When Algorithms Hire: The Promise and Pitfalls of AI in Recruitment

Welcome back to on the Job. I'm Avery Thompson. If you've applied for a job recently, chances are some filtering software saw your resume before any human did. That is, if a human saw it at all. Today we're exploring how artificial intelligence is transforming how and who we hire. And I've got not one, but two experts in the field to help us separate fact from fiction on what happens after we hit submit.

My nice being e Banks. I'm the CEO and head of Research for Lighthouse Research and Advisory, also the author of Artificial Intelligence for HR, among other books.

So Peter Capelli, I am the George W. Taylor Professor of Management. I also direct the Center for Human Resources at the Wharton School.

So, whether you're on the job hunt or the one doing the hiring, or like me, just curious what all this AI hubbub is about. Stick around. When you ask most little kids what they want to do when they grow up, you tend to hear some familiar answers, things like astronaut, fireman, professional athlete. That wasn't the case with Ben Eubanks.

I wanted to be an HR and as a kid, so I watched my parents working in their small business. They had trouble hiring people, mainteninent benefits, keeping them long term, all those things, and I thought, I'll figure out to do that thing, whatever that is.

For Peter Capelli, well, human resources wasn't exactly his childhood dream. Like Ben, he also recognized a system that needed fixing.

It was kind of the discovery of just how bad it was.

That discovery led Peter to a career in academia. And the more he came to learn about how we hire in this country, the worse it seemed. To get.

What we're looking for. I think as researchers is something which is a surprise. That's the big win for us. And this was a surprise, just unfortunately a band surprise, but surprising nonetheless.

And I think it's fair to say Ben agrees the hiring process has always had issues always to that end, AI is being heralded as a potential game changer in the field, able to not only process thousands of applications and seconds, but also uncover relationships and patterns and data that humans likely miss and Ben Eubanks says that initially most people in the field looked at the arrival of AI with open arms.

There are some opportunities where AI can play and let us do things we could have never done unless we had an unlimited budget and unlimited people on the recruiting team. There's not a company out there like that. So the cause of that, everybody's trying to get an infinite amount of work done with a finite amount of people hours.

But that doesn't mean these companies necessarily knew what they were working with.

I don't expect HR professionals, recruiters, learning leaders. I don't expect any of them to be experts in technology and data science and AI. I don't expect that because they have a full time job already.

And Peter Capelli says, CEOs, we're guilty as anyone forgetting caught up in the AI hype.

The people at the very top of the companies. These are the CEOs in particular. I think that large language models and generative AI are just plug and play things. You just asked chat gbtwo to do your job for you, and then they're going to do it right. And as a result, they are pushing lower down in HR in particular to use more and more AI.

This plug and play approach. As Peter A. Capelli calls. It is something Ben Ubanks is all too familiar with, as human resources personnel try to outsource a lot of their work.

Everybody says, letay, I do the work that's kind of repetitive, and we can put the humans in on the strategic stuff. We can focus on the higher value work. That's the big promise of it is we're doing a lot of things. There's not a single person ever met that got into the worldoking resources like I can't wait to look at a stack of resumes, or I can't wait to go and schedule interviews and then have to schedule inities, and then that manager is six and then with the reschedule like,

And while AI can sort out that stack of resumes in the blink of an eye, it's becoming clear that these systems aren't always doing a good job.

And the thing that was most prevalent was discrimination. A fair amount of evidence that women and also minorities of various kinds got systematically lower scores on performance appraisals.

There could be a potential bias in there, and so when I'm seeing that the best companies do their buildings, technology is thinking about that, planning for it. But that doesn't completely mitigate that risk.

It's no surprise that both Ben and Peter brought up biases, because when it comes to hiring, that's always been the elephant in the room.

We are just full of biases, and particularly if you've got hiring managers who are not trained. You know, one of the dumber things we've done as a business community employer community is that we've cut back on recruiters, who are people who do this for living, you know, hiring find people, assess them, and we've pushed those tasks onto line managers, who are people who don't do this for a living and they've got other full time jobs.

No matter how equitable and objective a company may strive to be, humans are inherently prone to biases. So it makes sense that some in the HR field saw AI as a potential silver bullet, a purely analytical tool that could bypass all of our human foibles. No longer would we need to rely on gut feelings. Instead, we can just press a button and let the numbers speak for themselves that there's.

Some pretty wild data, pretty compelling that's coming out. There's an experiment done with recruiters that shows that when they're using algorithms, if they think are very predictive, they're more likely to take their hands off the wheel and let the car drive itself. And we generally know that it's not a good idea.

And unfortunately, as Peter Capelli explains, these AI systems were built by humans and rely on historical data that inevitably reflects the very inequalities we're trying to move away from.

There is a particular problem that is unique to large language models and machine learning in particular for hiring. The data that you're using to train the model is historical, right, it can't all happen today, and anything strange going on in the labor market ten years ago will show up being built into the model. And the thing that was most prevalent was discrimination.

