Skip to main content

New Ways to Drive DE&I with AI Talent Technology

Ask any HR or people team what’s on their list of strategic priorities, and the chances are that improving Diversity, Equity, and Inclusion, (DE&I) is pretty near the top. One of the areas they are exploring to that intent is how to drive DE&I with AI talent tech.

DE&I covers a range of complex issues – race, gender, disability, age, ethnicity, sexual orientation, to mention a few– and is an increasing focus for forward-thinking, values-led companies. According to The Hackett Group, businesses on both sides of the Atlantic are planning to double their spend on diversity by 2025.

And it’s not just a branding exercise, nor a nice-to-have. Improving DE&I in the workplace creates a better environment for employees and is proven to drive important business outcomes. Findings from McKinsey show that more diverse companies are more profitable and performant; a trend that will only accelerate in the wake of the pandemic.

But despite widespread understanding of its importance, overall progress on DE&I has been slow, and in some cases, is getting slower. One of the fronts on which HR teams can make progress is technology: investments in tools that can enable them to understand their people deeply and holistically, identify issues and build strategies to address them. AI can help.

 

The challenges of DE&I in hiring

DE&I is hard to get right: conscious and unconscious biases can creep in almost everywhere across a business, excluding important perspectives, hindering collaboration and holding back progress against business goals. It’s especially difficult to protect against in HR teams, where so much is based on personal interactions with other employees and candidates.

In fact, hiring processes can actively be a barrier to meeting DE&I targets if not managed sensitively. There are a number of potential issues that can arise as candidates move through the funnel, including but not limited to:

Confirmation bias

Recruiters evaluate candidates based on ‘gut feeling’, and steer interview questions to confirm their instincts, rather than objectively assess aptitude

Affinity bias

Recruiters respond more positively to candidates they feel they get along well with, or who share certain characteristics, backgrounds and personality traits

Halo effect

Recruiters rely too heavily on one positive trait (a degree from a good university, for instance) and use that to shape their judgement of a candidate, rather than properly interrogating their skillset.

 

Research has shown that even the wording in job descriptions can be filled with implicit biases which invite applications from one type of candidate, while discouraging others. When processes are so dependent on individuals and their personal judgement or interview styles, it can be difficult to achieve the behavioural change that’s required for DE&I initiatives to be successful.

 

Using AI to advance DE&I

That’s where technology – and AI specifically – can be useful. More data than ever exists within businesses, and that gives HR teams new opportunities for learning and improvement. By surfacing deep insights about hiring processes and team demographics, they can start to identify issues and build models that eliminate bias and improve outcomes.

As we’ve discussed elsewhere, AI is not a silver bullet. It’s a developing and complex technology, and an important caveat is that while AI can reduce some of the disparities and inequalities introduced by humans, it can also occasionally reinforce them. When trained with limited or subjectively selected data sets, it can exaggerate second-order trends and skew results. 

That’s why it’s so important to start with (and maintain) high volumes of cleaned and normalised data. Good tools will actively solve for these issues by continuously training and recalibrating their algorithms, and can help drive your DE&I strategy in 3 key ways: 

 

Identify areas of issue

Strong DE&I strategies start with understanding the people inside the business. That requires diligent and ongoing data collection across a number of different axes – looking not just at basic demographics, but operational, experiential and performance metrics, too.

Getting a holistic view of their people in a single source of truth enables HR teams to identify where there are gaps and weaknesses in the business, and use that information to build effective solutions. With AI, HR teams can quickly see and continue to monitor where certain groups are under-represented or underserved, so they can prioritise and focus resources around fixing the most impactful problems. 

 

Reduce bias

AI should be used to augment and improve human decision-making, not replace it altogether. AI can help remove inefficiencies by overriding human biases and ensuring a level playing field for all candidates. 

Models can be built to exclude bias in algorithms either explicitly (by removing identifiers like name, age and gender) or implicitly (by removing things like address, education or salary). AI can also be baked into candidate scoring systems to ensure consistent and equal weighting across data points, ruling out the possibility of over-reliance on a single factor.

 

Improve inclusivity

Inclusivity goes one step beyond diversity. It ensures that not only are the right people in the room, but that they’re enfranchised and empowered once they get there. The ways in which certain working environments and communication styles exclude specific groups isn’t always obvious. AI can help HR teams get a better picture of where and why particular voices aren’t being heard, and adjust their processes to be more inclusive.

Not all candidates want to be spoken to in the same way. Some might have a preference for different channels or times of day depending on their personality type (introverts might prefer emails to phone calls) or family background (parents might need flexible timing to work around childcare). AI can help identify these trends by examining communication data across internal tools, for instance, such as frequency of messages, length, responsiveness, etc. It can also learn about candidates’ interests and skills profiles, and suggest content that is outside of their usual wheelhouse to broaden their views and create new opportunities for colleagues to communicate and be more inclusive.

 


AI (and especially AI in the talent management and acquisition space) is an emerging technology that presents a lot of difficult ethical questions. Talent practitioners need to think critically about their own standards to prevent potentially negative outcomes – but used sensitively and strategically, AI can help businesses accelerate key diversity and inclusivity initiatives, improving candidate experience, internal mobility and business outcomes.