Hilke Schellmann: Is Your New Boss a Robot?

AI isn’t just coming for your job — it might already be your manager. Trevor and Eugene sit down with investigative journalist Hilke Schellmann to examine how artificial intelligence has quietly infiltrated the workplace. From hiring software that analyzes your facial expressions to productivity trackers that monitor everything from your writing style to your bathroom breaks, Schellmann explains what these systems actually do — and what they get wrong. Do they eliminate bias, automate it, or just hide it better? And what happens to human work when the algorithm is watching? You won’t want to miss this episode.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:04Speaker 00

  What I have learned by bringing AI into the talent acquisition hiring space, I learned like how bad our old processes are, like job interviews, actually really bad. Because you are, it sort of filters out the people who are good about talking, about doing the job.

• 0:19Trevor Noah?

  As opposed to doing the job.

• 0:21Speaker 00

  So we have this competence versus confidence problem. Like people who will like come off as confident. We often think like, well, that person speaks so confidently about the, they must be really good. It turns out like that are more often than not men. And that doesn't mean actually they're competent. So we sometimes complain.

• 0:37Trevor Noah?

  Us men? No.

• 0:39Speaker 00

  Never.

• 0:40Trevor Noah?

  What?

• 0:41Speaker 00

  So, you know.

• 0:43Trevor Noah?

  Little old us, Hilka? No.

• 0:48Speaker 00

  As always, not all men, but a lot.

• 0:51Trevor Noah?

  Us little old men, acting like we know more than we do? Us? Come on, Hilka.

• 0:59Speaker 00

  Men explaining what?

• 1:08Trevor Noah?

  This is What Now? with Trevor Noah.

• 1:15Trevor Noah?

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• 1:50Trevor Noah?

  This segment is brought to you by Google Pixel. You know what's really frustrating? Knowing the exact information you need is somewhere on your phone, but still ending up wasting your time digging through five different apps just to actually find it.

• 2:05Trevor Noah?

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• 2:48Trevor Noah?

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• 3:30Trevor Noah?

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• 3:57Trevor Noah?

  Are you based here? Where are you based?

• 3:58Speaker 00

  Uh, yeah, I'm based at NYU, 20 Cooper Square. I live in Brooklyn.

• 4:02Trevor Noah?

  Okay. Oh, what part of Brooklyn?

• 4:03Speaker 00

  Greenpoint.

• 4:04Trevor Noah?

  Greenpoint.

• 4:05Speaker 00

  It's an old Polish neighborhood.

• 4:07Trevor Noah?

  Why did your voice go down when you said Greenpoint?

• 4:09Speaker 02

  Greenpoint.

• 4:11Speaker 00

  You caught me.

• 4:11Speaker 02

  Greenpoint.

• 4:13Speaker 00

  Well, it's very different. I've been in the same apartment for 16 years. It's been beautiful 16 years ago. It's still kind of beautiful, but the neighborhood is changing a lot.

• 4:21Trevor Noah?

  But isn't it becoming cooler and younger?

• 4:23Speaker 00

  Yeah.

• 4:24Trevor Noah?

  Oh, that's what you don't like about it?

• 4:25Speaker 00

  Well, I like that it was like kind of Polish and you walk into a store and people talk to me in Polish and I don't really know Polish. The only thing I know is like one line that's like "niemie spodzomie poposku" and that is really bad in Polish saying "I don't understand Polish", but I kind of like that.

• 4:40Trevor Noah?

  Wait, that's Polish for "I don't understand Polish"?

• 4:42Speaker 00

  Well, it's very bad Polish, I was told, but it was enough Polish that the Polish Realtor was like, "Whoa, I've never met a German who speaks Polish." I was like, "Well, I just said that I don't speak Polish." And it took me six hours from the train from Berlin to Warsaw to learn this one phrase, because Polish apparently is very hard. So I kind of like that about Greenpoint and that's like becoming exceedingly less. But the uptick is like, the beauty of it now is like we have beautiful restaurants.

• 5:08Trevor Noah?

  Yeah.

• 5:09Speaker 00

  So that's pretty cool.

• 5:09Trevor Noah?

  Yeah.

• 5:10Speaker 00

  Maybe I'm just getting old.

• 5:12Trevor Noah?

  I've never understood why people learn the phrase "I can't speak your language" in another language.

• 5:18Speaker 00

  Because they want to be polite.

• 5:19Speaker 02

  And I think first it's a test on yourself to see how much you can learn.

• 5:23Trevor Noah?

  Okay, but now think about this, think about what this says to the other person.

• 5:26Speaker 02

  Yeah.

• 5:27Trevor Noah?

  You've said to them in their language, you can't speak their language.

• 5:30Speaker 00

  Yeah.

• 5:31Trevor Noah?

  To me, what it shows me is you just don't want to speak my language because you've learned enough to say you can't speak it and then you won't learn the rest.

• 5:37Speaker 00

  No, I think that's a thing really polite.

• 5:39Trevor Noah?

  No.

• 5:40Speaker 00

  You're like visiting them and like you want to be nice to them.

• 5:42Trevor Noah?

  You've literally walked up to somebody and you, someone came up to you and they're like, "I don't speak English." And then you're like, "Well, you did a great job there." And they're like, "Hmm, that's enough for me."

• 5:55Trevor Noah?

  Think about it. You're like, "No, that's enough for me." That's good. Well, Hilka, welcome to the podcast.

• 6:01Speaker 00

  Well, thank you for having me.

• 6:02Trevor Noah?

  Thank you so much for joining us. This is like, you know, sometimes, and maybe, maybe it's confirmation bias. Sometimes you'll see a thing in the world that confirms the feeling that you're having and the idea. And like a lot of us will be like, "It's a sign, it's a sign." Literally coming here into the, into the studio today, I saw these posters that are all over New York. It's a little QR code. And it says, AI, who are the winners? Who are the losers? And it's a QR code and I don't know what's happening. And there's all these different ones everywhere. And then they say, is your job next? Is your job next? And it's all ominous. It feels like it's promo for a movie, but it's not, I think.

• 6:38Speaker 00

  So what is on this QR code?

• 6:39Trevor Noah?

  I'm not gonna scan a random QR code. This is how your phone gets hacked. I'm not gonna scan the QR. I was just, I just looked and I was like, yes.

• 6:47Speaker 02

  I wish I did.

• 6:48Trevor Noah?

  I was like, we're talking to the perfect person today because you have dedicated more time in your life than most people into answering this question, like basically like, who are the winners and who are the losers? So like, before we delve into it, like if you were to explain to somebody who you are and what your passion is in and around the topic of AI and how it relates to work, how would you introduce yourself to them?

• 7:11Speaker 00

  Oh, wow. I guess I feel like, you know, I'm an investigative journalist and I have, you know, I used to investigate all kinds of things and now I just investigate AI. And I'm trying to understand like, how does it work in society? And maybe who are the winners and the losers? But also like, you know, I really think about like, well, it's changing the world of work. And I saw it eight years ago, starting. And I was like, oh, I don't know if people are aware of this and somebody needs to look into it. And there was kind of nobody else there who was like looking into it. So I was like, might as well look into it. I'm just driven by like sort of curiosity and I'm like, what is going on here? So now it has a little bit involved. Like I investigate AI, not only AI and hiring and in the world of work. I also build AI tools. I think about like how journalism will be impacted by AI

• 7:55Speaker 00

  and how we can maybe save journalism or a factual based society. And everything can be generated. So those are kind of things and questions that I think about.

• 8:04Trevor Noah?

  I love the idea of being an investigative journalist, doing everything and then focusing on one thing. Cause then it makes me go, what was it about this one thing that you thought supersedes everything else? Like what, all the other topics you were covering before this?

• 8:16Speaker 00

  Yeah, I mean, I covered, you know, like violence against women in Pakistan. I went to Pakistan. I looked at like South Asia. I did all kinds of things. And I don't know, I had like one Lyft ride in 2017 in the fall. I was in Washington DC. Trying to get from a conference that has nothing to do with AI to the train station. I got in the back of the car and asked the driver, how are you doing? And he said, I've had a weird day. In the history of me taking lifts, no one has ever said that. And I was like, really? Well, what happened? He's like, I had a job interview by a robot with a robot. And I was like, what? A job interview with a robot? He's like, yeah. You know, he had applied for a baggage handler position at an airport, and he got a call from a robot that asked him three questions. And he was really weirded out.

• 9:01Speaker 00

  This was in 2017. So we are, you know, light years further down the road of AI now. But I was like, I have never heard of this. So I started looking into it. And here we are. And then I went to a conference and I was like, wait a second. There are all these like AI vendors in HR and like it's being used everywhere. And no one talks about it. And whoop, down the rabbit hole I went. And somehow it never, it doesn't let me go. I'm thinking about like the next four books on AI, the next research studies on AI. It just doesn't, I don't know how I, I don't know. I'm very, I'm very bad at predicting the future. But I could tell that this is like a transformative technology that we need to pay attention to. And not only how the technology work, but it's like societal implication. What does this mean if we use AI in hiring? What is it?

• 9:46Speaker 00

  What are the consequences of this? If we use it in journalism, how does our world change? Or maybe not change? And how does it improve the world or maybe not? And I was surprised that

• 9:57Speaker 00

  there isn't maybe a whole lot of improvement as we wish it would be, at least in hiring. So I think that was a little bit surprising sadly. That when I first saw, like the first time I went to a conference and somebody was explaining how they do like emotion scanning on their faces and like checking the intonation of your voices to find out if you're going to be good at a job and like the words that you say. And I was like, wow, who knew that like facial expression in a job interview could be predictive of your success at a job? Like what, what a way, like a new way of science. And then, you know, we trust but verify as a journalist. So I trusted that information. And then I went on to verify it and talked to a lot of experts who were like, what? Emotion on faces? Like that doesn't exist to predict how good you are at a job.

• 10:42Speaker 00

  No ways. I was like, oh, that's too bad. Um, intonation of our voices, we can't really tell what kind of emotions you have. Like, we can sort of like make a prediction, but that's not always really the case. Like, you know, it's kind of like when I'm in a job interview and I say I'm nervous and, uh, sorry, uh, when I'm, when I'm in a job interview and I smile and people, you know, facial, uh, emotion scanning algorithm would say like, oh yeah, she's totally happy. She's smiling. And I'm like, I'm fucking nervous. I'm not happy in a job interview. Who in the world has ever been happy in a job interview? Uh, so that's kind of like, you know, it is a prediction, uh, but we're using it to like, sort of select people.

• 11:23Trevor Noah?

  It's just like your intuition, from what I hear, it's like your intuition as an investigative journalist was basically to say, there's something deeper that's happening here. There's a world, do you know what I mean?

