Hilke Schellmann: Is Your New Boss a Robot?

Summary

Podcast Summary: "Hilke Schellmann: Is Your New Boss a Robot?"

Podcast: What Now? with Trevor Noah
Date: February 26, 2026
Host: Trevor Noah
Guest: Hilke Schellmann (Investigative Journalist)
Main Theme: Exploring the rise of artificial intelligence (AI) in job hiring, the workplace, and the consequences for workers and society.

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Episode Overview

Trevor Noah welcomes investigative journalist Hilke Schellmann to discuss her deep-dive work on artificial intelligence's growing role in job recruitment, hiring, and management. Delving into the practical, ethical, and societal impacts, this episode unpacks the realities behind automated hiring processes, the biases encoded in AI, surveillance in the workplace, and the broader question: what does “work” mean when algorithms may decide who gets a job—or doesn’t—even before a human ever sees an application?

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Key Topics and Discussion Points

1. Setting the Stage: AI’s Invasion into Work

• Schellmann's Background: Hilke describes how her curiosity as an investigative journalist led her to focus on AI in hiring after a chance encounter with a Lyft driver who had a job interview conducted by a robot (09:00).
  • “I used to investigate all kinds of things and now I just investigate AI... I’m trying to understand, like, how does it work in society. And maybe who are the winners and losers?” — Hilke Schellmann [07:55]
• AI Posters in NYC: Trevor shares his unease seeing mysterious posters about AI’s effect on jobs across New York City, underscoring the growing public anxiety and curiosity (06:46).

2. How AI is Used in Hiring Today

• AI’s Place in Recruitment: Large companies use AI to handle vast numbers of applications, from resume screening to one-way video interviews and even personality games (21:44).
  • “Goldman Sachs said a few years ago for their summer internship, they had over 100,000 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.” — Hilke Schellmann [24:46]
• One-Way Video Interviews Explained: Applicants answer questions on video, alone, which AIs may then screen without a human ever watching the footage (23:23).

3. Biases Old and New: Human vs Algorithmic

• AI Can Encode Existing Biases: AI screening can unwittingly replicate or amplify existing workplace inequities, such as gender or racial bias, by learning from biased historical data.
  • Example: Amazon’s hiring algorithm devalued resumes with the word “woman” or "women," because the data it learned from was already gender-skewed (33:36).
  • “If you had the word woman or women on your resume, you got downgraded because, you know, the tool had learned over time... it's a pattern machine.” — Hilke Schellmann [33:36]
• Hidden Resume “Cheats”: Some AIs give extra points for seemingly random words ("Thomas,” "Syria,” or “Canada”), revealing the accidental, irrational logic of pattern-matching (35:34).
  • “If you had the word Thomas on your resume, you also got more points... Or like, in another case, it was like words like Syria and Canada... That got you up actually.” — Hilke Schellmann [35:34]
• Bias Transparency Paradox: With AI, for the first time, patterns of bias can become more visible, offering a unique—if challenging—opportunity for reform (46:47).
  • “Now AI has gotten involved, and we see the AI mirroring many of our biases. But the difference is with AI, we can actually see it. We couldn’t see it before." — Trevor Noah [46:47]

4. Candidate Gaming and “AI Warfare”

• AI vs. Applicant AI: Now, job seekers use AI tools (like ChatGPT) to enhance their resumes and cover letters—resulting in AI competing with AI in the hiring process (30:11).
  • “Now it’s AI warfare, because I’m going to use AI to apply for the job, they’re going to use AI to grade me. I’m going to use the AI to pass the grades.” — Trevor Noah [30:13]
• Questioning the Purpose of Interviews: The traditional “vibe check” and informal social fit has little evidence of predicting job performance—but is still encoded, by humans or AI, into hiring systems (31:21).

5. Productivity Surveillance and Job Security

• Work Surveillance: Modern AI doesn’t just hire; it’s used to monitor workers, tracking everything from email activity to bathroom breaks, with predictive algorithms flagging those who might quit or underperform (64:05-69:50).
  • “An AI will sort of take in all of the digital traces that you leave. How many emails you send, how many Zoom meetings you attend... and then tell the person… ‘Why aren’t you doing that?’” — Hilke Schellmann [64:33]
• Productivity Theater: Employees adapt by performing “busy-ness” for the algorithms (messaging early/late, scheduling emails) creating a charade rather than true productivity (67:14).
  • “You check in on Slack and be like, ‘Hey everyone, good morning, like 7:45 crazy.’ And then you turn around and take your dog for a walk." — Hilke Schellmann [67:40]

6. Legal, Ethical, and Societal Solutions

• What Can Be Done?: Hilke advocates for:
  • Greater transparency on how algorithms and surveillance systems are being used.
  • Stronger data privacy laws and worker protections.
  • Structures like Germany’s “worker councils,” giving employees a say in technologies that govern them (74:50).
  • More skepticism from HR and business leaders—demanding real evidence of AI effectiveness before deployment (74:51).
  • Worker awareness: use the right to request your data (in Europe), pressure lawmakers, and understand the basics of how these systems work [73:99].
  • “I think companies should tell, should be mandated to tell their employees what kind of software they use in them.” — Hilke Schellmann [74:51]
• Fundamental Question: Are we just automating broken processes? Both Trevor and Hilke agree: old human hiring practices were flawed, and encoding them into algorithms only “scales brokenness” unless fundamental reforms are made (61:28).
  • “It seems like we are expanding and scaling on a foundation that was already broken.” — Trevor Noah [61:28]

