Editorial: Minimizing Workplace Bias-What Surgeons, Scientists, and Their Organizations Can Do.

For clinicians and scientists, managing bias in the studies we design, conduct, and read is a topic that we deal with all the time. Perhaps because of this, we may imagine that we are less prone to carrying normal human biases into our places of work, and that we know how to handle it during interactions with our peers, staff, and patients. Indeed, much progress has been made in addressing overt or explicit bias in the workplace. And although it’s by no means fully behind us, gone are the days of “Want Ads” stating “only men need apply” or women being fired (explicitly) because they became pregnant. Unfortunately, there is ample evidence that explicit, and also unconscious (or more broadly, implicit) biases still exist in the doctor’s office, the hallways of hospitals, and the laboratory, and that these biases harm patients, providers, and scientists [8, 9, 11]. Both individuals and institutions have important roles to play to minimize bias and achieve fairer healthcare systems and workplaces. Explicit biases are easily understood as overt prejudices and attitudes about a group that an individual realizes (s)he holds; overt racism or misogyny are examples of explicit bias [14]. Unconscious and implicit biases are more subtle. Unconscious biases are associations or deeply held beliefs that drive our attitudes and behavior, even though at a conscious level we are not aware of them [4, 12]. Unconscious bias often develops early in life and can be reinforced by repeated social stereotypes; the persistent (and incorrect) idea that girls are biologically inferior at math or that Asian people are good at it are examples of unconscious bias [2, 10, 12]. Implicit bias is closely related to unconscious bias, but more broadly captures the notion that even when we recognize and understand on an intellectual level that a deeply held belief is inaccurate or false, it may still be hard to control its effect on our behavior. To carry the same example a bit further, an implicit bias would be demonstrated if an employer were to make a hiring decision predicated on the false belief that girls (and thus, women) are not good at math, despite being provided with evidence to the contrary [2] (Table 1). Certainly, we all have seen studies where identical resumes in science, engineering, or mathematics were evaluated either as though they were submitted by a man or a woman (only the names were changed), and even though everything else about them was identical, those that appeared to have been submitted by a man were rated more favorably and were more likely to be hired than those apparently submitted by a woman. It’s likely that both unconscious and implicit biases were at work in those studies; it may not be easy (or even possible) in some cases to separate their effects. It’s important to understand that implicit bias is pervasive, variable, and normal [1]. We all hold implicit biases. To better understand how deeply embedded implicit biases can be within us, take one (or more) of the Harvard Implicit Association tests (IATs) (https:// implicit.harvard.edu/implicit/takeatest. html). These tests cover a sobering range of topics, including Sexuality, Race, Age, Religion, Skin-Tone, Weight, Gender-Career, and Disability. The IATs can be a useful means by which to The author certifies that neither she, nor any members of her immediate family, have any commercial associations (such as consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article. The opinions expressed are those of the writer, and do not reflect the opinion or policy of CORR or The Association of Bone and Joint Surgeons.