Better Science by Beating Back Bias

Better Science by Beating Back Bias T he human mind takes shortcuts by using past experiences to fill in missing information.This special talent helped our forebears avoid unfamiliar dangers and facilitated the development of modern civilization.Today, it allows us to quickly size up new social situations and connect with complete strangers.As researchers, it helps us see patterns in nature that explain how the world works.But this inherently human characteristic has its flaws.In its most benign manifestation, our reliance on shortcuts makes us susceptible to optical illusions or a magician's slight of hand.More troubling is our tendency to fill in missing facts by making broad generalizations that can lead us to draw erroneous conclusions about our fellow researchers and the quality of their work.The idea that our lazy minds and the ways that we are socialized can cause us to draw unjustified conclusions, a concept known as implicit bias, calls into question the integrity of the peer review process.After all, if one of the main pillars of modern science is affected by preconceived notions, how can we be sure that we are publishing the most reliable and important research?Upon learning about implicit bias in the peer review process, most of us assume that we are not the culprits.But just as we can be tricked by a skilled magician, all of us are susceptible to implicit bias in the peer review process.Implicit bias can creep into every stage of the review process, causing us to misjudge research abilities and quality due to assumptions associated with gender, country of origin, and the academic reputation (earned or presumed) of our authors and reviewers.Through our experiences as faculty members at institutions that take diversity seriously, our years as members of diverse research teams, and our personal commitments to diversity, we thought that we were truly objective when we served as authors, peer reviewers, and editors.But a simple exercise that forces you to confront your implicit biases about students and peers, coupled with statistics about the review process in a journal in a closely related field, leads us to question this notion.In 2017, Lerbeck and Hanson analyzed the gender of reviewers of the 20 peer-reviewed journals published by the American Geophysical Union (AGU).They found that both men and women authors suggested fewer women reviewers than expected on the basis of AGU membership or prior authorship (i.e., 28% of AGU members and 27% of first authors are women compared to 21% and 15% of the reviewers suggested by women and men, respectively).AGU editors also invited fewer women to serve as peer reviewers than expected (22% and 17% of the invited reviewers by female and male editors, respectively, were women).In addition, even though AGU-accepted authors (both female and male) reside in roughly equal parts North America, Europe, and Asia, AGU reviewers came primarily from the United States, Canada, and Europe, suggesting geographic bias.The existence of the AGU data set was fortuitous because the computer system that their journals used made it feasible to assess potential bias.Although we have not repeated this

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