Sean Andrist at the University of Wisconsin-Madison has been examining robots' use of social gaze, and has developed algorithms to help robots look at people at the right times and in the right ways.
Andrist notes extroverts tend to look at the people they are talking to significantly more than introverts do, and a humanoid robot can use this information to interact more effectively with humans.
Andrist sought to test whether matching the robot's personality to the user's personality would improve the user's subjective ratings of the robot's performance and/or enhance compliance with the robot's requests to engage in a task for a longer period of time.
Participants were told they would be completing the Tower of Hanoi puzzle under the supervision of the robot, and the robot would provide all the necessary instructions for the rules and for progressing through the various stages of the puzzle. The findings indicate participants complied more with robots that matched their personality.
On the measure of total participation time, both extroverts and introverts exhibited greater compliance with the personality-matching robot. However, when measuring total puzzles solved and total disks moved, only extroverts exhibited greater compliance with the personality-matching robot.
In future research, the goal will be to increase the granularity and sophistication of the gaze models and test more targeted populations who would likely benefit most from robotic assistance.
From IEEE Spectrum
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