AI & Diversity: Artificial Intelligence Tools Making Workplaces More Inclusive
28 July 2020
Diversity and inclusion are key to creating a best-in-class workforce and work environment — and AI can help you reach your D&I goals. But what role does AI play in diversity and inclusion? And how will AI continue to shape diversity and inclusion in the workplace as technology evolves?
A diverse and inclusive workforce is one that brings together people of different backgrounds and mindsets to foster innovation and new ways of thinking — and to benefit the organization.
Diversity and inclusion can bring a variety of advantages for your business, from employee engagement to revenue.
Organizations with inclusive cultures are 3x higher performing, 6x more innovative, and 8x more likely to achieve better business outcomes.
And an open, welcoming workforce grows itself. 64% of candidates say that diversity plays an important role in their decision to accept a job offer. When you build a diverse workforce, you’ll attract greater diversity as a result.
D&I isn’t easy to get right
Establishing an inclusive culture takes time and effort — it requires total buy-in from everyone involved, and money needs to be continually invested to avoid the blind spots and weakness inherent in every organization.
The biggest obstacle of all? Human nature.
The human issue with D&I
What stops traditional recruiting processes from building diverse and inclusive workforces? Bias.
A bias can be defined as a general pattern or tendency that causes us to think or act a certain way. It might be assuming that only one profile of individual is capable of doing a job. Or only wanting to work with associates who studied at the same college as you.
All people have biases, whether we’re aware of them or whether they remain unconscious. A report from IBM explains that bias affects every part of recruiting, retaining, and engaging talent, including:
- Talent attraction
- Career development
- Performance appraisal
One study found that candidates who “whitened” their names on their applications got more interviews than those that didn’t. McKinsey and Lean In report that women ask for raises and promotions just as much as men do — but they’re 18% less likely to receive those promotions than their male counterparts.
Even if we think we’re completely unbiased, humans will always be vulnerable to partiality. That’s where artificial intelligence (AI) comes in: to help us override even the most unconscious prejudices, the ones that get in the way of building a diverse and inclusive workplace.
AI and diversity: what we’ve seen so far
AI and machine learning are already making diverse and inclusive hiring easier for companies around the world. Here’s how:
✺ Creating better interview panels
Some tools and applications use machine learning algorithms to create a more inclusive and unbiased interview process. The algorithms in these tools can help hiring managers and recruiters build diverse interview panels that reduce individual bias — and attract more diverse candidates.
✺ Finding diverse high-potential candidates (faster)
Machine learning and data science tools like Headstart’s diversity-driven Applicant Matching and Management System can help companies find high-potential employees to build a diverse, inclusive, and talented workforce.
Headstart uses machine learning to help clients identify the highest potential candidates for the job — regardless of gender, ethnic status, sexual orientation, or age.
Machine learning can also remove inefficiencies from the hiring process. AI-powered recruiting tools can help you find best-fit candidates, reject irrelevant applications, and speed through screening faster by using machine learning to create unique candidate-role fit scores.
Companies can also utilize machine learning to identify existing biases in their hiring processes: Headstart’s pipeline analytics can show areas with high drop-off rates for gender and ethnicity.
✺ Writing unbiased job postings
Social scientists found that coded gendered language in job ads can promote and sustain gender inequality. For example, job postings in male-dominated fields, like computer science, used masculine-coded language (i.e., “conquer” or “dominate”).
The researchers found that masculine-coded words can discourage women from applying for a job because they feel like “they don’t belong.”
AI-powered tools can help recruiters and hiring managers write gender-less job postings by recommending replacements for gendered language. This can help companies attract a more gender-balanced group of candidates; making D&I objectives easier to reach, and allowing true talent to flourish.
✺ Offer fairer salaries
If you remove the human element from pay gap discussions, what are you left with? Just the numbers. And AI-powered tools can take control of salary allocation, distributing fairer and more precisely calculated employee pay outs.
AI gives employers “new opportunities by rethinking the value that compensation programs deliver to the business and employees,” says George Zarkadakis, digital lead at Willis Towers Watson in London.
AI can analyze and parse market data to recommend competitive salary ranges. Calculating salaries with AI can help prevent pay disparities across employees based on gender, race, age, and other factors that may play into salary discrimination.
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What’s next? The future of AI and D&I
At Headstart, we’re really excited to see where AI and ML can take us in terms of diversity and inclusion in the workplace. But even the best automation tools will fall short without a company-wide commitment to D&I.
AI can — and will — continue to help companies build more diverse, talented workforces as long as business leaders (both those building the AI tools and those implementing them) make diversity and inclusion a main priority.
As AI and machine learning play bigger and bigger roles in corporate decision-making, it’s important to recognize that they’re not infallible. The best AI systems for diversity and inclusion are those built for and by diversity-minded teams.
AI itself must be trained to think inclusively.
An article from MIT Sloan explains that some of the data sets used to train AI “contain historical artifacts of biases.
“Looking to the future, we need to focus on creating truly unbiased machine learning algorithms. And, at Headstart, we do just that — empowering true and valuable diversity in organizations across the world.“
Wondering how a machine learning tool like Headstart can help your company overcome bias and create a more diverse and inclusive workplace? Book your free demo today.
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