Robots can perform surgery, shampoo someone’s hair, read a mammogram and drive a car. A chatbot could probably write this article. Now that machines can do nearly everything humans do, the question is what effect they have on human motivation. Do they make our lives easier and more efficient, or will they make us lazy?
A study published in October 2023 in the journal Frontiers in Robotics and AI has an answer: A person who works alongside a robot is less likely to focus on details than when he or she works alone. Anyone who has worked in a team knows that one or two people usually carry the load while the others sit back and watch; researchers call this “social loafing." It turns out that people treat robots the same way. Remember the study groups in graduate school when only a couple of us did all of the work?
The study was led by Helene Cymek of the Technical University of Berlin, who has previously studied social loafing involving human partners. “When two pilots are in a cockpit monitoring the dashboard, they each reduce their effort. [Airlines require] two people because they want to increase safety. They call this the four-eye principle. But we found social loafing," Cymek said.
See: https://redskyalliance.org/xindustry/tesla-bots-are-you-ready
For the new study, her team recruited 44 volunteers to inspect electronic components for manufacturing errors such as bad welds or seams, a task that, in factories, is often performed by humans paired with robots. The volunteers were divided into two groups. One worked alone, while the other was told to double-check components that had already been inspected by a robot named “Panda.” People in that group were shown Panda an articulated arm with a visual sensor on the end on their way into the lab and heard it humming along as they worked.
But in fact, there was no robot at work. Both groups were deliberately given a set of components that included the same number of mistakes, so if the two groups were giving the same degree of attention to the task, their results should have been roughly the same. Instead, the researchers found that the humans working alone picked up an average of 4.2 out of 5 errors, while those who thought they were being assisted by a robot detected an average of 3.2 or 20% worse.
It is not a huge difference, but if you think about quality-control teams where humans and AIs work together on medical imaging or aircraft navigation, it is clear that the phenomenon of social loafing could potentially carry a high cost. Cymek notes, it is known that in mammography screening, it makes a difference if a radiologist is checking an image for the first time or double-checking someone else’s work: “If the person knows it has been checked first, they slack off."
This finding does not exactly boost my confidence in self-driving cars, even if there is a human at the wheel to take over in an emergency. “People take advantage of the support that is offered they are over-reliant on the system," Cymek said. “They look but do not see."
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