• 11:32Speaker 00

  Yeah, totally. And we, somebody has to look into it. And for some reason, it just sometimes happens to be me who's standing right there. So I have to like, take it on. It's like, you know, when the, when the, uh, chairwoman of the Equal Employment Opportunity Commission, when I was talking to her about AI and hiring, and she's like, yeah, I do wonder. Now we have these like one-way video interviews and, and, you know, the, the companies use the recording, run them through a transcription service, like speech-to-text transcription like you have on your phone. Uh, and then the AI predicts upon that transcription. And she was like, I wonder how good the transcription software works for people with accents, people with speech disabilities. I'm like, yeah, totally. And you have like a federal agency. You should totally look into that and study that. And she's like, oh yeah, I don't know. And I was like, okay, there's no one here.

• 12:14Speaker 00

  So I started to study it with the help of a research team, a computer scientist, sociology professor. I don't do this work alone. Um, but, um, yeah, so that's kind of the work that I do.

• 12:25Speaker 02

  You know, the more you speak, I realize this is how it sounds like whenever I speak to Trevor about technology. He knows so much about technology. I only know how to send texts.

• 12:33Trevor Noah?

  But you send them very well.

• 12:35Speaker 02

  Very well. Sometimes I send pictures as well with those texts. And then emoji, don't get me started.

• 12:41Trevor Noah?

  You know, I've actually never heard you talk about AI, now that I think about it.

• 12:44Speaker 02

  Never. Because also I don't understand how much of it is in my life. And I don't also understand how much it scares people. So I'm even scared to ask people, what is it about AI that scares you? Because I don't interact with technology that much. So how would you explain to me what scares people? And how much I've been using without even knowing I've been using.

• 13:03Speaker 00

  Yeah. Um, but we use it in everyday life. Do you have a spam filter on your email?

• 13:07Speaker 02

  Nix.

• 13:09Speaker 00

  Well, you know, it's like sort of the rise of AI has been everywhere, right? And it's really like software, really, what it comes down to. It's just sort of like maybe software and steroids. It does things better than we used to where we say like, oh, if this, then do this. Like we have our self learning tools that can sort of do translations from, you know, we could now be talking in German or French and an AI could just translate that in our voices and an AI can generate that. So we see it kind of everywhere, moving into everything.

• 13:49Trevor Noah?

  That's crazy. Like, so wait, you're saying with the technology now, out of nowhere, we can just go from speaking English and then we just switched into another language? In real time. In real time?

• 14:01Speaker 00

  I don't know if it works in real time, but we can definitely do it.

• 14:03Trevor Noah?

  Das ist unglaublich.

• 14:04Speaker 00

  Yeah.

• 14:05Trevor Noah?

  Und dann du sprichst Deutsch und dann Eugene spricht Deutsch, du auch?

• 14:08Speaker 00

  Yeah, ich spreche auch Deutsch. Sie sind so gut, geht das AI? Okay, you now have to emulate the AI.

• 14:14Trevor Noah?

  I fucking nothing.

• 14:17Trevor Noah?

  You know, your book, your book really, I think, shook me up in the perfect ways because you've written extensively about the world of AI. And what I wanted this conversation to do, because I try to talk to people like Eugene, funny enough, who I realize don't have the handle or like the passion for tech that I have, you know? And sometimes I think if you love tech too much, you're just focusing on like the tech side of it and you're like, wow, the engineering.

• 14:44Speaker 00

  The new tech, yeah.

• 14:44Trevor Noah?

  And then when I speak to a person who's not into tech, they just go like, wait, wait, wait, wait. What does it do for me? What does it do against me? And how do I need to think of its role in my life? And your book really broke it down because one of the first things I noticed about your writing is

• 15:01Trevor Noah?

  AI is fundamentally gonna change what the word job means. Do you know what I mean? Like, like, job has constantly had like evolutions over time. Like, people used to go like, a job is this, and you don't like, it meant using your hands. And be like, that's not a job. And the first people on a computer or thinker, they're like, that's not a job. And then now people go, that's not. But fundamentally, from everything I've seen you write, and obviously, everything that's happening in the world. It seems like job itself is gonna change. What have you found in, in your investigations on like, how AI is changing? What jobs actually are or aren't, like in different fields, lawyers, doctors, etc.

• 15:37Speaker 00

  Yeah, I mean, I think we already see some of it coming down.

• 15:44Speaker 00

  You know, we see, we, we already see some of the consequences of like AI infiltrating our, our daily lives. We see a lot of, way less like sort of early career hiring. Cause I think a lot of times people who use AI a lot sort of describe it as like, oh yeah, I have like a little intern with me. Who does like a lot of jobs for me, right? Like, they can write code for me. They can do, you know, you can generate a research report of stuff that I need to know. Like, I can generate emails, newsletters, like stuff that I have to write.

• 16:11Trevor Noah?

  And these were all the, these were all the early jobs that people would.

• 16:14Speaker 02

  Set my calendar, book my flights.

• 16:15Trevor Noah?

  Yes.

• 16:15Speaker 00

  Yeah.

• 16:16Trevor Noah?

  Remind you of stuff.

• 16:17Speaker 00

  Yeah, totally, totally. It can, it can do a lot of that. You know, we're still thinking about like, still are looking into like agentic AI. Can it really book the best flight for you that you want? You know, we're still working on that, but can definitely help you like generate research, doing math problems, all kinds of things. So I think we, we see a lot of companies already moving towards like, oh, having fewer headcounts. And sort of like, I worry a lot about like, what is, how is this pipeline gonna break of people? Doing like, early entry jobs. How they're gonna get the expertise and the wherewithal to like move up if we sort of take out the, the first layer of jobs. Maybe just to like upskill people and.

• 16:56Trevor Noah?

  But how do we, how do we, that, that seems to be the conundrum, right? Is law firms, most of the people who start out in a law firm, start out, they've got their law degree. They go and work at a law firm and it sounds like your job is just to like go through the paperwork and do the research and write up briefs and do this. But you're working for someone, but in that process, you're learning. And they're teaching you what they're looking for and they're trying to. But if we cut off that level. Then where does the expertise come from?

• 17:23Speaker 00

  Yeah.

• 17:24Trevor Noah?

  Because we say upskill, but then who is doing the up of the skill?

• 17:26Speaker 00

  Yeah, yeah. I mean, I think it's like sort of, you know, what I sometimes fundamentally think of, and you know, we don't have all the answers yet to some of these questions, if I may say that. It's like, sort of like, what stays as a human in the age of AI, right? If like, AI can do sort of what we think is like very human.

• 17:45Trevor Noah?

  Yeah.

• 17:46Speaker 00

  Things like if AI can write better than I do, how can I express myself? Like, and what does it mean for humans in a world of AI? Like, what do we bring to the table now that AI can do so many things for us?

• 17:59Trevor Noah?

  Don't go anywhere, because we got more What Now? after this.

• 18:05Trevor Noah?

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• 18:50Trevor Noah?

  Yeah, one of my favorite YouTube Premium features is smart downloads. Because how many times have you gone somewhere and realized, "Ah, I forgot to download anything." And now you're on the way to the airport and you're like, "Download, download, download, download." You're on the plane, "Download, download, download, download." There's no Wi-Fi. "I wish I downloaded." Now, all of those things that you were gonna watch are just on the internet. Smart downloads basically thinks ahead for you. It automatically downloads recommended videos based on what you like to watch. So even when you forget to prepare, YouTube Premium didn't. I love it. It's like packing for a trip and discovering somebody already remembered the thing you always leave at home. It's always the underwear. If you like YouTube, you'll love YouTube Premium. Sign up now for your free trial at youtube.com/premium.

• 19:35Trevor Noah?

  Terms apply. Cancel anytime.

• 19:38Trevor Noah?

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• 20:23Trevor Noah?

  apple brown butter cookies, and chocolate bourbon pecan pie. And with no artificial sweeteners like sucralose, artificial colors like red dye number forty, or high-fructose corn syrup store-wide, nothing gets in the way of the flavors you came for. Shop fall flavors with higher standards at Whole Foods Markets. Earth can be a lot sometimes: heat waves, gas prices, bad hair days. Why not go where life is good? Escape to Pluto TV. Turn off your problems and turn on your favorite movies and shows. You know, the ones you already love. From Anchorman, The Legend of Ron Burgundy, to Dirty Dancing, to Top Gun Maverick,

• 21:04Trevor Noah?

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• 21:22Trevor Noah?

  In the job space, actually, I would love to know, like,

• 21:25Speaker 00

  Yeah.

• 21:26Trevor Noah?

  You've done a lot of investigating, and I want to get into some of the stories because I think people will be fascinated by how humans have been affected by AI already. Is there like a concrete number on how much hiring is actually done by AI now and how much is human? Because a lot of people out there, if you told them, "Oh, hey, your job application, your CV, your resume, whatever you type up, it's not even seen by a human in some companies."

• 21:50Speaker 00

  Not?

• 21:50Trevor Noah?

  Yeah, nothing.

• 21:51Speaker 00

  Yeah, sorry. So we think about like-

• 21:53Trevor Noah?

  How do you think you got here? You think if I knew you were coming, you'd be here?

• 21:57Speaker 00

  If I looked at your resume.

• 21:57Trevor Noah?

  This was AI.

• 22:01Speaker 00

  You now have to say it was like shitty AI or something.

• 22:06Speaker 02

  This freaks me out at every, at every turn. Wait, wait. So someone applies for a job.

• 22:10Speaker 00

  So you like upload your resume or you don't even have it uploaded. Like you already have it on LinkedIn and you just hit the one click. Yeah.

• 22:17Speaker 02

  To the company I'd like to work for.

• 22:19Speaker 00

  Yeah. So like all of these big platforms, they all use some form of AI. That I can tell you. We don't have like a central register where companies have to register and say like, we use this AI tool or not. We just know this from surveys and sometimes me calling companies. So I know that they use AI. So you have to think about like the beginning of the hiring process. You often have thousands of people applying for a job, right? We call this like sort of a big funnel. And some companies, you know, this is a couple of years old, but I talked to Google, they get over three million applications. IBM gets five million, over five million applications a year. So it's a lot of resumes that come into this funnel. So what we now see is like a lot of companies and usually large companies, a lot of Fortune 500s,

• 23:00Speaker 00

  use AI to reject people, to sort of cull the herd of all these applicants. And like, so we see in the early stages, rejection, rejection, and like a few people going on the yes path for AI and then, you know, doing like one way video interviews. And now we have video avatars interviewing people.

• 23:18Trevor Noah?

  Just break down, what is a one way video interview? Cause I think a lot of people, I didn't know what that was until I read your work.

• 23:22Speaker 00

  Yeah, totally. Yeah, I hear you. I've done so many.

• 23:24Speaker 02

  Until 30 seconds ago. What are you talking about?

• 23:27Trevor Noah?

  No, but I didn't know.

• 23:27Speaker 02

  Me?

• 23:28Trevor Noah?

  Yeah.

