{"id":12012,"date":"2021-03-21T08:04:52","date_gmt":"2021-03-21T02:34:52","guid":{"rendered":"https:\/\/www.allerin.com\/blog\/?p=12012"},"modified":"2021-03-19T08:07:38","modified_gmt":"2021-03-19T02:37:38","slug":"4-recruiter-biases-that-cost-organizations","status":"publish","type":"post","link":"https:\/\/www.allerin.com\/blog\/4-recruiter-biases-that-cost-organizations\/","title":{"rendered":"4 recruiter biases that cost organizations"},"content":{"rendered":"

\"hiring<\/a><\/p>\n

We come across various lawsuits against companies for discrimination in the hiring process. In November 2012, Alliant Techsystems Inc., an aerospace and defense manufacturing company, paid $100,000 to the EEOC lawsuit because of race discrimination<\/a> in its hiring process. Recently a long-running lawsuit against Google claiming age discrimination was settled for $11 million<\/a>. Governments create employment discrimination laws to avoid hiring biases. For instance, Title VII, the Americans with Disabilities Act of 1990, the Rehabilitation Act of 1973, and the Equal Pay Act are some of the employment discrimination laws in the USA<\/a>. Similarly, the Employment Equity Act<\/a> in Canada, the Equality Act 2010<\/a> in the UK, and the Employment Act<\/a> in Singapore are some examples of anti-job discrimination laws.<\/p>\n

<\/h4>\n

When a bias is challenged with the help of anti-job discrimination laws, it costs a fortune to organizations. But even if not challenged, hiring biases can directly impact businesses. For instance, a McKinsey report shows that companies in the top quartile with gender diversity in their executive teams are 21% more likely to earn above-average profits<\/a>. Hence, it is important for recruiters to identify such biases and avoid them while hiring.<\/p>\n

Hiring biases that can cost you a fortune<\/h2>\n

Various conscious and unconscious biases can influence wrong hiring decisions that can result in employment discrimination and lead to additional costs for businesses.<\/p>\n

\"hiring<\/a><\/h3>\n

Confirmation bias<\/h3>\n

Confirmation bias occurs when a recruiter creates a hypothesis and then tries to find and focus only on the information that proves it — for instance, creating a hypothesis that a candidate is intelligent and then looking only at the grades to prove it while ignoring skills. Another example can be when recruiters look at the degree or institute where a candidate has taken education to arrive at the conclusion that he or she would be very intellectual. Confirmation bias can be positive or negative.<\/p>\n

Expectation anchor<\/h3>\n

Anchoring is a psychological term used to describe the human tendency to make decisions based on a single anchor or trait. Expectation anchor bias in recruitment is like favoring a single candidate and putting others at a disadvantage. For example, a recruiter gets convinced that a candidate is the best fit for a job opportunity, while still conducting interviews.<\/p>\n

Affinity bias<\/h3>\n

Affinity bias is influenced by human nature to be surrounded by similar or likable people. As a result of affinity bias, recruiters make decisions based on similar traits with a candidate. For example, recruiters will become partial towards candidates who went to the same college, have spent their childhood in the same place, or have similar behavior.<\/p>\n

Effective heuristic<\/h3>\n

The effective heuristic is making quick decisions about a candidate based on superficial factors while completely ignoring the capabilities of that person to perform the job. It can be influenced by various factors, such as:<\/p>\n

Sexuality: <\/strong>LGBTQ+ candidates face biases in the recruitment process and are often sidestepped for vacancies due to recruiter biases.<\/p>\n

<\/h4>\n

Race: <\/strong>Recruiters can get influenced by candidates\u2019 physical characteristics and get into racial bias while hiring. For instance, they can hire candidates based on their skin, hair, or eye color.<\/p>\n

<\/h4>\n

Ethnicity: <\/strong>Recruiters might get biased based on the cultural background or religion of candidates. For instance, the lawsuit against Alliant Techsystems that we discussed earlier in this article was based on ethnic discrimination. The company didn\u2019t want to hire an African-American woman.<\/p>\n

<\/h4>\n

Disabilities: <\/strong>Physical disabilities or even medical history cannot stop a candidate from being considered for a job. Recruiters often consider not hiring an unhealthy employee, thinking that the person might require a lot of sick leaves. Another example can be when a recruiter states that all candidates must have a driving license. This puts physically disabled candidates at a disadvantage.<\/p>\n

<\/h4>\n

There are various other hiring biases along with the ones mentioned in this article that can cost organizations heavily if challenged. It makes obvious sense, then, that businesses should consider avoiding such hiring biases. But the fact of the matter is that it is hard to avoid some unconscious biases as recruiters might not even be aware that they are making biased decisions. Businesses can solve problems caused due to hiring biases with the help of AI-based recruitment intelligence tools. Recruitment Intelligence makes decisions based on the training and input data and assists recruiters in hiring without the baggage of bias. Contact Allerin<\/a> to know how you can avoid discrimination and biases in your hiring process and increase profitability with the right candidates in your team.<\/p>\n","protected":false},"excerpt":{"rendered":"

We come across various lawsuits against companies for discrimination in the hiring process. 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