Do humans get lazier when robots help with tasks?

By Angharad Brewer Gillham, Frontiers science author

‘Social loafing’ is a phenomenon which occurs when members of a staff begin to put much less effort in as a result of they know others will cowl for them. Scientists investigating whether or not this occurs in groups which mix work by robots and people discovered that people finishing up high quality assurance duties noticed fewer errors once they had been instructed that robots had already checked a bit, suggesting they relied on the robots and paid much less consideration to the work.

Now that enhancements in know-how imply that some robots work alongside people, there may be proof that these people have realized to see them as team-mates — and teamwork can have detrimental in addition to optimistic results on folks’s efficiency. Folks typically loosen up, letting their colleagues do the work as an alternative. That is referred to as ‘social loafing’, and it’s frequent the place folks know their contribution gained’t be seen or they’ve acclimatized to a different staff member’s excessive efficiency. Scientists on the Technical College of Berlin investigated whether or not people social loaf once they work with robots.

“Teamwork is a combined blessing,” mentioned Dietlind Helene Cymek, first writer of the research 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,” said Onnasch. “In longer shifts, when tasks are routine and the working environment offers little performance monitoring and feedback, the loss of motivation tends to be much greater. In manufacturing in general, but especially in safety-related areas where double checking is common, this can have a negative impact on work outcomes.”

The scientists pointed out that their test has some limitations. While participants were told they were in a team with the robot and shown its work, they did not work directly with Panda. Additionally, social loafing is hard to simulate in the laboratory because participants know they are being watched.

“The main limitation is the laboratory setting,” Cymek explained. “To find out how big the problem of loss of motivation is in human-robot interaction, we need to go into the field and test our assumptions in real work environments, with skilled workers who routinely do their work in teams with robots.”

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