Recent research from the University of Portsmouth delves into the intriguing realm of self-serving biases and their influence on how we evaluate ourselves and others.
In a study involving 426 students, participants engaged in a computerized quiz followed by team-based tasks alongside either a human partner or a virtual robot. Feedback on performance was provided, and participants were then tasked with assessing both their own and their partner’s abilities.
Self-serving biases
The results revealed a notable trend: when paired with a human partner, participants displayed a tendency towards self-serving biases. They weighed positive feedback more heavily, leading to inflated confidence levels in their performance. Interestingly, this bias also translated into a reluctance to switch partners, even if potentially more skilled options were available.
Conversely, when paired with a virtual robot, participants exhibited a more balanced approach, considering both positive and negative feedback when assessing performance. This yielded more accurate self-assessments.
These findings have various practical implications, particularly in workplace settings, where insights into feedback mechanisms can enhance staff development and performance evaluation.
“The behavior observed in the controlled settings of a lab can manifest in various aspects of our lives, from academic group projects to professional teamwork,” the researchers explain.
“You might find yourself overestimating a colleague’s proficiency to justify delegating tasks, thereby avoiding the stress of extra work and the potential revelation of your own shortcomings.”
Work implications
Imagine you’re in a team project, eager to shine as the star player. The easy route might seem to be taking on most of the work yourself. But that comes with risks—you could end up overwhelmed or realize you’re not the flawless expert you believed.
Instead, our minds often take the simpler path by reassessing our partner’s abilities. When it comes to providing feedback and development chances for employees, this research advises caution against relying solely on team performance feedback.
“Our findings suggest that overconfident employees are in a way too content with their teammates and have little inclination to change teams,” the authors conclude.
“That means, where possible, organizations should deliberately re-shuffle their work teams from time to time, thereby allowing their employees to learn about their true strengths and weaknesses.”
“Overconfidence seems to be less of a problem when employees co-produce with a robot or an AI tool. In such situations, individuals exhibit a greater capacity to integrate performance feedback and gain insights into their genuine abilities.”
