Podcast: Beating the AI hiring machines – Texas News Today

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When it comes to hiring, it’s increasingly becoming an AI’s world, we’re just working in it. In this, the final episode of Season 2 of our AI podcast In Machines We Trust, and the conclusion of our series on AI and hiring, we take a look at how AI-based systems are increasingly playing gatekeeper in the hiring process—screening out applicants by the millions, based on little more than what they see in your resume. But we aren’t powerless against the machines. In fact, an increasing number of people and services are designed to help you play by—and in some cases bend—their rules to give you an edge.

We Meet: 

  • Jamaal Eggleston, Work Readiness Instructor, The HOPE Program
  • Ian Siegel, CEO, ZipRecruiter
  • Sami Mäkeläinen, Head of Strategic Foresight, Telstra
  • Salil Pande, CEO, VMock
  • Gracy Sarkissian, Interim Executive Director, Wasserman Center for Career Development, New York University

We Talked To: 

  • Jamaal Eggleston, Work Readiness Instructor, The HOPE Program
  • Students and Teachers from The HOPE Program in Brooklyn, NY
  • Jonathan Kestenbaum, Co-founder & Managing Director of Talent Tech Labs
  • Josh Bersin, Global Industry Analyst
  • Brian Kropp, Vice President Research, Gartner
  • Ian Siegel, CEO, ZipRecruiter
  • Sami Mäkeläinen, Head of Strategic Foresight, Telstra
  • Salil Pande, CEO, VMock
  • Kiran Pande, Co-Founder, VMock
  • Gracy Sarkissian, Interim Executive Director, Wasserman Center for Career Development, New York University

Sounds From:

Credits

  • This miniseries on hiring was reported by Hilke Schellmann and produced by Jennifer Strong, Emma Cillekens, Anthony Green and Karen Hao. We’re edited by Michael Reilly.

Transcript

Synthetic Jennifer: Hey everyone! This is NOT Jennifer Strong.  

It’s actually a deepfake version of her voice. 

To wrap up our hiring series, the two of us took turns doing the same job interview, because she was curious if the automated interviewer would notice. And, how it would grade each of us.

[beat / music]

So, human Jennifer beat me as a better match for the job posting, but just by a little bit.    

This deepfake? It got better personality scores. Because, according to this hiring software, this fake voice is more spontaneous.

It also got ranked as more innovative and strategic, while Jennifer is more passionate, and she’s better at working with others.

[Beat/ Music transition]

Jennifer: Artificial intelligence is increasingly used in the hiring process. 

(And this is the real Jennifer. Just, by the way.)

And these days algorithms decide whether a resume gets seen by a human, gauge personalities based on how people talk or play video games, and might even interview you. 

In a world where you no longer prepare for those interviews by putting your best foot forward—what does it mean to present your best ‘digital self’? 

Sot: Youtube clips montage: Vlogger 1: Want to know three easy hacks to significantly improve your performance on video interviews like HireVue, Spark Hire, or VidCruiter? Vlogger 2: Please do make sure you watch this from beginning to end, because I want to help you to pass your interview. Vlogger 3: And if you understand the key concepts, you can beat that algorithm and get the job. So let’s get started.

Jennifer: We look at just how far job seekers are willing to go to beat these tools.

Gracy Sarkissian: So there are all sorts of crazy stories about what students have done in the past to get their resume past the applicant tracking system. But what we do is we make sure that students know what to expect and are prepared to be successful. 

Jennifer: That success is measured by algorithms across a whole host of variables, from automated resume screeners attempting to predict an applicant’s job performance, to one-way video interviews,  where everything from a candidate’s word choice to their facial expressions might be analyzed. 

Ian Siegel: Literally this is one of those instances where conventional wisdom will kill you in your search for a job. And it’s such a shame because I think even many of the experts don’t realize how the industry is actually working today.

Jennifer: You can’t dress to impress an algorithm. So, what does it look like to game an automated system?  

Sami Makelainen: What if you  just had the AI interview an AI, could that be done? Could it be done now? Could it be done in the future? I mean—it’s fairly clear that in the not too distant future, you will have this kind of a much more common ability to develop artificial entities that look pretty much exactly like humans and act very much like humans. Or could we use one of these things to do the interviews for us? 

Jennifer: And in the absence of meaningful rules and regulation, where do we draw the line?

I’m Jennifer Strong, and in this final episode of a four-part series on AI and hiring we explore how we’re adapting to the automated process of finding a job.

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Anonymous Jobseeker: These AIs or artificial intelligent robots are reading resumes through a parser. So if your resume is not up to par, it won’t go through to the next steps. 

Jennifer: That’s the job seeker we’ve followed throughout this series. She asked us to call her Sally but that’s not her real name. She’s critiquing the hiring practices of potential employers… and she fears it could impact her career. 

In a previous episode, she told us how she applied for close to 150 jobs before landing one and how she encountered AI at several points in the process.

Like Sally, the first time you might see AI during a job search is with a resume parser, or screener. It sorts and chooses which ones get passed along to the next stage of the hiring process. 

She suspected her resume wasn’t getting through.

And she did some further research, after she got her hands on some of this technology.

Anonymous Jobseeker: So right now, when I put my resume through, it reads me as a software engineer, with a hint of data analysis, which is my field. So that’s fine. 

Jennifer: A friend of hers is also working on this problem. He’s testing a different tool that puts a percentage match on how qualified it judges each resume to be for a given job.

Anonymous Jobseeker: He has another parser where it gives you your percentage. So he’s been asking other people who are data scientists and already far in the field for their resume and theirs go through 80% to 90%.  

Jennifer: They’re even testing templates they find online, just to see what happens and if that formatting helps.

But so far, when they fill out those templates they’ve all received a low match score—under 40-percent qualified.

Anonymous Jobseeker: If you just Google resume templates, if you need help with your resume, we tested those whatever popped up. And we realized the templates aren’t good. So, when you put the templates inside the parser, no matter what job you are, you’re still at that 40 or under 40. So, there’s a problem with the machine reading it. 

Jennifer: Sally is a programmer. She knows how to go about finding and testing this type of software. But, most of us don’t. We’re unlikely to know if these algorithms are reading our resume in the way we intended, and extracting the ‘right’ skills.

Anonymous Jobseeker: If you fill out a job application online and it says convert resume. And if, once you convert your resume, if the boxes aren’t filled in to what your resume is stating, then you know, your percentage is low. And that makes a lot of sense because when I was applying to like Goldman Sachs or Capital One, like bank industries and stuff when I pick, take the, um, information from my resume, it was never correct. And I always had to fill in the rest of the stuff to match with my resume.

Jennifer: She says when she made this discovery, it finally clicked.

And she wishes she understood how this worked before she started applying for jobs, because it would have helped with her imposter syndrome.

Anonymous Jobseeker: So everybody that doesn’t know about this doesn’t have a chance, ‘cause they don’t even know.

Jennifer: Over the course of this reporting we found a number of different groups trying to get under the hood of these systems. Whether to help themselves, or others, adapt and engage with these tools.

And, we visited a workforce readiness program in New York City called The Hope Program. Many of its participants have dealt with homelessness, substance abuse and long-term…

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