How To Address Bias In The Workplace, And Why You Should

• Personal biases can lead to workplace discrimination and negatively impact company morale, innovation, and an organization’s ability to attract and retain talented employees. 
• Understanding and making plans to address implicit bias can make a big difference in creating an inclusive environment for underrepresented minorities.  
• Instead of simply lecturing employees, the best anti-bias training challenges them to visualize everyday scenarios and consider their actions, creating valuable self-awareness.

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Personal biases can lead to workplace discrimination and negatively impact company morale, innovation, and an organization’s ability to attract and retain talented employees. 

Many times, biases are implicit/unconscious. An implicit bias develops over the course of our lifetimes, and is embedded in our ways of thinking from our upbringing and culture.  

Unlike explicit bias (which refer to conscious forms of discrimination like intentionally not hiring someone because of their race, age, gender), implicit bias emerges involuntarily and without us even realizing it. 

In order to combat conscious or unconscious biases in the workplace, leaders need to ensure that employees as well as managers are properly trained to recognize bias.  

Understanding and making plans to address implicit bias can make a big difference in creating an inclusive environment for underrepresented minorities. Here are some steps that can be taken to address and combat bias in the workplace.  

Unconscious bias training

Addressing implicit bias requires that individuals work to identify their own biases and ways to overcome them. For work leaders, this means taking a hard look at your policies and practices and being honest about where and how those practices perpetuate bias. Workforce analytics can help, and so can unconscious bias training.  

Behavior-based training offers a way to uncover how employees may act when confronted with certain situations, such as interacting with people who are different from them, and teach them how to navigate and combat their unconscious biases to affect real change.  

Instead of simply lecturing employees, the best training challenges them to visualize everyday scenarios and consider their actions, creating valuable self-awareness.  

Addressing unconscious bias is a continual effort, not a once-a-year training course. 

Training leaders/managers as well as employees to navigate and avoid unconscious biases ensures they are prepared to put what they’ve learned into practice should a situation in the workplace ever arise. 

It’s especially important to ensure managers are being trained as well, as they play a key role in promoting employees, assessing their performance, and shaping their experience.  

If a manager has even the slightest implicit bias, their judgments and actions can have significant and long-lasting impacts on their employees’ careers. 

Measure your workplace’s bias quotient

Data from a variety of sources and channels can be collected to help organizations determine their bias quotient. This data includes: 

• Behavioral training data 
• Exit and stay interviews 
• Helpline reports 
• Demographics 
• Employee surveys 
• Hiring, promotion, and attrition data 
• Policy incidents and violations 

The goal of measuring and acting on your organization’s bias quotient is to strive for employee growth and continual improvement.  

Ultimately, employees should be trained to be better, more self-aware versions of themselves, which helps to lead a workplace culture in which everyone feels respected and heard. 

Track promotions by race and gender

Advancing in their careers is quite a struggle for women and minorities, even in this day and age. A McKinsey study found that for every 100 men promoted to manager, only 85 women advanced. That number was even less for women of color. 

Companies have been known to promote a majority of white men based on potential, whereas women and minorities are awarded positions based on experience.  

This behavior feeds the “prove it again” bias, the often unconscious expectation that women and minority employees readily supply evidence of their competence. 

In a survey of bias in engineering, 68% of respondents of color stated that they had to continually prove themselves, while only 35% of white male engineers felt similar. 

When promotions and pay data are tracked alongside a company’s diversity and inclusion strategies, the company is forced to hold itself accountable to its employees. This makes the company better equipped to identify inequality, and able to uncover existing bias in promotion practices. 

Ensure the hiring process is unbiased

When it comes to recruitment and hiring practices, the influence of implicit bias is serious and detrimental.  

From a reliance on traditional recruiting sources to judging candidates based on their name, judgment can take many forms. 

A vast body of research shows that the hiring process is biased and unfair. Unconscious racism, ageism, and sexism play a big role in who companies hire, but this can be changed with the help of artificial intelligence that eliminates human bias.

Arya Pulse provides employers with one consolidated list of qualified candidates from 70+ professional channels instantly. Arya uses advanced machine learning and AI to qualify candidates based on a company’s inputs. Arya helps organizations meet their individual diversity, equity, and inclusion goals while eliminating human hiring bias. 

Similarly, Knockri is an HR tech startup that uses AI to create interview assessment tools to help companies eliminate all hiring bias in the workplace.   

Knockri uses Ethical AI technology to score candidates based on their answers, excluding their appearance or name. This has resulted in an average increase of racial and gender diversity by 25% and increase in quality of hire by 22% for their clients.   

AI anti-bias hiring technology is not just designed to help companies meet their diversity quota; it’s meant to bring them the best candidates with the layer of initial bias removed that might come with the first interview or application.