Q&A: Brian Gaspar, Chief Product Officer of Turn, explains how AI is transforming hiring and recruiting

Turn Chief Product Officer Brian Gaspar

start RoundThe AI-powered HR technology tool revamps talent acquisition for companies that depend on large recruitment in industries such as healthcare, retail, e-commerce and delivery. Introduced to TechCrunch disrupts 2022, the autonomous recruitment platform reduces recruitment costs for companies by 83%, according to the CEO of Turn Rahier Rahman.

Turn’s process includes automated marketing, recruiting, candidate sourcing, screening, compensation data, background checks, job simulations and onboarding. The platform also provides integration with recruitment software from companies such as The sink, Fountainand Tight.

With a tight labor market and an uncertain consumer spending during the holidays as the season approaches, the prospect of meeting hiring needs by adding thousands of recruiters can be daunting for businesses. According Rahmanthe startup’s goal is to simplify and streamline talent acquisition through machine learning (ML) while delivering benefits to workers.

“What often goes unnoticed is that our platform is also designed to help workers,” Rahman said. “We analyze and survey thousands of workers every month and found that they are mostly underutilized. People say they have more ability to work than they actually work. It’s not usually people watching In effect Where career builder. Our technology enables 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 to us in an interview about how Turn’s platform can help alleviate the challenges businesses face in today’s job market.

The following has been edited for clarity and brevity.

Insider Intelligence (II): Given the paradoxical labor market in which companies are laying off workers while having difficulty hiring the talent they need, how does Turn’s technology help solve these problems?

Brian Gaspar (BG): The labor market is cyclical and it is very difficult to have consistency, so organizations are set up to adapt, grow or shrink as needed. The challenge is all the time and effort needed to achieve this, which is why our solution is valuable.

The adjustment does not require the addition of thousands of recruiters. As an example, during my time at Amazon, when we entered peak hiring season over the holidays, we would go from 1,200 people to 6,000 people just for hiring. The other aspect is that the time it takes to adapt to changing market conditions is usually around three months. With our solution, this is done in seconds because we are constantly adjusting.

Amazon just announced a wage increase for warehouse workers to $19 an hour and I’m sure it took them four months to do it. For us, we adapt every day according to what is happening in the market, which can save time and money.

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

BG: When we look to target people for hire, we find that people with one job can have another – a security guard can also be a driver. There are many exchanges that can occur with progressive skill building. As part of retargeting, we look at how many people have a particular core skill. Then we look at adjacent people who could also learn that skill and qualify them to do the job.

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

II: What are the prospects for HR professionals and recruiters whose jobs could be replaced by your technology?

BG: If you look at a recruiter, he’s a salesman at heart. They try to make a deal by finding someone to take the job. These people have adjacent skills where they can switch to sourcing in another concept or selling.

With our technology, companies are finally going to be able to build the things they’ve always wanted because they’ll have quality employee engagement, the right culture, and can spend more time making sure the first couple of a employee days are positive. Because if you have a bad experience in the first two days, the attrition rate increases by 50% in the first 12 months.

We also don’t believe self-employment 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 built into the process, but it allows recruiters to do their job better with billions of data points they can act on.

II: How can businesses actively engage to get the most out of your platform?

BG: Turn allows them to understand what is going on with each position they have. For example, we work with a $10 billion company that hasn’t been able to fill a position for 10 months, and we were able to tell them why. We found that they offered a job title that was only used by the financial industry and that they were automotive. Thus, 96% of the candidates they identified were in the banking sector. We educated them on the titles they should use, 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 scattered and very difficult to aggregate. We can help companies answer hiring questions before they even start.

II: There is concern that AI could cause hiring bias. What is Turn doing to ensure this doesn’t happen on its platform?

BG: For us, this is all about ethical AI, that is, making sure at ground level that data is used correctly. The first step is to assume that you are going to get hacked and make sure no one can access the data.

The second step is to continuously test to ensure that there is no bias in the data. This is both an automated test and a manual test where we look at the areas we place people in and have set up alerts so that if the hiring data is skewed for a specific job , the system notifies us and we evaluate the reason.

We can track down to street level, basically. We know how diverse a zip code or city is, and if hiring starts to fall outside the norm, we dig to see what happened.

Companies need to have these kinds of procedures in place – you can’t set and forget AI because the model could be wrong and something could happen that you don’t know about.

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