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Leveraging Artificial Intelligence (AI) to Support Diversity, Equity and Inclusion Efforts (DEI)

AI and DEI

Artificial intelligence (AI) has become ubiquitous in our lives, promising to revolutionize various industries. But what about its potential impact on diversity, equity, and inclusion (DEI)?

In 2017, “Artificial Intelligence” (AI) became an industry buzzword with the slogan “data is the new oil” echoing across boardrooms and headlines. It was also said to be the disruption that went beyond the usual trend (like the metaverse). However, at that time, the use of the term AI was often inflated and only referenced basic concepts of machine learning, chatbots, voice recognition, and Software as a Service (SaaS) models. It wasn’t until the end of 2022, that we started seeing its disruptive manifestation and capacity for wide-scale transformation, particularly with the emergence of Open AI and ChatGPT. 

In 2020, after the Black Lives Matter protests and the call for more diversity and inclusion, AI in diversity, equity and inclusion (DEI) gained momentum and was touted as the ultimate solution to reducing unconscious bias in hiring, addressing inequality in various industries and senior management roles, and the first step to creating a truly diverse and inclusive workplace. 

As a result, many organisations, particularly in the tech space announced initiatives using AI to promote DEI. Google’s “AI for Social Good,” IBM’s “AI Fairness 360,” and “Diversity in Faces” projects are just a few examples. Many organisations also adopted DEI language in their job descriptions to show their commitment to creating an inclusive environment for people from different backgrounds, orientations, and races. Despite the hype, the impact of these initiatives is still up for debate. 

Now, AI is everywhere, promising to make our lives easier and transform various industries. But what about its potential impact on DEI?

The Potential Benefits of AI on DEI

As much as we try to be objective and unbiased, our conditioning, upbringing and exposure have ways of influencing our decisions. That is where we need to rely on data and tech to fill in the gaps where human capabilities fall short. AI has the capacity to avoid affinity bias such as a preference for candidates from certain universities in the hiring process so that the best candidates are chosen based on merit, rather than subjective criteria.

Here is how Ted Sergott EVP, of Product Development at PRO Unlimited describes it: an organisation runs a job description through its AI platform, and the algorithm will suggest alternatives to biased, gendered or off-putting language, helping develop a more balanced job description. Then, when a resume is submitted, the technology strips out elements that might create bias — name, pronouns, address, educational institutions, extracurricular activities, etc.

Although inclusion is harder to measure, AI can measure it by analysing people’s networks, identifying hidden biases in language use, and even diagnosing inclusion problems that manifest themselves in trust, engagement, and retention. Think of it as a data mining tool. For instance, natural language processing could be used to detect if ethnically diverse employees are addressed with micro-aggressive words and passive-aggressive mannerisms. Email metadata could reveal if ethnically diverse employees are excluded from central social networks in the organisation and other hidden dynamics between interactions at work. AI tools can also help leaders become more mindful of their communication and ensure that no group is unintentionally disrespected.

Beyond that, AI can measure performance based on metrics that matter, such as sales, revenue, profits, productivity, innovation, engagement, and turnover – ignoring factors like gender, race, age, and attractiveness. This can shed light on why some employees aren’t getting promoted even when they’re clearly capable, and reveal any unspoken opinions and views that senior leaders may have about their suitability for advancement.

Thomas Chamarrow Premuzic gave an example using Uber and how its algorithm uses features such as the driver’s number of trips, revenues, profits, accident claims, and passenger ratings to measure performance, instead of relying solely on human managers to decide whether a driver is better than others.

Of course, AI isn’t a perfect solution – humans are biased by design. But with the help of AI, we can finally keep our biases in check and reduce the ingroup and outgroup feelings that have plagued workplaces for too long.

At Career Masterclass, we understand that creating a diverse, equitable, and inclusive workplace is crucial for any organisation’s success. That’s why we provide cutting-edge DEI services that align with the latest trends and best practices, including the use of AI.

Our goal is to help you become a thought leader in your industry and stay at the forefront of innovation and progress in DEI. With our customised training programs, specialised consulting services, and partnerships with other DEI experts, we offer a comprehensive approach that is tailored to your unique needs.

To learn more about how we can help, Click the LINK to schedule a call and take the advancing of your DEI initiatives.