Everywhere you look, people are talking about AI – and the field of recruiting is no different.
Based on the technology as it is today, I wanted to share a few thoughts for talent acquisition leaders, HR leaders, and business leaders to keep in mind.
General AI Challenges
Let’s face it, AI algorithms are only as unbiased as the data they are trained on. If the data used to train the AI model is biased, then the model will be biased as well. This can result in a lack of diversity in your candidate pool.
A second general challenge to keep in mind is that AI is only as good as the technology behind it. Technical limitations, such as poor data quality, can impact the accuracy and effectiveness of the AI model, leading to suboptimal results. “Garbage in, garbage out” as the saying goes.
Third, implementing AI in any recruitment can be expensive, both in terms of the technology itself and the resources required to manage and maintain it. Yup – it takes experts with specific skills sets to make sure these tools are working as designed.
What Will Candidates Think?
Consider how AI – or any new technology will affect candidate experience.
While AI can automate many aspects of the recruitment process, it lacks the human touch that is important in building relationships with candidates. This can result in a negative candidate experience, which can hurt the company’s brand and reputation.
Take Amazon’s new AI screening tool. Now I don’t know exactly how the tool works but imagine it from the candidate’s perspective.
What if you go through the whole screening process without ever talking to a real person?
What if your first impression of a company is that their recruiters are too busy to talk to you – so they have a robot do it?
As advanced as AI is, it’s still not a replacement for a real conversation with a real human being.
And in today’s talent market, you have to actively sell your positions to get the best candidates to apply.
Handling interview scheduling is one thing, but can we really expect AI to know how to sell a position effectively?
Data and AI Should Inform Decisions – Not Make Decisions for Us
Another key point to consider is that AI is not necessarily smart enough to make screening and selection decisions entirely on its own.
I am a big believer in using data and technology to help us pick better candidates. We’ve had tremendous success at Qualigence using platforms like the Predictive Index and Perception Predict to understand how candidates will mesh with our unique teams, leaders, and culture.
It allows us to build teams with real chemistry rather than just hiring individuals with the best credentials (who often end up not getting along).
However, I believe technology should be used to GUIDE our decisions – not make them for us.
We’ve all seen great resumes for bad candidates and vice versa.
And how confident can we be that AI won’t make the same biased mistakes that it did just a few years ago?
If you’re not familiar, Amazon had to retire an AI recruiting tool in 2018 because it actually taught itself that male candidates were preferable – downgrading resumes that included phrases like “women’s chess club.”
Ideally, humans can leverage AI to combat unconscious bias by helping us pick candidates that will excel. But I think we’re asking for trouble if we trust AI to make decisions without any human input.
AI May Be the Future – But We Might Not Be There Yet
I 100% see the value in leveraging AI in recruiting. But I do think we have to be very careful about how we use it and consider the impact it will have on our candidate experience.
Based on what we know today, I would be hesitant to make AI an integral part of my screening or recruiting process. That said, AI technology is changing fast – who knows what might change tomorrow?