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Diversity and inclusion have become important topics in the modern workplace. Despite companies’ best efforts, unconscious bias and discrimination still exist in recruitment practices. Fortunately, artificial intelligence (AI) has the potential to help decrease diversity biases in recruitment. We can already see this from AI powered job search platforms that are revolutionizing recruitment, so why not implement it in more areas of recruitment?

What is Diversity Bias

First, it is important to understand what diversity bias is and how it manifests in recruitment. Diversity bias refers to the unconscious prejudice towards or against a particular group of people. In recruitment, this can mean that hiring managers unconsciously favor candidates who share similar backgrounds or characteristics, such as gender, race, or ethnicity.

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This can lead to a lack of diversity in the workplace, which can limit the perspectives and experiences that are brought to the table. Implementing AI to recruiting practices would help HR departments everywhere.

Blind Screening

One way that AI can help decrease diversity bias in recruitment is through the use of blind hiring practices. Blind hiring is the practice of removing identifying information such as a candidate’s name, gender, and race from resumes and applications. By doing so, hiring managers are forced to focus on a candidate’s qualifications and skills rather than their demographic characteristics. AI can assist with this process by automatically scrubbing resumes of identifying information and highlighting relevant qualifications and experience.

AI can also assist with the creation of diverse job postings. Studies have shown that job postings can inadvertently include language that is gender-biased or discourages certain groups from applying. AI can analyze job postings to identify any language that may be discouraging diverse candidates from applying and suggest alternative phrasing that is more inclusive.

Data-Driven Candidate Selection

Another way that AI can help with biases in recruitment is by widening the candidate pool. Traditional recruitment practices often rely on personal networks or job boards that may not reach a diverse range of candidates. AI-powered recruitment tools can analyze a wider range of job posting sites and social media platforms to identify and reach a candidate pool that is more diverse and inclusive, reflecting well on a company.

Thanks to machine learning and a good algorithm, AI can be trained to analyze factors about candidates, such as their work experience, education, and skills, and identify patterns that are predictive of job success. This can help recruiters focus on objective qualifications rather than subjective biases. Additionally, AI can assist with the creation of targeted recruitment campaigns that specifically target underrepresented groups.

Specialized Assessments

Furthermore, AI can provide objective assessments of candidates. Traditional recruitment practices often rely on subjective assessments of candidates, which can be influenced by unconscious bias. AI-powered assessment tools, on the other hand, can analyze a candidate’s skills and qualifications objectively without regard to their demographic characteristics.

These assessments include engaging and interactive games that measure the cognitive abilities and soft skills of job candidates, such as problem-solving, teamwork, and communication. Additionally, AI can assist with creating assessment tools that are more inclusive and reflective of diverse backgrounds and experiences.Diversity Analytics

Diversity Analytics

Finally, AI can analyze data on the diversity of a company’s workforce and identify areas where there may be biases or disparities. This can help recruiters identify opportunities for improvement and create more inclusive hiring practices. Overall, AI can help decrease diversity biases in recruitment by providing a more objective and data-driven approach to evaluating job candidates. By removing human biases from the process, AI can help ensure that companies are hiring the most qualified candidates, regardless of their background or identity.

AI vs. Humans: Baseline Comparisons

Blind Screening

• AI can eliminate unconscious bias while screening candidates
• Humans may have inherent biases that can affect the screening process

Data-Driven Candidate Selection

• AI can process vast amounts of data to identify the best candidates for a job
• Humans may rely on their own biases, gut feelings, or limited information when selecting candidates

Creating Specialized Assessments

• AI can create customized assessments based on job requirements, candidate data, and feedback
• Humans may create standardized assessments that do not accurately measure a candidate’s abilities or fit for a job

Data Analytics

• AI can analyze vast amounts of data to identify patterns and insights that can inform recruitment and talent management decisions
• Humans may struggle to identify relevant patterns or may be limited by their own biases and assumptions when analyzing data

AI is Not Perfect

While AI has the potential to decrease diversity bias in recruitment, it is important to note that AI is not immune to bias. AI algorithms can inadvertently perpetuate bias if they are trained on biased data or if their inputs are biased.

The Bottom Line

Diversity and inclusion are important goals for any modern workplace, and AI has the potential to help decrease this form of bias in recruitment.

By using blind hiring practices, creating diverse job postings, widening the candidate pool, and providing objective assessments of candidates, AI can help ensure that companies are hiring the best candidates based on their skills and qualifications, regardless of their demographic characteristics. It is important to remember that AI is not a cure for bias as it still has margins for error. However, it can certainly help.

Wanna become a data scientist within 3 months, and get a guaranteed job? Then you need to check this out !

This blog originally posted on https://thedatascientist.com/how-ai-helps-decrease-diversity-biases-in-recruitment/