What Are Your Unconscious Biases?

What Are Your Unconscious Biases?

What Are Your Unconscious Biases?

From birth we begin social learning: babies imitate facial expressions, adults aspire to be like those ahead of them in their careers. This isn’t good for our science, we don’t want everyone to be the same, think in the same way, or take the same level of scientific risk in their experiments. We need to give conscious attention to improving the distribution and diversity in science in order to improve the quality of our science.

Implicit association tests (IATs) can reveal your unconscious attitudes and beliefs towards a variety of topics such as race, gender and age. At the end of September the Babraham Institute launched the LIBRA IAT. This test was specifically designed by Project Implicit for the LIBRA project and identifies your biases related to gender and STEM/art disciplines and gender and family/career.

On October 10th Femi Otitoju from Challenge Consultancy came to address unconscious bias at the institute. Femi provided a general seminar for all staff where she revealed what unconscious bias is and provided us with many every day examples. This was followed by a focussed discussion with group leaders, line managers and committee chairs to talk about what we can do to reduce the impact of our unconscious biases on recruitment, promotion and staff support at Babraham. By being consciously aware that these biases exist we can reduce their impact. The Royal Society have produced this video to help explain unconscious bias.

Nicolas LeNovere, Group Leader at Babraham attended the seminar. "As scientists, we strive to stick to relevant facts and correct for all known biases. What the IAT and the seminar showed me was that no-one, and in particular not me, was immune against unconscious biased, engraved in us during all our life by family, peers and society. I think unconscious biases are therefore potentially more damaging than conscious ones, since they are very hard to detect and to correct for. We must not underestimate the effort needed to infer their existence and minimise their impact."