• 23:30Speaker 00

  So like a one way video or audio interview, like, you know, there's now a traditional way to do this, which is like six or seven years old, where you don't have anybody else on like, you know, you kind of lock in, you get a link, do this video interview if you want the job in the, in the next 48 hours. So you click the link and then instead of a human on the other side, it's on a Zoom call. You just like get maybe a video of somebody saying, hey, welcome to company X. We're so delighted you are here. We have a couple of tests for you. And then you get a question like, what are your strengths and weaknesses? Why do you want this job? And then you tape yourself, basically you get like a couple of minutes of prepare. And then you tape yourself like saying like, my strength and my weakness is this.

• 24:10Speaker 00

  And then I think all of the applicants I've spoken to think that like a human watches all these videos, bless their hearts if they do, and some companies actually do have humans watching all of these, but some companies also use AI to rank people and do that. So we see that more and more, and we see this often, like entry level jobs, we see this in like retail companies, fast food, like it's called high turnover, high, no, high volume, high, I don't remember. So it's

• 24:43Trevor Noah?

  Jobs, jobs that generally have people where people are coming in quickly and leaving quickly.

• 24:47Speaker 00

  Exactly.

• 24:47Trevor Noah?

  Like they're not gonna be, it's not a career job. So people are going

• 24:50Speaker 00

  Sometimes it's a career job.

• 24:51Trevor Noah?

  Oh, but it's just like high turnover.

• 24:52Speaker 00

  But it's a, it's a high turnover, or you have like lots of candidates that you have to go through.

• 24:56Trevor Noah?

  Okay, got it, got it.

• 24:57Speaker 00

  So for example, like Goldman Sachs said, a few years ago for their summer internship, they had like over a hundred thousand applications. So they have to like go through these applications and like narrow down the pool. So you use like resume screening AI, you use like video interviews.

• 25:13Trevor Noah?

  Yeah, yeah, yeah.

• 25:14Speaker 00

  You can use games. We see like personality, these games are supposed to find your personality while you're clicking on balloons, pumping up balloons, they find your personality, all kinds of ways to assess you without maybe putting in a whole lot of work because humans are expensive to do this work. And also, sorry to say this, but a lot of humans, they do suck at hiring because we have bias, we have human bias.

• 25:39Trevor Noah?

  But that's, so now that's a conundrum.

• 25:41Speaker 00

  I suck at hiring.

• 25:41Trevor Noah?

  But this is the conundrum though. So, so, so this is, this is the thing that's like weird now just for this part of it is my reflex, my reflex, when I hear something like that is to go, oh no, this is, this is not good. How can you have AIs screening people's interviews? And but then on the other hand, I go, if you have a hundred thousand people applying to a job. Let's be honest. I don't think there's any human who's gonna get through those hundred thousand application. I don't think there's any humans. And I wouldn't be shocked if there were like a bunch of humans who were skipping through this before, because they were just like, it's like auditions in a way. At some point, the person's tired.

• 26:16Speaker 00

  Yeah.

• 26:16Trevor Noah?

  You know, you want to get them when they're fresh. You want to get them when they're in the mood.

• 26:20Speaker 00

  Yeah.

• 26:21Trevor Noah?

  And I wonder, is there a world where, like, does the AI make it better then?

• 26:27Speaker 00

  You know, I wish I could tell you that.

• 26:29Trevor Noah?

  So we don't know.

• 26:30Speaker 00

  We don't know. I've asked many, many companies to let me come in as a researcher and like sort of look at like, here's your traditional way of hiring. Here's your AI hiring.

• 26:40Trevor Noah?

  And what do they say?

• 26:41Speaker 00

  Run it both times and then sort of double check, like, you know, the people that they I said that would be high performers, did they actually turn out to be high performers? And I have not seen a company do this or want to share this with me or with anyone. I think it's because, I don't know, there's like a lot of turnover in HR, like these processes don't work that that well. And I think what we already know, so what we know from a survey of C-suite leaders, like sort of leadership in companies of over 2000s in Germany, the UK and the US. When they asked them, if your company uses AI tools, do they reject qualified, do they reject qualified candidates? And almost 90% of the leadership said yes.

• 27:25Speaker 00

  So they know that their tools reject qualified candidates. They still use it because I guess the efficiency from using AI versus humans, it's just much, much more greater. But it's not that we know that one process is better than the other. I mean, we do know that like humans are very biased in hiring and even the best anti-bias training is not going to get out of it.

• 27:47Trevor Noah?

  Yeah.

• 27:48Speaker 00

  And, you know, we all know the shortcuts, right? If you see somebody on your resume that they went to Harvard, you're like, oh, they must be smart. No.

• 27:54Trevor Noah?

  They're not.

• 27:57Speaker 00

  Well, we know from social signs.

• 28:00Trevor Noah?

  This episode, you Jim Cozak learns about the world. She's like, wait, what are you telling me?

• 28:08Trevor Noah?

  But, but, but you go, you know, so this, this is, this is, this is where I feel like we stumble on the, on the first conundrum. Generally, generally, machines like predictability.

• 28:17Speaker 00

  Yes.

• 28:17Trevor Noah?

  Right? Algorithms like predictability, that's what an algorithm is fundamentally sort of trying to do.

• 28:23Speaker 00

  It finds like patterns and, you know, yeah.

• 28:25Trevor Noah?

  And a pattern is a predictability.

• 28:26Speaker 00

  Yeah.

• 28:26Trevor Noah?

  Right? The conundrum or the paradox of being human is that the biggest breakthroughs that have come from humanity have often come from the pattern breakers. The person who didn't think correctly, the person who didn't fit the algorithm, the person. The outlier. Yeah, the outlier. So I wonder, I wonder if companies in moving all of their resources towards efficiency and pattern recognition might go the opposite direction of innovation. Because it's like, it's almost like the misfits and the mistakes are sometimes the ones who give you the biggest flips. Do you know what I'm saying?

• 29:00Speaker 00

  Yeah, yeah, yeah, totally.

• 29:02Speaker 02

  I feel like the solution has caused a problem. Well, we were speaking about how many people had applied to Goldman Sachs. And I think if it wasn't for technology, would you still get that many applications?

• 29:13Trevor Noah?

  That's interesting.

• 29:13Speaker 02

  Would a hundred thousand people from all over the world show up at the address to put in their resumes? So I think technology also allowed easy access. Because I also think there's people who know they don't qualify, but would do it anyway. So why would you put a human through all of this? But also, I think it's a box ticking exercise for some companies as well. I think some companies don't want to hire anybody, but they'll just put out a thing that says, we want to hire somebody. Then they'll end up doing the internal process anyway, because if you're going to trust people with people's monies and files and information, you'd want someone that you know. So I think companies know exactly what's going on, but they're just sending out hope. And I think once you advertise a job, it's a great way to advertise your company as well.

• 29:51Speaker 00

  Yeah, yeah. I mean, sort of like people online, you know, they, they often joke because obviously some people obviously are very aware that companies use AI. And now a lot of, you know, I think, I think it felt very like passive and, and, and sad for a lot of applicants until sort of L L M's and chat G P T and other AI came around where now it's like much easier for, for me as an applicant to generate a resume. There's actually now.

• 30:15Trevor Noah?

  So now it's AI warfare.

• 30:17Speaker 00

  Yes, it is AI versus AI.

• 30:19Trevor Noah?

  I'm going to use, I'm going to use the AI to apply for the job. They're going to use the AI to grade me. I'm going to use the AI to pass the grades.

• 30:26Speaker 00

  Exactly. I'm going to try to use AI to like outsmart the AI. There's actually AI programs that now apply for you. And so you don't even have to do anything. And so there's all kinds of stuff, but like the question is like, well, what are we then doing here? Like.

• 30:40Trevor Noah?

  Yeah, like what are we?

• 30:40Speaker 00

  Yeah. What are we doing? That is, that is a great question.

• 30:43Trevor Noah?

  That becomes the question. What are we doing? Because if the AI is hiring the people who are using the AI to get the job, that the AI has hired the people. Then we, that's what I mean is like, we have to ask the fundamental question. Wait, what was the point of this process in the first place? Because multiple studies have shown humans are terrible at predicting the future, especially when it comes to hiring, right? A lot of the time when you're hired, you're hired because the person sitting across from you saw something in you that they considered correct for the company. But a lot of the time, it's just wrong.

• 31:18Speaker 00

  Yeah.

• 31:19Trevor Noah?

  You know what I mean? It's just, it's wrong. And then people don't do well. And they go like, well, that, that didn't work, but, but the, the prediction is wrong.

• 31:25Speaker 00

  Mm hmm.

• 31:26Trevor Noah?

  You know what I'm saying?

• 31:27Speaker 00

  Yeah.

• 31:27Trevor Noah?

  And so now, I almost feel like we, we forgot what the whole point of an interview was. Like, I, I'm not a historian, but if I was to bet, I would think an interview was just to be like, let me see what your vibe is.

• 31:38Speaker 02

  It was a vibe check.

• 31:39Trevor Noah?

  It was a vibe check.

• 31:39Speaker 00

  Yeah, but it turns out like vibe checks, not so great, actually. Like, because you.

• 31:44Speaker 02

  At predicting who's a good employee.

• 31:45Speaker 00

  Yeah, but, but also like a vibe check is like finding people who like, like are often like, have the same background as you, they speak like you, they vibe with you.

• 31:54Trevor Noah?

  Exactly.

• 31:54Speaker 00

  So you find the same people again.

• 31:55Trevor Noah?

  Yes.

• 31:56Speaker 00

  Um, but you know, we kind of know that like diversity is good for companies. Um, also like, I mean, I think that's why we have, uh, you know, fewer women, people of color in leadership, uh, positions, because we have underestimated them as humans in hiring for decades and, and, and promotion decisions. So we have like, uh, sort of, uh, a lack of diversity already because of human bias and sort of the vibe.

• 32:17Trevor Noah?

  Yeah, the vibe.

• 32:18Speaker 00

  You know, when you come to a job interview, you want nothing more but like somebody, you know, like the HR manager or the hiring manager to like you. And then you start talking about like, well, what school did you two go to?

• 32:28Trevor Noah?

  If you walk in wearing the same shirts, oh, boy, it's on.

• 32:31Speaker 00

  You like this, you like this, uh, you know, uh, sports team, yada, yada, yada. And that chit chat feels like very good for humans to make a human connection.

• 32:38Trevor Noah?

  Yes.

• 32:38Speaker 00

  But it's actually really bad, uh, cause that brings the bias in. Because now as a hiring manager, I'm like, oh, man, you went to the same school as me. It's so cool. I see you in a completely different light than other people. And I'm supposed to look at like, what are the capabilities and like, uh, your skills that you need for the job? Not if you went to the same school, but we as humans do that. And that's where like a lot of the bias, uh, comes in. The unfortunate thing is you might think. Well, AI is like a pattern machine that just finds patterns, right? And it will just look at your like capabilities, your skills and find the most skilled person. But what we've seen in some of the AI tools, when I talk to lawyers and others who get access to these tools, when like an AI provider, you know, they built the tool and AI vendor and a company may use their tool.

