There is a love/hate/curiosity involving the subject of AI in recruiting. Personally, I lean more towards the curiosity of the positive impacts AI can have in the recruiting industry but I am hyper aware it will not solve all. I have written a lot about the positive impact of AI in recruiting but I think it’s time to have a hard discussion about when to and when not to involve AI.
There are a number of positives when considering how to leverage AI in recruiting. We know how laborious the recruiting process can be- inundated with manual tasks and belabored with superfluous steps. I think this is one of the easiest areas AI can help streamline the processes and make them more efficient.
Companies are training AI/machine learning algorithms to help employers automate repetitive aspects of the recruitment process such as resume and application review. Imagine the day when you arrive to find your AI Buddy had been working all managing your more mundane tasks. Recruiters would be able to focus more time on value added interviews compared to today’s world wrought with frantic and chaotic processes that are inefficient and detrimental to the candidate experience.
AI platforms can also provide incredible data points for recruiters to learn how to make processes more efficient. Is there an email that gets candidates to respond quicker? Is there a time of day when candidates are more likely to respond? Can you automate a drip campaign to passive candidates to drive the top of the funnel?
These are all great data points and efficiencies AI can bring to the recruiting process. The primary goal of any tool, especially AI/machine learning, should be giving more time to recruiters to focus on the human side of recruiting and less on the inefficient processes.
If you’re into documentaries, I’d recommend taking some time to watch Coded Bias on Netflix.
In her provocative documentary, “Coded Bias,” filmmaker Shalini Kantayya questions the neutrality of technology, contending computers have a built-in bias reflecting faulty assumptions by the humans (usually men) who program them. Her focus is on the effect that this bias has on marginalized communities through business enterprises and the enforcement of laws. The film was inspired by the work of Joy Buolamwini, a doctoral candidate at the Massachusetts Institute of Technology, who conducted experiments using artificial intelligence to identify faces. When she looked deeper, she found these programs had trouble recording women as well as men. By digging deeper into the roots of these problems, “Coded Bias” serves both as a wake-up call and as a call to action.
According to Plum CEO Caitlin McGregor, instead of relying on historical data like resumes and CVs that are “full of bias,” organizations can turn to solutions to measure human potential data that measures a candidate’s ability play a certain role. The results of these evaluations are re-analyzed using algorithms to decide if the candidate’s skills meet the requirements of the job. The unbiased results generated by such methods help organizations easily address recruitment bias issues, even on a large scale.
If you use a platform to screen candidates using AI, it should not go unwatched. I like to treat my “AI partners” like employees an inspect what I expect. I have found instances using such platforms can have a negative effect on candidates and the brand image if left unguarded. There is still much to learn and evolve in how we use AI in recruiting.
So what do you do?
I will often get asked what is the right approach. I’m a simple guy who likes metaphors so I always like to use my favorite example of how to blend AI in recruiting.
Iron Man is the perfect blend of AI and human at its best. Tony Stark uses AI to enhance his human abilities but does not yield all decision making to his other half. Recruiters have a powerful human gift that cannot, and I daresay, will not be replicated by AI in the very near future: our gut.
I’ve found leveraging data provided by my AI partners along with my gut instincts or queues I picked up from interactions with a candidate provide a healthy balance. There have been times when my gut has been a little off but the data or insights provided by AI helped me recognize it. Conversely, there have been times that AI may have overlooked a candidate or process because of how it was programmed that I was able to intervene and course correct.
The epitomy of success should be balance. Recruiters should definitely embrace AI buddies to help them manage the mundane and transform into the super recruiters their organizations need. Sure, AI can definitely help source great candidates but recruiters own the commitment to an equitable approach to find the best qualified candidate with as little bias as possible.
There are limitations on both sides. Understanding and managing these limitations will be the key to success in AI and recruiting.
and Sprint Recruiting
I joined the HR industry in 2004 after working as a sales leader in the Financial Services Industry for eight years. After spending his first couple of years in HR trying to fit in, I found my voice. Now I leverage all of the things I once hated about HR to become a consultant and invaluable partner to the businesses I support. I contribute to the HRGazzette and to DataDrivenInvestor on Medium. WARNING: my writing style is raw and in your face, not what you would expect from an HR executive.
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