There are some tasks that artificial intelligence is really good at – and some that it’s not. And that has implications for the use of AI in trucking, from chatbots to autonomous trucks.
Stefan Seltz-Axmacher, who founded Starsky Robotics before it folded earlier this year due to lack of new capital, explained in an interview, “You and I are really impressed by computers, because computers can do stuff that we can’t do. I’d be quite surprised if you could, off the top of your head, tell me what the square root of 827,904.6 is. But your phone can do that super easily.
“On the other hand, because computers are so much better than us at a number of tasks that we find incredibly hard, we assume that it follows that they’ll be really good also at tasks that we find really easy. And the inverse is actually true. It’s a really hard robotics problem to make an arm that can pick up an object and hold it up. It’s a really hard and mostly unsolved robotics problem to do something that we’ve been doing since we were toddlers – to walk. It turns out that humans are really good at exactly the type of things that robots are really bad at.”
Ray Ghanbari, chief technology officer for SmartDrive, names four broad types of problems that AI is good at:
1. Classification or detection. A classic example here is computer vision. AI is good at figuring out if there’s a vehicle in front of you and if you’re in danger of colliding with it. It can detect when drivers are distracted based on things like head orientation and eye orientation.
2. Prediction. In trucking, AI is making its way into areas such as predictive maintenance, the ability to forecast rates, and predicting which drivers are more likely to quit or to crash.
3. Outlier detection. “AI is particularly good at identifying patterns of what is normal and not normal within very large data sets,” he explains. That’s why AI offers much more sophisticated alerts than those that are set to go off with basic thresholds, whether it’s a driver alert in the cab that he’s doing something potentially dangerous or an alert about something unexpected in the patterns of your business data.
4. Decisioning. “This is basically training an artificial intelligence algorithm to basically be an expert in a box – so if you were to hire a world-class expert on which safety events you should intercede in and coach, what would that expert tell you to focus your attention on?”
In a post on Medium, Patrick Poirier, co-founder of Humaniti, says, “We strongly believe that AI has an important role in augmenting humans, especially when humans and machines pair up, they can achieve more than either one separately.” However, Poirier explains that AI cannot automate jobs that involve:
- Conversational skills
- Making decisions without thousands of data points as a reference
- Making decisions while acknowledging their effect on the world
- Making decisions that require a general understanding of the world
“Judgment, common sense, and understanding are irreplaceable human traits as far as we know.”