• 33:23Speaker 00

  Sometimes they bring in lawyers and do their due diligence, like, how does this tool work? And what they found out is when the lawyers looked at it, that the tool used, some of these tools use kind of problematic keywords. So for example,

• 33:37Trevor Noah?

  Oh, there's the Amazon story that you wrote about.

• 33:40Speaker 00

  Yeah, the Amazon story is one of them. So this was, this was like if you had the word woman or women

• 33:46Trevor Noah?

  Yes.

• 33:47Speaker 00

  on your resume, you got downgraded because, you know, the, the, the tool had learned over time. You know, you, you give it resumes of people who currently work here or who maybe made it to the last round of hiring, sort of labeling them as these are the successful people. Well, if you work in a tech company and you probably have a gender disparity already, built in from maybe previous bias, you kind of replicate that, right? The people who are in the role use their resumes, the machine does what it does best. It looks for patterns and it finds out, wow, women are less successful here. So we should downgrade them in the hiring process.

• 34:23Trevor Noah?

  Yeah, there were some applications in the story where Amazon was hiring people.

• 34:31Trevor Noah?

  And their system basically went on its own, doing its job as it had been told. And it went, oh, I've noticed women's soccer team, women's baseball, women's anything does not match with the people who are currently at the top of Amazon.

• 34:47Speaker 00

  They don't have that word on their resumes, basically.

• 34:49Trevor Noah?

  Exactly. So this person is less likely to be like that person. So we're going to downgrade that. But this had nothing to do with your actual qualifications.

• 34:57Speaker 02

  Wait, did AI do that or did someone who put the input to the AI do that?

• 35:01Trevor Noah?

  No, AI did that.

• 35:02Speaker 00

  No input. This was, this was a release. Yeah, you have to think about like, you know, sort of present day AI. What we do is like, we give the AI just the data we have and have it like, we call it unsupervised learning, have it like, figure out what do these people have in common and who should we hire?

• 35:18Trevor Noah?

  The best fit for here.

• 35:19Speaker 00

  So, yeah, so it looks at like, patterns in the, the, the resume lake that you give it, and I guess it scans all of the words, and then, then it does what it does best. It does a pattern analysis and finds out, you know, one other example was like, if you had the word Thomas on your resume, you also got more points.

• 35:39Trevor Noah?

  If you had the word what?

• 35:40Speaker 00

  Thomas.

• 35:40Trevor Noah?

  Thomas?

• 35:41Speaker 00

  Thomas.

• 35:41Trevor Noah?

  Like the name Thomas?

• 35:42Speaker 00

  The name Thomas. Or like, in another case, it was like, words like Syria and Canada.

• 35:48Trevor Noah?

  What, those got you up or down?

• 35:50Speaker 00

  That got you up, actually.

• 35:51Trevor Noah?

  If you had Syria and Canada.

• 35:53Speaker 02

  If you had the combination, you were hired.

• 35:54Speaker 00

  Yes.

• 35:55Trevor Noah?

  Wait, wait, but now, but now.

• 35:56Speaker 00

  If your name is Thomas, I'll top it.

• 35:57Speaker 02

  From Syria via Canada.

• 35:58Trevor Noah?

  Yeah. So here's my question, though, does that mean that people could, are there tricks that people could use now? So if I was writing a resume today, could I just write somewhere randomly?

• 36:10Speaker 00

  Syria, Canada.

• 36:11Trevor Noah?

  Passions, reading about Syria, uh, Canada, I like it.

• 36:16Speaker 02

  Maple syrup.

• 36:17Trevor Noah?

  Thomas, you know what it is?

• 36:19Speaker 00

  Thomas, Thomas, Thomas, Thomas, Thomas in white.

• 36:21Trevor Noah?

  Thomas, Thomas, Thomas, and then, and then.

• 36:23Speaker 00

  Well, so I think the, the problem is that like, most tools are like individually calibrated to each company, so.

• 36:29Trevor Noah?

  So I could, I could only get hired at Amazon by doing this?

• 36:31Speaker 00

  Well, Amazon had that women's problem, but they say they changed that. They also say that their machine learning algorithm was never used solely to make hiring decisions.

• 36:42Trevor Noah?

  But no one would say that it was.

• 36:45Trevor Noah?

  Like, I mean, which company would be, I don't think I've seen a single story where a company has come out and said, yeah, man, we were just using a computer to choose who was coming here. All of them go like, no, no, this was not the only thing. This was merely a pilot program that determined.

• 36:59Speaker 02

  You know, the more you guys talk, the more I realize. Are we, are we under, you're a journalist, you know this, are we underplaying the role that biases have played in our lives? People choosing whatever it is that represents a certain group of people or a company even, based on what they think the taste of the, of the population or demographic is? Do you understand what I'm saying?

• 37:22Speaker 00

  Yeah, yeah, yeah. So, so you're thinking generally or in the hiring process?

• 37:26Speaker 02

  Not in the hiring process. Because if you're gonna work for a company and the person sits there goes, I think you'd be great here because of what, what, what?

• 37:32Trevor Noah?

  Yeah, yeah, yeah.

• 37:33Speaker 02

  Now, we are going, because I think biases always, and I could be wrong, always comes in when we speak of race, gender, or religion. Once you've ticked those three boxes, we're like, yeah. But how many places have we gone to where there's that mix because of someone's biases who decided maybe people who are six foot with muscles should be in construction and because they look like this, they sound like this, they talk like this, actually they'll be great for this job? So how many, how many of us are beneficiaries of biases?

• 38:01Speaker 00

  I think, I think a lot of us are beneficiaries and a lot of us also have been sort of the victims of bias and probably unbeknownst because, you know, you go in for, for a job interview or you, you, you send in your resume and most likely is you get rejected, right? Because there's only so many jobs at the, at the, that are being given out. So the question is like, were you rejected? And I think most of us humans think, oh, well, I was rejected because I wasn't the most qualified candidate. Well, it might have been that you've been rejected because your name is Thomas. Or in one actually instance, there was the word African American that was used to weigh resumes. In another instance, there was, if you had the word baseball on your resume, you got more points. If you had the word softball on your resume, you got fewer points.

• 38:46Trevor Noah?

  Damn.

• 38:47Speaker 00

  So that's probably gender discrimination, right?

• 38:49Trevor Noah?

  I would give you, I would give you zero points for both. In my company, I would be fair. You say baseball, you say softball, I would detract the points.

• 38:57Speaker 02

  But Trevor, do you see how it circled back? How those?

• 38:59Speaker 00

  And this was not a baseball position.

• 39:01Trevor Noah?

  No, it really does.

• 39:01Speaker 00

  The question is like, you know, like, does it have to do with baseball?

• 39:04Trevor Noah?

  Yeah, this has not even in baseball. But no, you know, you know what? Whoa. In a, in a way, I know this, this is gonna sound like a little crazy, but like, I can sort of understand these ones. And when I'd read the examples in your work, I would go, this sort of makes sense. I can see where they've made a mistake here and they can rectify it. But there are some examples that you've given that that blow my mind. For instance, there's one, there's one story that you go into of a guy, I think by the name of Mike. And he's like working for Bloomberg or he's like working, trying to get a job at Bloomberg or something. And please help me understand this because from what I understood, I'll say it and then you let me know if I'm right. Or if I, he had to play a game like Candy Crush type stuff of popping balloons.

• 39:48Trevor Noah?

  And then he got fired because of how he popped the balloons?

• 39:52Speaker 00

  He didn't get fired, but he did apply to a job.

• 39:55Trevor Noah?

  Okay.

• 39:56Speaker 00

  He was based in Barcelona and and and play and he was based in Barcelona and applied to a job in in London. And he got a link immediately after applying saying like, hey, go to this link. And you know, I I sort of feel like we as job applicants, we are sort of forced consumers of this tech, right? Because if you want the job and you get an email with the link saying like, hey, you have forty eight hours. Click on this link, play this game. What are you gonna do? You're gonna do it. Even though you were like, and he was like, while he was doing it, he was like, this is where you're.

• 40:26Trevor Noah?

  It sounds like the beginning of a horror movie. Do you wanna play a game?

• 40:29Speaker 00

  Why do I have to do this? Like, it sounds great. And I think a lot of applicants technically like it better than answering hundred questions about like, are you the life of the party? Like, I rather pump it balloons. But when you realize, wait, is this the only criterion I'm gonna be judged on how well I like pump balloons? Or like, in in in in one of the games, I had to hit the spacebar as fast as possible. And while I was doing that, I was like, you get like fifteen seconds or so to do that. And I was like, what does it have to do with the job? Like, in what jobs do you have to hit the spacebar as fast as possible?

• 41:00Trevor Noah?

  Maybe it's like a company where like, there's like big gaps between people's names. Maybe there's like, maybe you're working at a company where it's like suspenseful pause incorporated. Maybe it's like. I mean, I want to know what this job is now, where somebody out there is just like,

• 41:14Speaker 00

  Yeah.

• 41:15Trevor Noah?

  Maybe it's a company, maybe it's a company that had to cut costs because all the enters, the enters on the keyboards were broken. And now they have to hire people who can use space to get to the next line. Because you can't just press return. You can't just press, come on, come on. And then that boss is like, you know, we need, we need people who can press the spacebar. Get me the fastest spacebar presses in the world.

• 41:36Speaker 00

  We found them, we found them. But you know, I mean, what's interesting like that, actually, that suite of games was, was used by like multinational companies around the world.

• 41:44Trevor Noah?

  Like, we're talking like legitimate, not some random company. You're saying this is used by like big name companies. How fast can you press a spacebar?

• 41:53Speaker 00

  And that is one of the many games that you have to, have to, have to play. And you know, they say they're not actually like looking at your capabilities of hitting the spacebar. It's like finding out how much like, you know, how risk averse you are, like what your personality is underneath this. Like, are you somebody who likes challenges or not? I guess.

• 42:11Trevor Noah?

  Who takes any order that you're given. I'm sure even the, the time between you deciding are you going to press the space button or not, actually maybe counts. Oh, that's interesting. Did you really think about this instruction?

• 42:22Speaker 00

  I don't, I don't know if that counts, but I did talk to industrial, um, industrial organizational psychologists, uh, who said, yeah, we looked at all of those things. And actually, the people that take longer, um, until they start playing, they're actually less successful. But he said, we are not using that criteria.

• 42:40Trevor Noah?

  Called it, man. Touch me. Called it. You called it.

• 42:46Speaker 00

  You did call it.

• 42:47Trevor Noah?

  Yeah.

