Should Artificial Intelligence Be Used As a Replacement Tool in Diversity Recruitment?
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Many people ask this question. Today, I finally get to take a moment and talk about artificial intelligence in the context of diversity recruiting.
I know! We’re all looking for tools to support the work of increasing diversity, while also reducing the amount of time-consuming tasks. I get it. I’m constantly talking to vendors to learn more about the newest products or service offerings in the world of diversity recruitment. But there are so many new “solutions” popping up daily, that it’s enough to make your head spin. That is why we are unpacking it today.
There are two ways AI is mishandled in the recruiting space. The first is AI’s ability to absorb human biases. The second is using AI as a replacement tool for humans.
In the meantime, we have a video on today’s topic here. Check it out if you’re the kind of person who likes to sit back, relax, and watch.
For the wordies out there, here’s a quick read:
Conversation #1: Bias-Baked AI
Have you ever heard someone say, “trash in equals trash out,” or in this context, “bias in equals bias out”? Although artificial intelligence is meant to eliminate bias, it does not eliminate the bias within the designers of the technology or the data that feeds these AI algorithms. So, whenever I talk to recruiters and hiring leaders, and they tell me that a significant portion of their diversity recruiting strategy relies on tools with artificial intelligence baked in, I often feel a little concerned.
Even though AI is powerful and can filter out human-led biases, it can unintentionally perpetuate existing biases in the data it’s trained on. If your AI learns from biased data, it will make biased decisions. For example, if an AI tool is trained on past hiring data that favored a specific gender, it might continue to prefer candidates of that gender, overlooking other applicants.
Also, AI analyzing video interviews might unfairly penalize candidates for cultural differences in communication styles, such as eye contact, which could result in biased assessments. Overlooking this aspect might lead to overlooking qualified candidates from underrepresented backgrounds, undermining the very goal of increasing representation.
Conversation #2: AI As a Replacement Tool
AI is often used as a replacement for the inner work that hiring professionals on the frontlines (i.e., recruiters and hiring managers) also need to do. You can remove names all you want and create blind resumes, but eventually, the hiring team will still have to face their own biases within the interview process.
Let me be clear: Don’t use AI as a replacement tool, because it’s not a substitute for the human element in inclusive hiring.
Remember that inclusive hiring and training still need to happen for everyone working to increase diversity at your organization. Now, I’m not asking you to not use AI. But be cautious when deciding what tools to use or companies to partner with. Also, do not use it as a replacement for the real inner work of dealing with your resistance and bias.
Most importantly, be sure to measure outcomes. Look at your data and see if the tool you’re using is delivering what it’s supposed to deliver. Is it data-driven? Is it value-added? Or does your tool have side effects that you weren’t aware of? Learn with intent.
Finally…
All right, let’s wrap this up. AI can be a powerful ally in diversity recruitment, but it’s not a magic fix. Use it wisely, keep human judgment at the center, and never stop questioning the tools you rely on. Measure outcomes, stay vigilant, continuously improve the quality, and ensure your recruitment process is genuinely inclusive and effective.
JOIN US IN THE COMMENTS: What are your thoughts on using AI in recruiting? Have you had any experiences, good or bad, with AI tools in hiring? Join the conversation and share your insights in the comments below!
