The Risk of Working With Robots: How Humans Social Loaf With Automation

Saturday - October 21 2023, 01:40 UTC - 1 year ago

Scientists at the Technical University of Berlin investigated whether humans social loaf when they work with robots. After testing their hypothesis, they found that when humans work with robots, they unintentionally miss errors due to not paying as much attention when they assume the robot won't miss anything. This could have serious implications for professions where humans work with robots, such as healthcare.

Now that improvements in technology mean that some robots work alongside humans, there is evidence that those humans have learned to see them as team-mates—and teamwork can have negative as well as positive effects on people's performance.People sometimes relax, letting their colleagues do the work instead. This is called "social loafing," and it's common where people know their contribution won't be noticed or they've acclimatized to another team member's high performance. Scientists at the Technical University of Berlin investigated whether humans social loaf when they work with robots.

"Teamwork is a mixed blessing," said Dietlind Helene Cymek, first author of the study in Frontiers in Robotics and AI. "Working together can motivate people to perform well but it can also lead to a loss of motivation because the individual contribution is not as visible. We were interested in whether we could also find such motivational effects when the team partner is a robot." .

A helping hand .

The scientists tested their hypothesis using a simulated industrial defect-inspection task: looking at circuit boards for errors. The scientists provided images of circuit boards to 42 participants. The circuit boards were blurred, and the sharpened images could only be viewed by holding a mouse tool over them. This allowed the scientists to track participants' inspection of the board.

Half of the participants were told that they were working on circuit boards that had been inspected by a robot called Panda. Although these participants did not work directly with Panda, they had seen the robot and could hear it while they worked. After examining the boards for errors and marking them, all participants were asked to rate their own effort, how responsible for the task they felt, and how they performed.

Looking but not seeing .

At first sight, it looked as if the presence of Panda had made no difference—there was no statistically significant difference between the groups in terms of time spent inspecting the circuit boards and the area searched. Participants in both groups rated their feelings of responsibility for the task, effort expended, and performance similarly.

But when the scientists looked more closely at participants' error rates, they realized that the participants working with Panda were catching fewer defects later in the task, when they'd already seen that Panda had successfully flagged many errors. This could reflect a "looking but not seeing" effect, where people get used to relying on something and engage with it less mentally. Although the participants thought they were paying an equivalent amount of attention, subconsciously they assumed that Panda hadn't missed any defects.

"It is easy to track where a person is looking, but much harder to tell whether that visual information is being sufficiently processed at a mental level," said Dr. Linda Onnasch, senior author of the study.

Safety at risk? .

The authors warned that this could have safety implications. "In our experiment, the subjects worked on the task for about 90 minutes, and we already found that fewer quality errors were detected when they worked in a team—be it with a person or a robot," said Dr. Cymek.

Many professions, such as healthcare, require people to work with robots and automation, meaning that they could be at greater risk of making errors due to taking on responsibilities that are better done by others. To fix this, the authors suggest that people are properly informed about the roles in a team setting.