Artificial intelligence (AI) is rapidly affecting numerous industries, and many people are eager to see how it could improve their businesses and workflows. Applying this technology could help fleet owners manage routes and prioritize safety, but these decision-makers must be aware of common mistakes when using AI in trucking.
1. Failing to Hear Drivers’ Concerns
The trucking industry attracts many people who appreciate their independence and want to make a living outside the confines of a typical office job with near-constant oversight from bosses. Understanding that initial appeal makes it easy to understand why some drivers don’t like the idea of AI in trucking applications.
Some people with extensive experience in and knowledge of the logistics industry say many drivers see the change as an insult to the self-understanding and road knowledge they build up over years in their roles. Upset drivers may view high-tech, in-cab systems as tools to erase their livelihood rather than supplement it.
Any successful plans to rely on AI in trucking must recognize the real-world insights and skills drivers bring to their work. In-depth, respectful conversations with concerned drivers about what artificial intelligence can and cannot do should anyone who’s hesitant feel more open about the positive sides of implementing the technology.
Artificial intelligence excels at processing vast amounts of data, and many algorithms improve with use. Even the most aware drivers can’t feasibly notice everything happening in their environments. However, AI could fill the gaps, helping them feel well-equipped for anything.
2. Putting Too Much Trust in a Solution
AI gets a lot of hype, but there’s some well-deserved positive feedback mixed into it all. For example, one study of AI dashcams found a commercially available solution could notify drivers in 86% of cases involving potentially dangerous behind-the-wheel behaviors. The hazardous actions ranged from having cell phones in their laps to following other vehicles too closely.
However, as it becomes more common to see AI in trucking industry applications, interested persons must remember that no technology is perfect, and some products may misinterpret situations. One driver for a major e-commerce brand said his company used in-cab technology to determine bonus eligibility. However, he described numerous occasions where the product incorrectly attributed safety aspects to him that were beyond his control.
For example, the technology gave him an audible reminder to keep a safe distance when the issue was that other cars cut him off — which happened frequently along his routes. He found it discouraging to get that feedback after doing nothing wrong, especially since it made it more challenging to receive safe-driving incentives. Other drivers echoed his account, with many saying employers refused to let them contest what the technology concluded about their performance.
Anyone considering installing AI technology in truck cabs must realize that even the most advanced technologies won’t pick up everything, and some may give the wrong impressions. Refusing to meet with drivers who feel unhappy about how an in-cab product perceives them will quickly erode morale and may cause workers to look for positions elsewhere.
3. Reserving Too Many Resources for AI in Trucking
Some logistics industry leaders become fixated on artificial intelligence solutions for truck cabs, spending too much time and resources on those products while overlooking other necessities. The outcomes of such mindsets could overshadow many of the safety and efficiency benefits artificial intelligence can provide.
For example, worn tires can reduce fuel efficiency by up to 3%, highlighting the importance of tire tread monitoring. People should assess their company’s circumstances to see what percentage of their budget they can put toward AI without sacrificing the other essentials of running a trucking business.
Investments in artificial intelligence or other emerging technologies only make sense if the company can afford them without excessive financial strain. Many people applying AI in trucking do so to improve their maintenance processes. Algorithms can help them become aware of problems sooner, preventing costly downtime.
Choosing a goal-oriented approach will help people stay committed to using AI for well-defined reasons, such as to overcome known challenges. They should also investigate whether vendors offer monthly plans, allowing them to try artificial intelligence without committing to large upfront payments.
4. Overlooking the Importance of Privacy
Many trucking professionals appreciate road-facing cameras for the peace of mind they offer. The captured footage can show how traffic conditions or other drivers contribute to unwanted outcomes. Then, people in truck cabs can show they did everything right, but the situation still went badly. Such insights can be beneficial if another road user wants to sue a trucker for something that happened.
However, many industry professionals have a much different view of cameras aimed at drivers. One Utah-based owner-operator with three decades of driving experience said he would never install driver-facing models, even if an outside party mandated it. He explained that his truck is his home on the road, meaning the cab crosses professional boundaries and enters personal space.
A camera installed in a cab doesn’t just track what a driver does at work, but it shows what someone does to make the space more comfortable and pleasant. Others raise concerns about what happens to the collected data and who sees it. Will footage of drivers’ faces get permanently stored on distant servers, handled by strangers?
Some tech companies tackle these challenges by assuring potential customers they can turn off the cameras during non-driving time or that drivers’ faces get blurred by built-in features. Even if decision-makers are strongly interested in using these options, they must take drivers’ concerns seriously.
It’s especially important to do that if those considering using AI in trucking have not been behind the wheel for years — or ever. Such cases can make it difficult to understand drivers’ worries and why they may not want cameras trained on them at all times.
Carefully Choose When to Rely on AI in Trucking
Adding artificial intelligence to truck cabs can give people better oversight, allowing them to make confident, data-driven decisions. However, this technology has valid downsides, and people must weigh all those against the anticipated benefits. Considering the associated costs, driver feedback and other aspects will increase the chances of reaching well-informed decisions that will help their companies and lead to measurable outcomes.