• 42:47Speaker 00

  But, um, so we don't know exactly, but you know, all of these, like every spacebar hit and everything that I do obviously, uh, gets recorded somehow and can be used. But the question is like, you know, on a good day, our personality is such a low predictive measure to measure how good we are going to be in a job, because it also turns out like I can overcome things in my personality, right? Like, I don't know if any one of you have, like, I try to, you know, I used to be like, Really shy. I didn't like to talk to strangers. I know it's part of my job. I like calling people on the phone and chatting with them, but like going to like, like a party, like a reception with actual people I don't know and like

• 43:26Speaker 02

  Sound like us.

• 43:26Speaker 00

  Going up to them is like, oh, I used to hate it. And then I was like, it's part of my job and I made it, I made it a game to challenge myself. So I was like, I'm gonna, I'm making a game for myself.

• 43:37Trevor Noah?

  You just walked into parties with a keyboard and you're like, how fast can you hit this spacebar?

• 43:44Speaker 00

  You win.

• 43:45Trevor Noah?

  Nice to meet you. Nice to meet you. I'm Hilka. We can be friends.

• 43:49Speaker 00

  This is, this is my research.

• 43:55Speaker 00

  That would be, I should, I should have done that. That would have been much more interesting.

• 43:59Trevor Noah?

  But what were the games?

• 44:00Speaker 00

  A conversation.

• 44:00Trevor Noah?

  What did you?

• 44:00Speaker 00

  No, no, the game was that I have to approach strangers and like say hi.

• 44:04Trevor Noah?

  Oh, you did this for yourself?

• 44:04Speaker 00

  Yes, yes.

• 44:05Trevor Noah?

  And what was your reward?

• 44:08Speaker 00

  My reward was just like, well, getting to know people and like learning about them.

• 44:13Trevor Noah?

  I like this. So this was how you overcame it for yourself. You went, I'm afraid of speaking to people, so I'm gonna make it a game where I just walk up to a stranger.

• 44:20Speaker 00

  Yeah.

• 44:21Trevor Noah?

  Speak. What happened?

• 44:22Speaker 00

  That's what I tell my journalism students.

• 44:23Trevor Noah?

  What happened when it didn't go well?

• 44:25Speaker 00

  Well, I'm still here. So I was afraid I was gonna get decapitated, right? People are nice and they're like, but you know, I'm still here and you know, sometimes people were just like, eh, and like just left me standing there. I was like.

• 44:36Trevor Noah?

  It's not as bad as you thought.

• 44:37Speaker 02

  Yes, but you see, this is AI again, having, let's say if this was a program, you would score higher because you're a woman. It's easier for women to do that than a man to do that.

• 44:47Trevor Noah?

  Oh, that's interesting.

• 44:48Speaker 02

  If I walk to, into a random room, then there's a bunch of women there and I'm like, hey, guys.

• 44:54Speaker 02

  I should make a game where I'm trying to be social.

• 44:59Speaker 02

  Stranger danger psycho. But for a wo- For a woman is much easier. So the bias is kicking again. If I go to a Midwest town as a black man from Africa and I walk in there, there's truckers and I go, howdy, folks. No one's gonna say hi to me.

• 45:16Trevor Noah?

  That was a good howdy though.

• 45:17Speaker 00

  Yeah.

• 45:18Speaker 02

  You like that?

• 45:18Speaker 00

  You nailed that. You nailed that.

• 45:20Trevor Noah?

  I'm in. If my eyes were closed when you walked in.

• 45:23Speaker 02

  Close your eyes now. Howdy, folks.

• 45:25Trevor Noah?

  Aye, who's that over there?

• 45:26Speaker 00

  That was not bad. That was not bad.

• 45:27Trevor Noah?

  I'm in.

• 45:28Speaker 02

  Done.

• 45:29Trevor Noah?

  Once I look up, things might change.

• 45:32Speaker 02

  So you see how biases is informing how the, what the outcome ends up being?

• 45:37Speaker 00

  Well, but it wasn't a bias challenge. It was just like a personality, like, overcome challenge, right? Because we all have like certain things that we like to do and we don't like to do.

• 45:46Speaker 02

  You were unbiased. They were. On the other, on the receiving side of it, they were like, here's a woman. She's smart. She's nice. She's saying hi. Let's, yeah, less threatening.

• 45:55Speaker 00

  That's true.

• 45:56Speaker 02

  Exactly. So the bias is kicked in. So the same applies when an HR manager is sitting across someone who they look at and go, I wouldn't want to be stuck with you in an elevator on the 14th floor.

• 46:06Trevor Noah?

  But then, but then that.

• 46:06Speaker 02

  At six at night.

• 46:07Trevor Noah?

  Yeah, but then that raises the question then.

• 46:11Trevor Noah?

  Is there ever going to be a world without bias? And is that what we should be looking for?

• 46:15Speaker 00

  I mean, look, we can all wish, but we know that that's, that's never gonna happen. Like, we hu, we humans are biases machines.

• 46:23Trevor Noah?

  Yeah, but now that, but now that the machines.

• 46:25Speaker 02

  You're right.

• 46:26Trevor Noah?

  But now that the machines are doing the job, could it be possible? And I know, I'm not saying it will, but I'm saying, could it be possible that the AI? Cause, cause here's, here's what I think about in, in what you're talking, in what you're saying.

• 46:40Trevor Noah?

  We're living in a world where we know that biases exist. We know, right? So whether it's in courts, whether it's in law enforcement, whether it's in jobs, whether it's in schools. Doesn't matter. We know that bias.

• 46:54Speaker 02

  Social settings.

• 46:54Trevor Noah?

  Social settings, bias exists, right? Now AI has gotten involved and we see the AI mirroring many of our biases.

• 47:03Speaker 00

  Yeah.

• 47:04Trevor Noah?

  But the difference is with AI, we can actually see it. We couldn't see it before and we couldn't like prove it. We had to conduct like weird studies. We had to, before you couldn't say, this company didn't hire anyone because they didn't say baseball or because they had woman or because they said black. But now you can, you can actually look at the data and go, oh damn. And I, I sometimes wonder if it'll be easier, and again, this could be the optimistic side of me. But I, I sometimes wonder if it could be easier for us to address. Bias in society because we actually have concrete data now that shows it. And we get to blame it. We don't have to blame each other. We'd be like, oh, my God.

• 47:41Speaker 00

  AI.

• 47:42Trevor Noah?

  The racist AI was to you.

• 47:44Speaker 02

  H R A I is a Trojan horse. You're right.

• 47:48Trevor Noah?

  Is there, is there, do you, do you see a world where that's possible?

• 47:50Speaker 00

  Yeah, yeah. I mean, I, I wish companies would, would, would actually look at these tools more closely. I think the, the, the, the general notion though.

• 47:58Trevor Noah?

  That's interesting.

• 47:59Speaker 00

  Is they buy it from a vendor, the vendor sort of like, you know, sort of services the algorithm over time and make sure they still run. And there, there's less bias, like they check if there's like gender and like very basic racial bias in there. But they never look at like, you know, does it let people with disabilities through or something like that, right? Like, and it also, we don't see a whole lot of companies actually checking. How are the decision being made? And I think that's sort of where the problem lies. Like if we actually, somebody would look at the thousands of keywords, resume processors use to predict. If you're going to be good at the job, they would find those keywords that are learned from lawyers and other places.

• 48:37Speaker 00

  And, you know, those are keywords we shouldn't be using. We should be looking at like your skills and your capabilities and not if you are on the baseball team or not. Like, you know, and I came to this as a human. I remember like for the first time talking to a lawyer about this. And I was like, well, maybe the AI found something that humans couldn't that like, in this case, it was playing lacrosse in high school. That was like a predictor of success. And I was like, maybe it found out for this, like whatever insurance job or sales job. It was really good to play, you know, to play lacrosse in high school. It found this like hidden gem that we humans couldn't. And the lawyer started laughing and he was like, God, you think like a human? I was like, really? He's like, it's a pattern machine. It does a statistical analysis.

• 49:18Speaker 00

  For whatever reason, like playing lacrosse in high school, a bunch of people who were in the job had that criteria.

• 49:24Trevor Noah?

  Lacrosse.

• 49:25Speaker 00

  It doesn't mean, yeah, it doesn't mean that like lacrosse has anything to do with your success. And in fact, he's like, well, if it's like playing team sports, what's with all the other team sports? Like, why weren't they included? Why do you get more points for baseball and fewer points for softball? But it's essentially. I think as a non-American, it's the same game, just a bigger field.

• 49:46Trevor Noah?

  You see, Hill is on my team, minus points for both.

• 49:48Speaker 02

  Like how you saw pickleball and cricket ball.

• 49:51Speaker 00

  Beach ball, we call it beach ball.

• 49:52Trevor Noah?

  Don't, don't bring pickleball into this, please. Let's not bring.

• 49:56Speaker 00

  Trevor doesn't want to talk about pickleball.

• 49:58Trevor Noah?

  Don't press anything. We've got more. What now, after this? Everybody has that oddly specific thing that they're curious about. Maybe it's restoring old watches. Maybe it's Japanese ceramic making. Maybe it's watching someone explain why one bridge in a remote area of Norway is secretly better than all the other bridges in the world. YouTube always has exactly what you're looking for, even when you didn't know you were looking for it. With YouTube Premium, those deep dives feel even smoother. You get ad-free viewing, but you also get background play when you need your hands free. And you get offline downloads, so you can keep watching wherever you happen to be, even if you happen to be off the grid.

• 50:44Trevor Noah?

  It's everything you already love about YouTube, just somehow even better. Yeah, one of my favorite YouTube Premium features is smart downloads. Because how many times have you gone somewhere and realized, "Ah, I forgot to download anything." And now you're on the way to the airport and you're like, "Download, download, download, download." You're on the plane, "Download, download, download, download." There's no wifi. "I wish I downloaded." Now, all of those things that you were gonna watch are just on the internet. Smart downloads basically thinks ahead for you. It automatically downloads recommended videos based on what you like to watch. So even when you forget to prepare, YouTube Premium didn't. I love it. It's like packing for a trip and discovering somebody already remembered the thing you always leave at home. It's always the underwear. If you like YouTube, you'll love YouTube Premium.

• 51:30Trevor Noah?

  Sign up now for your free trial at youtube.com/premium. Terms apply. Cancel anytime. I think one of the things you realize when you start caring about clothes is that simple doesn't have to mean basic. Because a T-shirt is a T-shirt. Until you find the right T-shirt. Ooh, then suddenly you're talking about the cut, the fit, the weight, the way it falls on your body. Then you're like, no, no, no, you don't understand. Look at the sleeve. And that's what I've really enjoyed about Quince. One of my favorite things is their Pima Cotton Lux Touch T-shirts. And it's become one of those pieces I keep reaching for. The cotton has this really smooth, premium feel to it. The fit is great. And it just lays really nicely.

