Recognizing, Characterizing and 'Unsettling' Unintended Bias in the Faculty Search Process in Engineering - A Case Study

摘要

Faculty searches are one of the most critical activities undertaken with regards to shaping the future of a department, college or university. Despite the importance of this activity, most search committees are comprised of faculty who have very little time to commit to this task, and little if any training on 'best practices' or policies for conducting searches. National recognition of the need in faculty search processes for decision-makers to understand the prevalence of unintended biases and how to combat them has grown precipitously in recent years. Cognitive scientists have shown that many of the selection and evaluation processes we undertake on a daily basis are alarmingly contaminated, despite our good intentions. The term 'cognitive errors' has been coined to describe such errors in judgment. The objectivity of these evaluations is further compromised when we are overburdened and distracted. Common beliefs about how women and men, people of color and white people, act, feel, and express themselves often unintentionally enter into our decision-making processes. This is true even among people who eschew sexism and racism-because beliefs about gender and about race are part of the social norms of our society. Few of us stop to consider how taken-for-granted beliefs and expectations might be affecting our decisions. It is in this manner that gender and race biases commonly impact faculty search processes. In turn, engineering departments continue to struggle with hiring highly qualified women faculty. However, there are strategies to minimize the impact of unintended bias on faculty search results. In this paper, we discuss two examples of faculty search processes in which biases were demonstrated both in conversations and evaluations within search committees and in letters of recommendation for candidates. The extensive research on cognitive errors is used to provide a systematic analysis of these examples and approaches to minimizing the impact of unintended bias through promoting awareness are presented.