but the transition is being made incrementally.”
“Some of today’s safety features like automatic emergency braking, traffic jam assist, and seats that vibrate when a vehicle begins to drift out of the lane are all examples of how artificial intelligence has already changed how fleet managers think about and implement safety policies,” Jacobs adds. “As these features build on each other, more of the driver’s role behind the wheel will be automated.”
Source: https://www.fleetsolutions-digital.com
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