As an example, imagine a company builds a screening system to identify the best applicants, only to realize that system was filtering out all the women who applied. Unfortunately, that's not science fiction, but what actually happened. And at Amazon back in twenty fifteen.

And even if you took out names and other attributes, it would still find in the algorithm anything that was associated with being a woman, like your college courses. You know, if you took women's studies courses, more likely be a woman maybe, And so it would still give women lower scores because historically that was one of the predictors. Any biases that were in the data earlier are going to be codified into the algorithm.

Not sounding like the answer to all our hiring problems now, is it? In fairness, though, these are the growing pains of a new technology, one whose powers and limitations were still discovering.

See, AI is not a decision engine. It's a recommendation engine, especially in hiring it should be, and so it's recommending this path, and it's giving me inputs, and I, as the HR person or the recruiter, can make a choice on what to do next.

But companies aren't the only ones trying to utilize the power of AI. Job applicants are also giving these new technologies to go. So when we come back from the break, we'll explore how AI is helping job seekers land their next gig.

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We're back with our human resources experts, Ben Ubanks and Peter Cappelli. In the first half of the episode, we uncovered how HR departments and staffing agencies are incorporating AI into their hiring processes. But they aren't the only ones utilizing this powerful new tool. As companies increasingly automated hiring, job seekers are also turning to AI.

We're seeing in our research one out of every three candidate says they're either using AI to help apply for jobs or they're going to start. So it becomes almost an arms race. If everybody else is doing it and I'm not, I'll be shut out the market.

But can you blame these applicants. Anyone who's ever applied for a job knows it's a tedious, time consuming process and often hitting submit feels like we're just throwing our resumes into a digital waste paper basket. And unfortunately, there's actually a fair bit of data to back this up.

A couple of years ago. The last time I look the probability that you're going to get hired if you send your application into one of the big job where it's like Indeed or one of those, that was about two percent. So how many people would actually look at it, say, the short list is double that, so maybe you got a four percent chance. Don't expect that people are sitting around at night debating the merits of your resume.

It seems that job seekers have responded to these incredibly low success rates by flooding the market. Would you, at least in theory makes sense.

Let's say I'm tired of applying for jobs. I can go to a lazy apply or some other websites I can pay a little fee, and they're automatically applying to hundreds or thousands of jobs on my behalf without me ever lifting another finger to do that. That's happening right now, and employers are getting flooded by resumes because of this. I talked to a company the other day that said we used to get twenty thousand resumes a month. Big global company.

So, Peter, are we at a state where it's just computers applying to computers? Yeah?

I think we probably are now. I guess the slight caveat to that is it has to start and be based on something real. That is, you would think any smart employer, their selection software is ba them what they really want. And if you're an applicant, your experience really is a little unique. So it isn't completely standardized at least if it's sensible. But is it automated? Still? Yeah, it is.

I gotta say I find it refreshing to hear two people more knowledgeable about AI not talking to me about it like a couple of used car salesmen. Sure, AI will probably transform things in our world, including the way we hire, but it doesn't seem like it's going to happen overnight. In the meanwhile, Ben Ubanks and Peter Cappelli suggest companies take a more cautious and considerate approach to how they incorporate these technologies.

Well, I'm doing a keynote on this topic of AI. The headline in the Guardian says, job hunting and the age of AI is grim, frustrating, dehumanizing. When I ask an audience of HR leaders, hey, how many of you put your hands up if that's what you want your job start process to look like at your company? Not a single hand goes up, Absolutely not. But that's what we end up with if we're using AI because someone told us to quote unquote get to an AI.

And we need to remember that these advanced systems are only as good as the information and we're feeding them. So before we look to them for the answers to all of our future problems, we might want to first look back at how we fall in short in our own past.

Every company out there that takes a job description out of the old vault blows all the dust off and says, Okay, let's use the same one from five years ago to hire this job again. You are doing your company to service because that job has changed. I can guarantee you it has changed to some degree. It's an imperfect system, Honestly, Avery, we're using imperfect job descriptions with imperfect resumes and trying

What happens now, for the most part, is that we hire people who we like, and those tend to be people who are similar to us.

So, after all this discussion about AI's potential and its pitfalls, I wanted to end the conversation with some concrete advice for those of you listening who are struggling to find a job, and you might be surprised by what they recommended.

I'm going to tell you something that is going to upset anyone to know that's in the recruiting world, and is going to be helpful anyone who's looking for a job. But the best way to beat the system is to stay out of the system. Find a human, find a connection, find a relationship, and play that up.

One of my kids had a real problem getting a response from a company he had applied to, and eventually I told him write them a letter, physical letter. I don't know whether that's why he heard from them or not, but I'd like to think it is because they don't want thousands of people pinging them about jobs. They don't have time to read them, but a letter. There aren't very many come in so might very well get to the person.

There you have it, folks, what's old is new again. So maybe instead of spending money in the latest and greatest AI subscription, we should all go out and buy some Forever stamps before they go up and price again. For on the job, I'm Avery Thompson.