Dr. Chia-Jung Tsay (UCL School of Management) studies the psychological influences on decision making and interpersonal perception, and how expertise and biases affect professional selection and advancement. Dr. Tsay’s work has been published in leading academic journals and featured in media outlets including the BBC, Economist, Harvard Business Review, Nature, and NPR, and in television programs, radio stations, and newspapers across 48 countries. For us, she answered three questions regarding her latest work titled “Naturals and strivers: Preferences and beliefs about sources of achievement”.
“We sacrifice objective qualifications to hire the natural”.
Dr. Chia-Jung Tsay, UCL School of Management
How do you position your argument against the idea that hard work and perseverance are key to achieve success?
There’s a lot of great research out there that suggests that differences in achievement likely reflect deliberate effort and persistence, rather than only innate talent. So it’s interesting that we may have little awareness that we actually have a preference for the natural, and we even sacrifice objective qualifications to hire the natural – and yet it may well be the consistent and persevering individual who achieves more in the long run.
Why are we willing to give up better-qualified candidates in order to hire those believed to be naturals?
Delving into how/why the naturalness bias develops is of great interest for future research. One possibility is that we have a preference for potential over even demonstrated achievement. It is also possible that natural talent is attributed more to stable internal characteristics, and thus be perceived as an immutable, more authentic, and more certain path to success.
Your research suggests that our bias for natural talent is unconscious. How do you think this bias could be circumvented then, e.g. in recruiting?
Further work would be necessary to reveal more specific levers through which we may attenuate the effects of the naturalness bias. If the way in which this bias functions overlaps with those of more established biases, we may consider several possible solutions at the point of performance evaluation. These solutions might include ensuring more precise and tangible metrics of assessment, confronting evaluators with highly achieving exemplars of both naturalness and striving, allowing evaluators to have the time and cognitive resources to fully consider the metrics that are important and valued for actual performance, or simply filtering out any candidate application materials that reference sources of achievement.