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Q&A: Turn chief product officer Brian Gaspar shares how AI is transforming hiring and recruitment

Turn Chief Product Officer Brian Gaspar

Startup Turn’s AI-driven HR tech tool is revamping talent acquisition for companies that depend on high-volume hiring in industries like healthcare, retail, ecommerce, and delivery. Featured at TechCrunch Disrupt 2022, the autonomous hiring platform can reduce companies’ hiring costs by 83%, according to Turn CEO Rahier Rahman.

Turn’s process features automated marketing, recruitment, candidate sourcing, pre-screening, compensation data, background checks, job simulations, and onboarding. The platform also provides integration with hiring software from companies like Lever, Fountain, and Greenhouse.

With a tight labor market and an uncertain holiday consumer spending season approaching, the prospect of fulfilling hiring needs by adding thousands of recruiters can be daunting for companies. According to Rahman, the startup’s goal is to simplify and streamline talent acquisition through machine learning (ML) while yielding benefits for workers.

“What often gets missed is our platform is also designed to help workers,” said Rahman. “We analyze and survey thousands of workers every month and have found that they’re predominantly underutilized. People say they have more capacity to work than they’re actually working. These aren’t people typically looking at Indeed or Careerbuilder. Our technology allows workers to discover more opportunities to increase their productivity.”

Turn chief product officer and former head of technical product management at Amazon Brian Gaspar spoke with us in an interview about how Turn’s platform can help alleviate challenges companies face in today’s labor market.

The following has been edited for clarity and brevity.

Insider Intelligence (II): Given the paradoxical labor market we’re in where companies are laying off workers while they also face difficulties hiring the talent that they need, how does Turn’s technology help address these issues?

Brian Gaspar (BG): The labor market is cyclical and it’s very hard to have consistency, so organizations are set up to adjust, scaling up or down based on need. The challenge is all the time and effort it takes to do that, which is why our solution is valuable.

Adjusting doesn’t have to require adding thousands of recruiters. As a great example, during my time at Amazon when we entered peak hiring season during the holidays, we would scale from 1,200 people to 6,000 people just in recruiting. The other aspect is that the time it takes to adjust to changing market conditions is typically about three months. Using our solution, that happens in seconds because we’re always adjusting.

Amazon just announced upping their pay for warehouse workers to $19 per hour and I have no doubt that it took them four months to do that. For us, we adjust every single day based on what’s happening in the market, which can save time and money.

II: What solutions do you provide for companies struggling to find candidates with the skills they need?

BG: As we look at targeting people to hire, we see that people in one job can do another job—a security guard can also be a driver. There’s a lot of interchange that can occur with incremental skill building. As part of retargeting, we look at how many people have a particular primary skill. Then we look at adjacent people who could also learn that skill and we get them qualified to do the job.

We screen them to make sure that they have the right qualifications and put them through job simulations to determine if they have the right tendency to be a good fit for the job or if they have skills that might not be obvious from a resume.

II: What’s the outlook for the HR professionals and recruiters whose jobs might be displaced by your technology?

BG: If you look at a recruiter, they’re a salesperson at heart. They’re trying to close a deal by finding someone to accept the job. These folks have adjacent skills where they can move into sourcing in another concept or sales.

With our technology, companies are going to finally be able to build the things they’ve always wanted to because they’ll have quality employee engagement, the right culture, and will be able to spend more time on making sure that an employee’s first couple days are positive. Because if you have a bad experience during the first couple days, attrition rate goes up by 50% within the first 12 months.

We also don’t think that autonomous hiring can completely replace recruiting teams, but it can work alongside them and allow them to be better at their role. There’s a human element that still needs to be incorporated in the process, but it frees recruiters up to do their jobs better through billions of data points that they can take action on.

II: How can companies be actively engaged in getting the most out of your platform?

BG: Turn allows them to understand what’s happening with every position they have. For example, we’re working with a $10 billion company that hadn’t been able to fill a role for 10 months, and we were able to tell them why. We found that they were offering a job title that was only used by the financial industry and they were automotive. So 96% of the candidates that they identified were in banking. We educated them on the titles they should be using, and when they changed it, they had 14 people scheduled for interviews within 24 hours.

The information we use to educate companies to recruit better is dispersed and highly hard to aggregate. We can help companies answer hiring questions before they even get started.

II: There’s concern about AI causing bias in hiring. What is Turn doing to make sure that doesn’t happen on its platform?

BG: For us it’s all about ethical AI—ensuring at the ground level that data is being used properly. The first step is to assume that you’re going to get hacked and make sure that nobody can access the data.

The second step is continuously testing to make sure there’s no bias in the data. It’s both an automated and a manual test where we look at the areas where we’re placing people and have alerts set up so that if hiring data is skewed for a specific job, the system notifies us and we go in to assess why.

We can track down to the street level, essentially. We know what the diversity is in a ZIP code or city, and if hiring starts to skew outside the norms, we dig in to see what happened.

Companies need to put these kinds of procedures in place—you can’t set and forget AI, because the model could be wrong and there could be something you don’t know occurring.

This article originally appeared in Insider Intelligence'sConnectivity & Tech Briefing—a daily recap of top stories reshaping the technology industry. Subscribe to have more hard-hitting takeaways delivered to your inbox daily.