There’s Unconscious Bias at Work & AI Can Change That! Do you think you’re a biased person? At the top of your head, you probably aren’t. But each one of us imitates some degree of unconscious bias, especially in the workplace. Unconscious bias is when we judge, assess or form opinions of other individuals based on their name, race, gender, and other factors; without realizing it. This concept holds true for a lot of us, but it’s not really our fault. Rather, it’s a result of values, beliefs, and the culture that we have been accustomed to.
While most of us are aware of gender disparity in the corporate world, very few know or fully comprehend the unconscious bias that exists.
Numbers Don’t Lie
In a study conducted by MIT & the University of Chicago, 5000 resumes with Caucasian & African-American names were sent to 1,250 employers, with each person receiving four resumes. The study discovered that resumes with typically ‘white’ names received a 50% call-back as compared to the African-American names who were, in fact, more qualified.
In 2014, Google admitted that their male staff consisted only 3% Latino men & 2% African-American men. They acknowledged that the lack of diversity was a result of unconscious bias and in response, Google introduced bias-busting initiatives & workshops to educate their employees on the subject. Similarly, the Royal Bank of Canada provided sessions for roughly 1,000 executives to help them address unconscious bias.
Where AI Fits In
AI has brought drastic improvements to the HR process. From automating everyday functions (such as payroll & scheduling shifts) to using keywords and scanning resumes to assisting in performance management, there’s a lot that AI is simplifying. Now, add to it the option of eliminating unconscious bias!
Here’s how. AI uses Natural Language Processing (NPL) and cognitive learning to detect repetitive patterns that might suggest bias at work place. For instance, AI systems can skim through previous applications of hired employees to identify significant demographic trends in terms of age, race, and gender. This helps the system point out unconscious bias – something that the organization can work towards.
Studies suggest that bias also occurs well before the hiring process, going as far back as the language used in Job Descriptions. Words such as ‘ambitious’, ‘dominate’, and ‘ninja’ dissuade female candidates from applying. Organizations can address this issue with AI models that track biased language and accordingly suggest alternatives.
Monjin is a disruptive tech platform which understands the sensitivity of the situation. We are constantly working to address the issue of unconscious bias in a unique way. Our system automatically matches candidates with interviewers based on their industry & expertise, thereby eliminating human bias.
The Women in the Workplace study by Leanin.org & McKinsey found that for https://www.pass4lead.com/400-151.html every 130 men promoted, only 100 women were. And according to a study by Princeton & Harvard, blind auditions increased the scope of hiring female employees up to 46%. Unconscious Bias is an oft-ignored issue which when addressed, delivers an ethical and economic impact.