• 52:15Trevor Noah?

  And I think that's what you sometimes take for granted with simple clothes. When they're done really well, they become the foundation of an entire outfit. You can throw on a jacket, a sweater, whatever you want, but everything works because you started with the right thing. That's what I like about Quince. It feels premium without feeling like you're trying too hard. It's effortless. So find your next fall favorites at Quince. Download the Quince app for app exclusive offers or go to quince.com. Get free shipping on your order and 365 day returns. Now available in Canada and the UK too. Hello over there. Oh, and if Quince asks you where you heard about them,

• 52:58Trevor Noah?

  let them know it was What Now with Trevor Noah. It's the best way to support the show.

• 53:03Speaker 03

  Pressure doesn't change what matters most. The people on your site. You lead the job. You set the standard. The crew counts on you to get it right. Pros know leadership starts with safety. That's why staying ahead matters. Catching issues before they escalate. Keeping small risks from becoming bigger ones. When it comes to reinforcing safer work from start to finish, Hilke brings tools, systems, and services built to support the way you lead. So that every person goes home safe.

• 53:39Speaker 02

  You know what I realized speaking to you guys about this? Because I wanted to know as little as possible about the topic. So I can get enlightened in real time is companies.

• 53:48Speaker 00

  How's that going?

• 53:49Speaker 02

  Very well, because I'm because I've worked in retail before in South Africa.

• 53:53Speaker 00

  Oh, yeah.

• 53:53Speaker 02

  And I've realized that HR has always been the enforcer and the goon of the corporation. Because when you come in, they're the first people to ask you, what do you like? But basically, they're trying to see, do you want to fit in here and be here? And where do you come from first? Then, when you get let go, you do what they call an exit interview.

• 54:10Speaker 00

  Yeah.

• 54:10Speaker 02

  And that will help them not hire a person like me ever again. So I use public transport. I went to a township school. So they knew that all of those factors and my age as well and how long I stuck around in that job. So they know the propensity of me sticking around longer or doing something wrong. All right, according to them, is based on how long I stayed and where I come from. And what changes I've made in my life since I started working there. So they could predict if someone earns this much for this long at this age from this background, the money will start becoming too little for them to be here. So AI now is doing that at a rapid rate.

• 54:45Speaker 00

  Yes.

• 54:45Speaker 02

  Instead of saying, we don't want women, it will cut out words like soccer and blah and blah and blah and blah. And then the people that say those words, maybe they get hired because likelihood is they are men. How many kids do you have? How far from the job you live? And what are you willing to do for this job?

• 55:01Speaker 00

  I was gonna say like that, you know, like when you think about it, like how these kinds of statistics and prediction works, it precedes AI by a long time, right? Like, we know statistically that if you have a longer commute to your job side, you are much more likely to quit statistically. But is that fair? And, you know, we've seen companies trying to use this, like zip codes and stuff, to then say like, okay, well, we only hire the people that are right, you know, live in the zip code riding around our store location because they are less likely to quit. But like, does it really have that? That's a criteria that has nothing to do with the job. It doesn't say anything about your capabilities and if you're going to be good at the job.

• 55:41Speaker 02

  It only says something about your situation.

• 55:42Speaker 00

  Yeah, and, you know, and also like, well, first of all, like. There are people who do the two hour commute each way and they do a fabulous job. So you're cutting out all those people and it's not their fault. And then on the other hand, you also have to look like we live in very segregated communities in the United States. There's historical vet lining. So if you like start taking out zip codes, you might actually like take out huge swath of like African American population or Asian American population. That's true around the world, to be honest. Doesn't matter where you're from. A real problem and we sort of see this kind of statistical bias get replicated again and again. But now we have this like layer of objectivity and we don't interrogate the tools again to actually.

• 56:26Speaker 00

  Plausible deniability to enforce more of the biases. How did you know that? I think it's plausible deniability of the companies that use it and buy from the vendor, because then they can't be taken, you know, it'd be very hard to have a court case where you say like, well, you knew that your tool was biasing women. And there's like two million people that apply to this, two million women that apply to this company. And you use the bias algorithm on them. So suddenly you have like potentially two million claims. That's why we see like sort of what I think is sort of a cloak of silence around this. Because companies also obviously don't want to come out. You know, I've had so many people who work in HR tell me like after the book came out, you know, oh yeah, we used that tool that you talk about and we, you know, stopped using it.

• 57:11Speaker 00

  And I'm like, oh, really? I was like, well, that's good. I'm glad you did. They're like, yeah, we sort of realized we had the same questions. We found the same things that you found. And we just didn't think it was fair. And I was like, okay, can you, can you talk about this? They're like, oh, absolutely not. But we need to learn, like we'll never get better. We never, we can't put pressure on the vendors to build better tools if we don't know how the tools work. And if there's any problems in the tool, I just looked at a fraction of these tools. Like I tested some of them myself. I worked with like scientists to test them. I looked at like, you know, I spoke with like whistleblowers and like lawyers who like work in the space. But I have just a sliver of the whole sort of world out there. Like we need to do a whole lot more, but I don't think it's in the company's interest. They want something that.

• 57:55Speaker 00

  You know, like sort of saves them money in HR. It's always a cost center. HR never generates money or talent acquisition, however you want to call it. And so in a way, they want to save more money, have less labor involved. And they don't want to like hire people who know stuff like picking apart the algorithms. Then, you know, then it might not work. And what are they going to do then? They just spend so much money in it.

• 58:15Trevor Noah?

  So when you, so when you look at what they're doing, you know, it seems like, and maybe I'm going to a dystopian conclusion, but I've read through some of the companies that you've investigated and some of the tools that they've used. It feels like it's becoming more and more pervasive. So first companies just looked at what you submitted to them, your resume. Then companies started scrubbing what the world knew about you. And then now because of the way data is shared, I'm even seeing stories where they're saying some companies may be able to go, you know, as far as your social media. I mean, one of the craziest examples I saw, which I don't know how true it is, is like, like your Uber rating is a possibility in the future,

• 58:57Trevor Noah?

  which sounds like something China was doing or trialing, by the way.

• 59:01Speaker 00

  Yeah, with this, with the social.

• 59:04Trevor Noah?

  Yes, remember that.

• 59:04Speaker 00

  Yeah.

• 59:05Trevor Noah?

  Basically.

• 59:05Speaker 00

  Social score, yeah. If you have a higher social score, you get to travel and you get like certain benefits of society. But if you're like J-Walk, oh, you're like, visit grandma.

• 59:14Speaker 02

  That's me.

• 59:15Trevor Noah?

  No, really. And so, but now when I, when I think of that, I'm like, what, like, are we heading towards a world where a company can hire you or fire you? Looking at your Spotify playlist going, oh, this, oh, no, oh, no.

• 59:29Speaker 00

  Oh, yeah, yeah, yeah. I mean, look, some psychologists say that like the way we behave is very predictive. And they can certain, find certain ways, like there was a, there was a, a, a, a big finding of a few years ago. And I think it was like that a lot of computer scientists are really into manga comics. And so. The question is like, well, if you look at their resumes, should you hire the people that like mangas? And because you know, they're going to be good computer scientists. But what is with the people who are great computer scientists who just are not into manga? Like, that's not fair to those people, right? So like, that's sort of the problem with these shortcuts. But I sort of do feel like there is a dystopian vision that like, you know, I sort of felt like at one point, I was like, wow, maybe at one point,

• 1:00:13Speaker 00

  we're just not even going to do a job interview anymore. A company will just tell you if you're hired or fired, or if they don't want you, based on all of the social exhaust, the data exhaust, we sort of leaf around and companies can predict who we are. It turns out, we did test the sort of personality testing that is being used on social media. It doesn't work, but it's still being used. It doesn't actually stop people from using shitty technology. That's sort of the bad part here, right?

• 1:00:44Trevor Noah?

  But it doesn't actually work to predict what the people are doing. It does make me think of a dystopian world, though. Like, just this idea that you will be hired before you've applied for a job. I just think of like, us in the year 3000 or something, and a van just pulls up, the door opens, and they're just like, "Welcome to the job, Jean Jean. We know you better than you know yourself, soldier." And you're like, "What are you talking about?"

• 1:01:10Speaker 00

  Yeah.

• 1:01:11Speaker 02

  But you might not even be wrong. In my conspiracy mind, I'm thinking that AI tools are just a big giant facade for data harvesting. Companies know if what they are offering to the public is still viable. Learning institutions know who are the most likely candidates. For them to start giving or keep giving the courses that they're giving, because we forget that high learning institutions are just businesses as well.

• 1:01:37Speaker 00

  Oh, yeah, totally. And some of them use this kind of technology, like one-way video interviews. And yeah, I mean, I think, I think what fundamentally it comes down to, it's kind of funny, what I have learned by like, bringing AI into the talent acquisition hiring space, I learned like, how bad our old processes are. Like, job interviews, actually really bad. Because you are, it sort of filters out the people who are good about talking, about doing the job.

• 1:02:04Speaker 02

  As opposed to doing the job.

• 1:02:05Speaker 00

  So we have this like competence versus confidence problem, like people who like come off as like confident. We often think like, well, that person speaks so confidently about, they must be really good. It turns out like that are more often than not men. And that doesn't mean actually they're competent. So we sometimes complain.

• 1:02:21Speaker 02

  Us men? No.

• 1:02:23Speaker 00

  Never.

• 1:02:24Speaker 02

  What?

• 1:02:26Speaker 00

  So, you know.

• 1:02:28Speaker 02

  Little old us, Hilka? No.

• 1:02:32Speaker 00

  As always, not all men, but a lot.

• 1:02:36Speaker 02

  Us little old men, ooh, acting like we know more than we do. Us, ooh, come on, Hilka, ooh.

• 1:02:44Speaker 00

  Men explaining, what?

• 1:02:49Speaker 02

  Wait, I think, I think this highlighting yet again, the same point again of saying that biases have gotten at this far. I've often heard people who go, if I'm in a criminal trial and I'm thinking of what kind of lawyer to get, I want someone who's, who's talkative, who's out there, who's loud. But the person who handles my finances must be quiet, you know, reserved and frugal. And they'll know how to handle my finances. You know what I'm saying?

• 1:03:12Speaker 00

  Yeah, yeah, yeah. I've never heard about this talkative lawyer, but I'm sort of like.

• 1:03:16Speaker 02

  Yeah, we have an idea. You want someone who goes, razzle dazzle. We've seen the lawyers that, that represent razz.

• 1:03:20Trevor Noah?

  Charisma.

• 1:03:20Speaker 02

  Yeah, charisma.

• 1:03:21Trevor Noah?

  Yeah, you want, and it's interesting to, to exactly what you're saying. If I hear you correctly, you're saying, in a, in a way, it seems like we are expanding and scaling on a foundation that was already broken.

