Statements like “I’m for diversity as long as we pick the best candidate for the job,” maybe based in an unconscious belief about who does this kind of work.  In reality, there can be multiple, equally acceptable definitions of “best”.  Listing the components of “best,” identifying some indicators of those components, and evaluating applicants on those indicators is useful.

Take time in evaluating candidates.  Research shows that unconscious bias has a more pronounced influence on decisions when time pressure or distractions exist.

Examine evaluating tools for biases.  Ensure that these tools clearly list relevant criteria – and only relevant criteria.

Requiring that all statements made about candidates be backed up by facts.

We would all like to think that we are objective and judge people based on their experience and achievements, but research has shown that we all bring a lifetime of experiences and cultural history that influences the evaluation process. It is important to note that in most of these studies, the gender of the evaluator was not significant, indicating that both men and women share and apply assumptions about gender.  

Take the status of the candidate into consideration when evaluating them; that is a newly graduated Ph.D. should not be judged against a post-doc candidate.

Be able to defend every decision for rejecting or retaining a candidate by asking committee members to back up their statements with evidence, not opinions.

Periodically evaluate your decisions and consider whether qualified women are included.  If not, consider whether evaluation biases and assumptions are influencing the decisions.  

As you begin to evaluate candidates, start to create a short list, which will provide several checkpoints at which you can make a considered decision about whether you are satisfied with the pool of candidates you have generated.

Develop a medium list from which to generate your short list.  Are there women or minority candidates on it?  

Evaluation bias is minimized if you interview more than one woman.  Research indicates that interviewers evaluate women more fairly when there is more than one woman in the interview pool.

Get consensus on the multiple criteria that will be used to choose candidates for interviews. Different criteria may produce different top candidates.

Consider creating separate short lists ranking people on difference criteria, such teaching,  research potential, collaborate potential and mentoring capacity.

Develop our final shortlist by taking the top candidates across different criteria.  

Evaluate this step before finalizing the list; consider whether evaluation bias may be affecting your choices