People become lazier when they work with robots

Researchers have conducted a new study to examine the impact the use of robots and artificial intelligence has on our work ethic. The results are surprising.

Will robots take over our jobs in the future? People have been dealing with this question and vision for decades. Intelligent machines are already being used in some industries. However, these are still dependent on humans. However, the topic of artificial intelligence has reignited the human-machine relationship.

In many places, intelligent algorithms are already doing some of our work for us. As part of a new study, researchers have therefore looked into the effects the use of robots has on our work ethic. Ultimately, robotics and artificial intelligence have both advantages and disadvantages.

What impact do robots have on people’s work ethic?

The research team at the Technical University in Berlin therefore put forward a thesis: Do we become lazier when we know that a robot can do our work? This principle is also known as “social loafing” and occurs when we work with a teammate who efficiently handles large portions of our work.

Then many of us like to sit back and concentrate on fewer tasks. For their research, the scientists showed 42 participants images of circuit boards and asked them to identify defects. These were blurry and could only be sharpened using a software magnifying glass. This enabled the researchers to understand how the participants proceeded.

Subjective feeling is similar – results are different

Half of the participants were informed that a robot named Panda had already checked the images. They were able to see and hear the robot beforehand. After the exercise, the researchers asked all participants how difficult the task was and how responsible they felt for the results.

As a result, both groups performed almost identically. But when the researchers looked at the details, the robot group found significantly fewer errors. They already seemed to rely on the machine’s preliminary testing. The researchers therefore warn that errors can be overlooked when a machine helps us.

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