• 1:03:34Speaker 00

  Yes, absolutely. The way we hired was already broken, like job interviews are broken, like sort of looking at, and you know, resumes are very, have very little predictability. Cause you know, like you, you put certain like things, you need to have this skill and this skill in, in the job. And then, and you put that on everyone who applies for the job, 99% of the people will have that on their resume. So, and you can't find like things like teamwork, are you a good collaborator?

• 1:04:01Trevor Noah?

  Yeah, you don't know.

• 1:04:02Speaker 00

  How are you gonna know that from a resume? How are you gonna know that from a job interview? You can ask like questions like, well, tell me how you overcome, you know. A challenging situation at work and but you can you can train for that like the best way. You know, one of the best way to predict if you're going to be successful. This will come to no surprise to anyone is to put you in the job. And then you can find out if you're going to be good at the job.

• 1:04:23Trevor Noah?

  Hey, look at that.

• 1:04:25Speaker 00

  Totally doesn't work for most companies to hire a hundred people and then let let ninety nine go at the end of the month. But sort of my hope sometimes is like, wait a second, like we have virtual reality, like we have other ways like, could we put people in the jobs and actually have them? Do the jobs, the most important parts of the jobs. And then figure out like.

• 1:04:43Trevor Noah?

  And then just see how they actually are at the job.

• 1:04:45Speaker 00

  And I think that would also give candidates a way to sort of understand better, what is this job actually?

• 1:04:50Trevor Noah?

  That is, have you suggested this to companies? Because this is, I like this idea. You, I really do, you, I really do.

• 1:04:56Speaker 00

  I do, I mean, I think it turns, you know, I do think it is a little bit more complicated than just what I'm saying. Because, you know, like a lot of jobs have different, yeah, they have like different capabilities and different things that you have to test for.

• 1:05:08Trevor Noah?

  Right.

• 1:05:08Speaker 00

  And some of it is is hard to test, but we need to be better. Or some like total cynics in this world have sort of suggested, you know what? If you want to hire, use a random number generator, because that is at least fair. You have the same fair chance as you, you and you to to get to get picked.

• 1:05:27Trevor Noah?

  Yeah, it's also a way to go bankrupt as a company. I mean, that's like a, I'm all for like, but that's also like chaos. There's random and there's chaos, you know what I mean? If you're going to say to people, yeah, random number, just bring the person in. Yeah, I don't.

• 1:05:42Speaker 00

  If they have the basic capabilities.

• 1:05:44Trevor Noah?

  Oh, okay, so you're going, okay, so you're going basic capabilities and then like you've got the qualifications, then it's random. I'm in for that, I'm down.

• 1:05:51Speaker 00

  Yeah, try that.

• 1:05:52Trevor Noah?

  Wait, so, but but you know what I want to move on to is like the, we're talking a lot about hiring.

• 1:05:58Speaker 00

  Yes.

• 1:05:59Trevor Noah?

  Your work really delves into keeping the job, which I think a lot of people aren't aware of. And might even be more terrified to find out about.

• 1:06:09Speaker 00

  Oh, yeah, what we see the surveillance at work.

• 1:06:11Trevor Noah?

  Yeah, like, for instance, and I know there was an explosion of this during covid. Once people were working remote and then companies like, we need software to know whether people are actually in their underpants or not. And we need to figure out like what people are doing at home. But now companies are starting to deploy AIs that not only see how like active you are, but they try to predict whether or not the company should fire you. Not based on what you're doing now, but what the company thinks you might. Want to maybe do or not do.

• 1:06:39Speaker 00

  Yeah, I mean, I think it's often like, you know, it's called like a digital neighbor or something like sort of like the the the idea is like you are a vice president of sales of North America. So there might be a vice president of sales in Europe. And one of them is like, uh, might be more, um, successful or not. That's actually kind of vague and hard. Um, but for this, the sake of this, this example, we'll assume, okay, maybe, maybe they're the European person is is better at their job. And so then in AI will like sort of take in all of the digital traces that you leave. How many emails you send, how many Zoom meetings you attend? Are you bullying Zoom meetings? Do you speak up? Like, you can kind of assess a lot of different things and then tell the person in the US like,

• 1:07:22Speaker 00

  hey, the person that is your job in Europe and like sells more or whatever, like is more successful, they do this. Why aren't you doing that? It's sort of like a clone of like looking at all of their, everything that gets recorded. And, um, you know, it's sort of like, I don't know, we have different ways to be successful. Like, maybe you write 500 emails. The next person is successful by doing like 100 in-person meetings a week. That's probably not possible, but you know, maybe they do 50 a week. Who knows? Um, but we sort of, and you know, what does it mean to be successful? Like, we have this like whole thing, um, probably don't remember this and I might be dating myself, but there used to be like algorithms in New York City to assess teachers like 20 years ago or so. Like every parent was like, I want to know about my teachers.

• 1:08:07Speaker 00

  Well, it turns out like these algorithms were terrible and and a lot of teachers were like put in rubber rooms, uh, because their their students didn't gain enough knowledge in a year. But it could be that they were already at the top.

• 1:08:19Trevor Noah?

  Wait, the teachers were put in what?

• 1:08:21Speaker 00

  They're called rubber rooms when like, when like teachers were not in the classroom anymore, but they were still on the payroll of the Department of Education. They called them rubber rooms at the time.

• 1:08:30Trevor Noah?

  Rubber rooms?

• 1:08:31Speaker 00

  Yeah.

• 1:08:32Trevor Noah?

  Oh, because in my head, I was like picturing a room.

• 1:08:34Speaker 00

  You had to go somewhere to work.

• 1:08:36Trevor Noah?

  Rubber, what like, what?

• 1:08:37Speaker 00

  No, it sounds like a cell. I think it wasn't a cell.

• 1:08:40Trevor Noah?

  Okay, no, because you just went through that. You're like, they put the teachers in rubber rooms? And then I was like, wait, they did what to them? Or they just called it a rubber room? Huh?

• 1:08:48Speaker 00

  I don't actually know the history of that. Good question.

• 1:08:50Trevor Noah?

  Yeah, I want to know.

• 1:08:51Speaker 00

  You want to know about the rubber rooms?

• 1:08:52Trevor Noah?

  Yeah, no, no, if someone's taking me to a rubber room, I want to know what a rubber room is.

• 1:08:55Speaker 02

  Oh, actually.

• 1:08:57Trevor Noah?

  You would love to go to- Take you to the rubber room. Oh, wow.

• 1:08:59Speaker 00

  Oh, my god. I don't, I don't, I don't know if I wanna go there.

• 1:09:02Trevor Noah?

  Wow. You're gonna get paid for free? At two. You don't have to do nothing? At two. Wouldn't you wanna be in a rubber room, Mr. Boy?

• 1:09:08Speaker 00

  Play, play squash?

• 1:09:09Trevor Noah?

  Play. Good place. In a rubber room. Good place to fall in a rubber room. I still, I still can't, I still can't believe how digital peeping Tom and the digital tattle tales is just everywhere now.

• 1:09:20Speaker 00

  Yeah, it is everywhere. I mean, you know, it starts like super benign with like your, your green light on your email, like are you active or not? That's sort of like a way.

• 1:09:26Trevor Noah?

  Yeah.

• 1:09:27Speaker 00

  Um, and, and, and, and then we see when people realize, oh, everything gets, gets recorded. Um, we see sort of what we call productivity theater. Um, you know, that people like-

• 1:09:37Trevor Noah?

  Slow it down. Did you say productivity theater?

• 1:09:40Speaker 00

  Yeah. It's like, like sort of gaming the algorithms. Um, so you're sort of-

• 1:09:46Trevor Noah?

  Acting like we're busy.

• 1:09:48Speaker 00

  Exactly. So like in the morning, like you check in on Slack and be like, hey, everyone, good morning. Like seven forty-five, crazy. And then you turn around and take your doc for a walk and then you don't show up at your desk at ten, but smoking screens. You were like, you were productive at seven forty-five. Uh, well, you know, an algorithm will now be able to, uh, understand that you haven't sent any emails in an hour.

• 1:10:10Trevor Noah?

  Can I tell you what you've just done, though? You have in a single sentence unraveled one of the greatest mysteries I have struggled with working in an office. I remember the first time and only time I worked in an office. I was always shocked by how some people were just constantly sending emails and messages. And I always felt like they were unnecessary and they were always at random times, something, sometimes on a weekend, some, I was like, what? But now, when you, when you put it that way, I go, they weren't working, they were trying to maintain the appearance of working.

• 1:10:51Speaker 00

  Productivity theater.

• 1:10:51Trevor Noah?

  So you're just like, yeah, you send a message at six AM and people are like, man, you up at six AM?

• 1:10:55Speaker 00

  Yeah, wow. Emails at three AM, what the?

• 1:10:58Trevor Noah?

  Um, well, you just don't stop working.

• 1:11:01Speaker 00

  Yeah. And, you know, I, I do think that like-

• 1:11:03Trevor Noah?

  Meanwhile, you just left the club.

• 1:11:06Trevor Noah?

  Send.

• 1:11:06Speaker 00

  Schedule, schedule send.

• 1:11:08Trevor Noah?

  Schedule send.

• 1:11:08Speaker 00

  Schedule send.

• 1:11:09Trevor Noah?

  Oh, schedules. Look at this.

• 1:11:11Speaker 00

  Yeah. But, you know, think about it, like the, the, the office was like sort of, uh, always a place to look for productivity, right? Because you had a manager look at everyone who was working and if you left early. That was not so good.

• 1:11:24Trevor Noah?

  Yep.

• 1:11:24Speaker 00

  Even though, you know, we know that some people just like sat at their computers or if the internet and didn't do any work, but they were physically at their seats. We didn't have the technology to actually like sort of see every one of their clicks and what they're doing. And now we do and sort of we can sort of look at everything you do. But like, the question is like, is this kind of analysis really meaningful to understand how many emails you sent? Does that actually have anything to do if you are productive or successful?

• 1:11:52Trevor Noah?

  Right.

• 1:11:52Speaker 00

  What does successful in this, in this job mean?

• 1:11:56Trevor Noah?

  Those, those computer systems you're speaking about, I remember reading about how warehouses also using it. Like this is, this is something that I hope people understand will be pervasive across all jobs. Cause if you work in an office where you're using a computer, they can track your clicks, they can track your, your typing, see what you're doing and how you're doing it. But in warehouses.

• 1:12:16Speaker 00

  Oh, yeah.

• 1:12:17Trevor Noah?

  I've seen that now they're deploying AI camera systems that see how many employees take bathroom breaks or don't take bathroom. I swear, how, how long you spend in the bathroom, how quickly you actually move one package over to the next, how.

• 1:12:32Speaker 00

  Yeah, they're putting different algorithms. How many like items do you put in a box per minute, per hour?

• 1:12:37Trevor Noah?

