The researchers then went on to identify two ways the public might be as inspired when robots carry out disaster relief tasks: Describe the robots as behaving more autonomously and/or describe the robots as facing high risk in achieving the results. The scenario used for this experiment was a Colorado wildfire described as “destroying nearly 1,000 homes and forcing tens of thousands of residents to evacuate” during which “firefighting robots worked for two days to control the blaze.”
Those study participants assigned to consider the robots autonomous also read text similar to, “With a built-in chip, the firefighting robots are highly autonomous and self-directed such that they can analyze a situation independently and freely choose which specific task to take on when extinguishing a fire.”
Those study participants assigned to consider the robots as exposed to high risk also read text similar to, “With a built-in chip, the firefighting robots are vulnerable to prolonged exposure to heat, such that the chip is at risk of burning up and the robot being permanently harmed.”
People reading either or both of those additional paragraphs showed greater prosociality than did people not reading either.
The researchers attribute this finding to the paragraphs conjuring up impressions of robotic courage and to courage in others inspiring our own socially conscious behavior. This explanation fits with the finding that people want to be able to easily tell whether the help they witness comes from a person or a robot, but once that’s done, they prefer an assistance-giving robot to resemble a human. This is particularly true regarding social intelligence of the robot, defined by researchers at University of Bristol and University of Bologna as the ability to perceive and mimic human emotions.
This definition came from the researchers’ statistically-supported cataloging of robotic intelligence. Verbal-linguistic intelligence allows a robot to accurately interpret information provided by the consumer and respond in readily understandable ways. Logic-mathematical intelligence is required for the robot to solve complex problems. If the robot will be moving through space, visual-spatial intelligence is essential. Processing-speed intelligence allows the robot to promptly complete repetitive tasks.
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