Artificial intelligence (AI) is gaining ground in the workplace - and the recruitment sector stands to benefit hugely. Firstly, AI will take care of all the mundane tasks like meeting preparation, reporting and data entry, allowing recruiters to spend more time doing what they do best: engaging with clients and candidates, and building lucrative relationships. Secondly, and perhaps somewhat unexpectedly for some, AI may also help recruiters attract more diverse pools of candidates.
Workplace diversity is high on the agenda for most businesses these days. A recent Deloitte survey confirmed that a diverse and inclusive workplace can generate 30% higher revenue per employee and is twice as likely to meet or exceed its financial targets. This means that recruiters are going to come under even more pressure to improve their sourcing capabilities and find a variety of suitable candidates that meet clients’ demands. Here’s how AI could help recruiters improve candidate diversity.
1. Remove gendered language from job descriptions
Certain words used in job descriptions may put some prospective candidates off from applying. For example, studies have shown that job posts with masculine-type words such as ‘dominant’ and ‘challenging’ are less likely to attract female applicants.
AI can detect and remove biased language from these job posts, using a technique called natural language processing (NLP) which enables computers to understand the written and spoken word. This will help ensure that the vacant position gets as many relevant responses as possible – from a more diverse pool of applicants.
2. Avoid unconscious bias in the CV screening process
During the applicant screening process, unconscious biases may put the candidate at an unfair advantage or disadvantage. These biases could relate to demographic factors such as race, gender and age. They’re typically triggered by information on a CV or application such as the candidate’s name, the schools they attended, and when and where they held previous positions.
AI can help recruiters avoid these types of biases by programing software to ignore certain information when screening CVs. This eliminates any social preconditioning or emotional response. The software is simply looking for candidates that are best qualified to fit the job in question.
However, it’s important to bear in mind that AI also has the potential to learn biases that might already exist in your data. For example, if your company has historically recruited candidates from a handful of specific colleges and universities, then AI trained on this data may learn to rank graduates from these schools as more qualified candidates. Of course, the advantage of AI is that compared to human biases, it’s much easier to audit and remove discrimination from a software program.
3. Support candidate sourcing and rediscovery
One way in which AI can assist recruiters find diverse candidates is by predicting applicants’ gender and race using first and last names as indicators. This would be useful, for example, if your client had specific diversity targets to meet. That way, you could design your sourcing strategy to engage those minority groups.
AI can also help recruiters rediscover candidate opportunities by analysing a job description and then cross-referencing its requirements with candidates who already exist in their ATS or CRM system. The importance of rediscovering existing candidates – in addition to sourcing new candidates – cannot be overstated, especially when it comes to filling challenging roles. Missing out on these opportunities ultimately means missing out on revenue.
The limitations of AI
Of course, technology can’t be relied upon solely to solve these issues. Recruiters themselves need to accept more responsibility for the candidate experience and look for ways to reduce bias in the search process.
Any good recruiter will tell you that success in the industry depends on personal relations. Incorporating AI into the recruitment process won’t change this: it can connect candidates and recruiters, but it can’t build the relationships. It’s important that firms realise the limitations of AI. It can process and generate questions and answers, but there is still a long way to go before AI can truly connect with people.
For instance, if a candidate has a speech impediment and part of the interview process is conducted orally, then they are at an immediate disadvantage. AI won’t be able to compute these communication issues and will rate the applicant poorly. What’s more, AI is programmed to ‘learn’ responses based on previous interactions. This naturally means that it won’t necessarily be capable of solving new problems as they arise.
AI cannot replace human recruiters, but it can help them do a better job. Firms need to focus on where and how AI can support their business goals – rather than expect the technology to do all the work for them. However, if and when recruiters put AI to work for them, then they will benefit from access to a more diverse pool of candidates and a more satisfied cohort of clients.