  Now imagine your bladder, your bladder is the reason that you, because you've got a smaller bladder than another person, you're getting fired.

• 1:12:45Speaker 00

  Technically, that would be illegal, but.

• 1:12:47Trevor Noah?

  Yeah, but they wouldn't say it's because of that. You, because they would just go like you take excessive bathroom breaks.

• 1:12:50Speaker 00

  Yeah. Or you have, you're falling under your productivity.

• 1:12:54Trevor Noah?

  Exactly. Because the other people around you, they're hitting these numbers. Why aren't you hitting those numbers?

• 1:12:57Speaker 02

  As a conspiracy theorist, I always say, who, who else is benefiting from, from this? Who is?

• 1:13:04Trevor Noah?

  Ching!

• 1:13:05Speaker 02

  Because I, I look at, at COVID and you explained to me how tough COVID was in the city.

• 1:13:10Trevor Noah?

  Yeah.

• 1:13:10Speaker 02

  But if you look around the world, how many running shoes have suddenly become in fashion? How many running clubs? How many running apps are being used? How many outdoor activities, hiking, you name it, that people are now having invested themselves in and investing a ton of money in because they missed being outside so much because it was taken away from them. Could it be? That people that fund startups are now having the time of their life because they realize there's these educated people who are trying to get into the job market with these kind of expertise and these kind of interests, but maybe they're not going to get in there. So how about we give them a hand and make money out of them?

• 1:13:46Speaker 00

  Sure. I mean, I think like the way we see like this kind of technology benefit is usually the companies because that's where the money is, right? Like, is an individual like gonna buy a success company, like success AI? Like, we don't really see it. It's not really a market, right? Like, the same way for like job applicants. There's like, there is some AI where you can sort of test your resume and the job description. But we see like vastly outnumbered AI for like vendors, the people that make the employment decisions, those folks, because that's where the money is. Like, I sometimes dream of like, you know, we were talking about bias. And I was like, you know, wouldn't it be cool if you have like a bias detector in job interviews that pings the hiring manager? Like, stop

• 1:14:31Speaker 00

  talking about your schooling. Like, you know, this is like where bias creeps in, or at least analyze afterwards. So you get like real time feedback like, hey, you shouldn't really ask those questions. Like, stick with the structured interviews in a job interview, for example. And we don't see that because I don't think there's really a market there

• 1:14:50Speaker 00

  to do that yet. You know, I sometimes feel like, you know, wouldn't it be cool? Like, I have a young kid. So like, if you're like a parent and you have a little AI who's like, hey, you really shouldn't get so upset with your kid. You should really say, I like how you did this and this. But like, I think a lot of parents wouldn't want to do that because as soon as you have the data, somebody else, like Child Protective Services or wherever can come in and look at that and be like, the way you talk to your kid, no good. Like, no one wants that, right?

• 1:15:20Speaker 02

  You're not fit to be a parent. We'd love to hire you as a manager at our company. How's your bladder?

• 1:15:26Speaker 00

  You have the personality to enforce the algorithm.

• 1:15:30Trevor Noah?

  So actually, let's talk about that then. As somebody who's investigated and gone down all of these rabbit holes, as somebody who's seen how AI is affecting who gets hired and how you get hired, who gets to stay in the job and how they get fired.

• 1:15:43Speaker 02

  How you get fired.

• 1:15:44Trevor Noah?

  Yeah. As somebody who's done all of this work, I'd love to know what you think some concrete solutions could actually be, like where we see progress, where we see solutions. Is there, is there something? Let's break it down. Is there something lawmakers can do? Is there something that companies can do?

• 1:16:02Speaker 00

  Uh huh.

• 1:16:02Trevor Noah?

  And then is there something that just workers can do?

• 1:16:05Speaker 00

  Yeah. Um, so I do think there's room for improvement in all levels.

• 1:16:10Trevor Noah?

  Yeah.

• 1:16:10Speaker 00

  So I do think that there could be uh better laws here. For example, what we see, uh, you know, the funny thing is like, I am originally from Germany, but uh I remember talking to the former head of uh talent acquisition at Vodafone, uh, which is a huge uh telecommunications company in Europe and other parts of the world, not so big in the US. And and he was laughing, he's like, you know what, like, we use AI in hiring now. And and when you want to upload your resume, there's like Germany and the rest of the world. Uh, because Germany has this one funny thing that like, once you're working in a company and you have, I think, more than five employees, they can um uh have a workers' council. It's not a union. Sounds like it, but it's different.

• 1:16:50Speaker 00

  And the workers' council, there's actually a law, and they get to co-decide technology in the workplace.

• 1:16:56Trevor Noah?

  Oh.

• 1:16:56Speaker 00

  So some of the surveillance technology, we don't see happening in Germany because the, you know, this workers' council has to be notified. And I think a lot of companies shy away from using some of this, like, very intrusive um AI tools. Um, but in the United States, for example, like, anything that happens on a work computer belongs to the company. So like, don't do it like private Slack messages, like private surfing, like, all of that can be recorded by the company, and it belongs to them.

• 1:17:21Trevor Noah?

  Yeah.

• 1:17:22Speaker 00

  Um, so you want to be very careful of that. So I think there needs to be many more privacy protections, and I think companies should tell, should be mandated to tell their employees what kind of software they're using them. So for example, like, some of it is, like, very basic, but like, if you suddenly print a lot, that might be an indication that you're at flight risk. So maybe the company lawyer should be looking into what you're moving away from your computer. Um, like, those kinds of, like, sort of uh digital tales. Um, you know, I think companies should tell us, and maybe there should be a way for, like, uh, employees to co-decision making, because some of the time, you know, if you're working in a nuclear power plant, maybe you do want AI to scan for, like, exposure to radiation. I wouldn't want that, like, um, so, you know, there might be cases where this is, like, actually.

• 1:18:06Speaker 00

  Really helpful and and maybe everyone agrees that like, you know what? Printing is a problem. You shouldn't be printing so much and you shouldn't like move files and that could be an indication that you're leaking. Yada, yada, yada, like, maybe, maybe we can make a decision together, but we don't, we don't see that. So it's like all top down. And people are, you know, these kinds of tools and decision makers are being used on them. And they don't even know it. And I think that's really unfair and there's no way to push against that. I think also that companies need to be much more skeptical when they buy these AI tools, not believe the hype that this is going to solve all their problems. They're going to hire the best people, like actually. Yeah. Show me, show me the evidence, like, show me how it works. I'd be happy to look at it.

• 1:18:49Speaker 00

  And, and, you know, I'd be open to it, like, maybe, maybe an AI is better. Wouldn't that be great? But we need to know, we don't actually know that kind of stuff. So we need to interrogate these algorithms, understand the processes underneath them and really critically assess them. I think that's where maybe humans are coming in, in this world. So we need to be much more skeptical there. And then, as like, the applicant for jobs? That's the hardest part because there isn't necessarily something you can do, except like call your congressperson and sort of be aware of what is out there. And like, try some of the tools, like, you know, there's, there's definitely better ways to like, have a machine readable algorithm and there's things you can do.

• 1:19:30Speaker 00

  But you know, when like 5,000 people apply for one job and they close the job description after, you know, they, they, they close the job portal after 24 hours.

• 1:19:40Speaker 00

  There's, there's nothing we can help you with there. Like it's, you know, it's sort of like a bigger societal change. To be much more skeptical about these tools and put pressure on lawmakers, decision makers to do a better job here. And to just be more transparent, like one of the stories like of Martin, like came through because he lived in the European Union and knew about the laws and he asked for the data, like there is a general privacy protection law. And you can ask for your data that companies have on you. And that's how he found out that the company used AI, which was against the law, law, law, law. So he got a, he, he, he got a settlement. He actually. Started a case. So that was like a goldmine for me. I call him patient zero. Cause he's sort of the first person who like encountered these kind of AI tools in the hiring phase.

• 1:20:26Speaker 00

  And then actually got the data on himself, right? That's like gold to me. So we could sort of unravel and, and, and, and talk about the case because we had the data. And we don't have anything like that, at least on a federal level in the United States. So there's like way more work to be done to make this better. And I do think in general, like I do, like, I think we talk a lot about like sentencing guidelines with AI to send people to prison. Should you get a mortgage? And, and, and I think those are all very consequential decisions and we absolutely need to take a closer look at those and look at them critically. But I also think hiring is really important too. Like it matters if I can pay the bills. Like it matters if I can food, put food on the table. Like also like happiness is tied to our jobs for many people.

• 1:21:11Speaker 00

  Like we spend enormous amounts of hours at our jobs. So like it better be something we kind of like at least. So it matters if I get the job or not. So we really should be scrutinizing these kinds of system if it makes decisions on humans. If it makes decisions about my spam and it doesn't work, I'll find another spam filter. Like fine, great use for AI. But for hiring in these critical human decision makings where human lives are at stake, you gotta be much more skeptical. Scrutinize these tools. And then we probably have a chance of building a better world.

• 1:21:44Trevor Noah?

  Well, I will say there's one part of the equation I'm very grateful for, and it's that we have an intrepid investigative journalist. Who's doing the work because I mean.

• 1:21:53Speaker 00

  Sometimes you wonder like, does my work have an impact? But I do think sometimes, you know, when I show people like my videos from eight years ago about like the emotion recognition of, of facial expressions and, and they're like, wow, that could be so easily biased. And I was like, wow, I guess our work sort of like has made a difference because eight years ago, we all looking at like, whoa, who knew this is so cool. And now everyone is like, oh, wait a second. Like if there are only like, you know, more men than women in the data, la, la, la. And I was like, wow, there is like sort of a much more education around AI and bias and all of those things. And I think it has made an impact slowly but surely.

• 1:22:30Trevor Noah?

  Slowly but surely. But I'll tell you, now I know for my next job, I've got something to think about when we get out there in the streets. And from my side-

• 1:22:39Speaker 00

  Oh, please, please work with me on hiring. Let's do like some-

• 1:22:41Trevor Noah?

  Oh, no, yeah, no, no. Thank you very much. You know, from me, you know, from Syria, from Canada and Thomas, we just want to say-

• 1:22:48Speaker 00

  Yeah, let's put a coin on hiring-

• 1:22:50Trevor Noah?

  Let's do it.

• 1:22:51Speaker 00

  And see how it works.

• 1:22:52Trevor Noah?

  Okay, thank you very much.

• 1:22:53Speaker 00

  Awesome, thank you.

• 1:22:57Trevor Noah?

  What Now with Trevor Noah is produced by Day Zero Productions in partnership with Sirius XM. The show is executive produced by Trevor Noah, Sanaz Yamin and Jess Hackel. Rebecca Chain is our producer. Our development researcher is Marcia Robiu. Music, mixing and mastering by Hannes Brown. Random other stuff by Ryan Harduth. Thank you so much for listening. Join me next week for another episode of What Now.

• 1:23:29Speaker 03

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