PETER IS THE AUTHOR OF THE BOOK, "TO BOLDLY GO: A PRACTICAL CAREER GUIDE FOR SCIENTISTS" 
PREVIOUS COLUMNS 
Are you a prejudiced person? Most of us would emphatically answer "no!" Yet, most self-aware individuals would admit that their upbringing, education, and experience have given them a set of perspectives that may bias their actions and decisions. As scientists, we pride ourselves on our ability to rise above this tendency and dispassionately analyze data, free from any subjective bias. And, relative to those in most other professions, I think we do a very good job. However, there is one area in which biases abound, for both scientists and everyone else: biases toward people. And nowhere is this more prominently displayed than in a job search.
Consider the negative and positive biases that exist concerning Ph.D.s. Most nonscientists have a very strong image of what Ph.D.s are like. Sure, they think we are super-smart, but they also think we are aloof, cold, geeky, stubborn, and poor as team players! We in science harbor biases just as negative about people in the outside world. We think people in business or law are venal, self-serving, greedy, and unprincipled. No wonder Ph.D.s have difficulty making transitions to nonscience careers.
Why Do We Have Biases?
From an evolutionary standpoint, biases make perfect sense. Biases arise because of our use of heuristics, or rules of thumb, to govern much of our daily decision-making. Heuristics simplify decision-making by providing us with tried-and-true recipes. Rather than reanalyzing things from first principals we use a shortcut; we use rules of thumb.
However, heuristics are biased by nature and can lead to biased decision making. For example, most people feel that traveling 400 miles in an airplane is riskier than driving 400 miles in a car. Why? Because we tend to judge the frequency of events by the availability of recall; extraordinary events appear more prominent and frequent in our mind than ordinary events. Other biases exist as well, including presumed associations and misconceptions of chance. In the workplace, these biases can result in substantial variations in who gets hired, promoted, and fired.
Biases in the Job Interview
As anyone who has been to one can tell you, the job interview is a highly subjective process. Interviewers often have a range of biases that dramatically affect their perceptions of individual job candidates:
The Primacy Effect. This is the effect associated with "the first impression." Psychologists have documented that interviewers' first impressions of a candidate play a powerful role in their subsequent assessment. It is difficult to control someone else's perception of you in an initial encounter. But it can help to glean some information about the person ahead of time and be prepared, relaxed, and confident.
The Contrast Effect. Often one's individual ranking is based on one's position relative to others in the group. If the interview pool consists of a number of outstanding candidates, it is extremely difficult for an average candidate to be picked as number one. But in a substandard pool, the average candidate stands out disproportionately.
The Halo Effect. Interviewers often cannot help associating success in one endeavor with an overall tendency for success in general. From a rational point of view, there is no reason to expect that a person who was, say, All-State Track Champion would be an excellent engineer, but many interviewers tend to be positively biased toward people successful in anything. This is an example of a bias that you may be able to work to your advantage. While it is not generally appropriate to put hobbies and outside activities in your resume, it is appropriate to describe honors and awards, even if they are nonprofessional in nature. By slipping in some of these "outstanding achievements" you may gain some of the Halo Effect in your interview.
The Similar-to-Me Effect. Research has clearly shown that interviewers and supervisors have an unconscious tendency to favor people who are physically and professionally similar to them. This is one of the factors that holds women and minorities back in the working world. Mentors often select protégés that are similar to themselves. And job interviewers tend to favor candidates who are like them. Since this is a hard bias to overcome in the interview setting, I advise people to be themselves but to look for any areas of potential overlap between them and their interviewers.
The Harshness/Leniency Bias. Some interviewers are generally amiable and lenient people. Others are critical and demanding. In each case, the bias toward harshness or leniency will tend to raise or lower the scores of all the people they interview. This is one reason that some organizations put job candidates through multiple interviews.
The Self-Fulfilling Prophesy Bias. Once interviewers have made an initial judgement about a candidate, they tend to look for evidence to support their conclusion. If they like you, they tend to interpret your responses more favorably than if their initial reaction is less favorable. This bias can also be acting even before you enter the room: if you are an interviewer's top candidate, he or she will look for actions and responses on your part that tend to confirm the initial judgment.
The Beauty Bias. Research in cognitive psychology (as well as a very famous 60 Minutes story) shows that job candidates who are more attractive physically have substantially higher odds of being hired. Unfair, but true. This is one reason career counselors recommend that interviewees try to look their absolute best. Though you can't control how your parents made you, you can control your clothes, hairstyle, make-up, and grooming. Use them to your greatest advantage.
Biases in Evaluation and Compensation
The biases listed above also operate in the workplace between employees and supervisors. In many cases the same strategies that apply when one is a job candidate also apply when one is an employee. However, employees are at an advantage because they have multiple opportunities to shape their supervisor's impressions of them. Some call this process "office politics." Maybe so, but few deny that those who are effective at it tend to rise faster and further than those who eschew it.
A final bias that can operate in the salary arena is the Anchoring Bias. This is the bias that causes supervisors to be influenced by initial and often incorrect estimates of salary levels for their employees. For example, a supervisor may be told that a starting engineer with a Ph.D. earns $55,000 on average. Even when given more precise data later, that supervisor seems to unconsciously factor the initial figure into subsequent decisions about salary. This can work either to one's disadvantage or advantage, depending on the degree and direction of the bias.
Fighting Negative Biases
By nature, biases are hard to combat directly. However, given a knowledge of the source and nature of biases in the workplace, a job candidate or new employee can use diligence and persistence to dull the negative biases he or she might face.
The first step is to understand the nature and source of the biases. Often people start with a set of biases because they are operating with heuristics and lack any contradictory data. By directly addressing workplace issues through your words and conduct, you can begin to change people's views about your performance and effectiveness. Remaining visible and seizing opportunities to make positive contributions to your workplace, will help you stand out and will begin to undermine any negative biases. Building your own network at work can also help you solidify a community of supporters who will speak on your behalf. Finally, politely but firmly challenging your supervisor when he or she displays acts of obvious bias can not only help to resolve situations quickly but also establish you as a potential leader.
Biases work both ways. You also probably harbor some unfair and unsubstantiated biases about people and professions. It is only fair that you too should strive to keep an open mind and challenge your own set of heuristics.