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Noteworthy Quotes & Moments

• “Multiple studies have shown humans are terrible at predicting the future, especially when it comes to hiring.” — Trevor Noah [31:36]
• “Maybe at one point, we’re just not even going to do a job interview anymore. A company will just tell you if you’re hired or fired based on all the social exhaust, the data exhaust we sort of leave around.” — Hilke Schellmann [57:23]
• “You have to be much more skeptical. Scrutinize these tools, and then we probably have a chance of building a better world.” — Hilke Schellmann [79:19]
• “Thank you very much. From Syria, from Canada, and Thomas, we just want to say let’s, let’s… Thank you very much.” — Trevor Noah, playfully referencing the “cheat codes” for resumes [80:35]

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Useful Timestamps

• Intro & Setting the Scene: AI and hiring bias [00:04–01:21, 06:46]
• Hilke’s investigative journey [07:55–11:27]
• Real-world impact: AI replacing entry-level jobs [16:21–18:43]
• How much hiring is AI-based now? [21:16–22:04]
• How AI screens resumes; one-way video explained [23:11–24:43]
• AI hiring horror stories (Amazon and resume keywords) [33:36–35:34]
• Gaming the system, ‘AI warfare’ [30:11–31:36]
• Discussion on bias—historical and algorithmic [46:47–49:39]
• Surveillance at work & productivity theater [64:04–69:00]
• Legal & ethical solutions; worker councils (Germany) [74:50–75:03]
• Final thoughts, ongoing impact of investigative journalism [79:38–80:46]

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Tone & Style

The conversation is inquisitive, humorous, and candid, with Trevor’s signature blend of skepticism and wit. Hilke is both analytical and warm, offering grounded examples, technical clarity, and societal context, while the co-host Eugene Koza acts as a proxy for listeners less immersed in the tech world, surfacing everyday concerns and observations about fairness, bias, and transparency.

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Summary Conclusion

This episode highlights how AI technologies are rapidly transforming the hiring landscape—but often by scaling up pre-existing human flaws rather than fixing them. Both the promise and peril of such systems are evident: while automation can bring efficiency, it can also magnify hidden biases, dehumanize hiring, and erode privacy for workers. The hope? With vigilant investigation, skepticism, legal reforms, and transparency, there’s still time to course-correct before our “new boss”—a robot—makes all the rules.

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For those interested in learning more about how AI works behind the scenes in job markets—and how to protect yourself as these algorithms become ubiquitous—this conversation with Hilke Schellmann is essential listening.

Transcript

[Hilke Schellmann]

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

[Trevor Noah]

the job as opposed to doing the job.

[Hilke Schellmann]

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 more often than not men. And that doesn't mean actually they're competent. So we sometimes complain. No, never. What? So you know, As always, not all men, but a lot.

[Eugene Koza]

Acting like we know more than we do.

[Trevor Noah]

Come on.

[Hilke Schellmann]

Hilka mansplaining. What.

[Trevor Noah]

This is what now with Trevor Noah. This message is a paid partnership with Apple Card. Imagine this. You're at a checkout counter. You're ready to pay, when you realize you don't have your wallet. You could drive all the way back home and you could get it, but you remember that you have your Apple card on your iPhone so you can tap to pay with Apple Pay. Imagine that. No need to carry a wallet. But, you know, one of the things I do like about having my card on my phone is we live in a world where you lose your card and then you don't know where it is. And then you're like, what do I do? Well, if your phone is connected to your card and your card is connected to your phone, you know what's going on. The best thing about having the Apple card connected to your phone is you know what every transaction is. You know, like, sometimes you're like, what did I spend this month? The Apple card will show you one month. I had spent an obscene amount of money ordering videos online.

[Eugene Koza]

Just videos.

[Trevor Noah]

They were just videos.

[Eugene Koza]

What kind of videos?

[Trevor Noah]

That's not the point. The point is, I knew that I didn't want to order those videos anymore because I'd spent too much money on was videos on how to not spend money online.

[Eugene Koza]

I felt like I'd been duped.

[Trevor Noah]

Point is, Apple showed me what I was spending my money on, and I was able to change my spending habits. And you can do it, too. I earn up to 3% daily cash back on every purchase with my Apple card. That's unlimited daily cash back no matter where I shop. Apply for Apple card in the wallet app on your iPhone. Subject to credit approval. Apple card issued by Goldman Sachs Bank USA Salt Lake City Branch terms and [e-mail] all right, Eugene, let's play a little Game. You know, make something fun. Two truths and a lie. Here we go. One, I've had to tell a world leader that their fly was undone. Two, when getting dressed, I don't do sock, sock, shoe, shoe. I do sock, shoe, sock, shoe. Three, I've been a Verizon customer for 11 years. What do you think?

[Eugene Koza]

Very confused. First of all, why would a world leader own a fly? Because those things just come uninvited. Secondly, lying to your friends is not cool. There's never been a game.

[Trevor Noah]

No, Eugene. Fly is for, like, the zip is what? And then it's not a lie. It's a game where I'm trying. It's like I give you information. Okay, I lied. All three are true, Eugene. And in case you were thinking, you know, Verizon isn't as expensive as you think. In fact, if you bring in your ATT or T mobile bill, they'll give you a better deal. And the reason I've been with them for this long is just because I travel so much. I need a network that's reliable. That's right. A better deal. On the best network with the most ways to save on plans, streaming and phone deals. Take your AT&T or T mobile bill to your local Verizon store today. Get your better deal and start saving for real. Based on RootMetric's best overall mobile network performance. US second half, 2025. All rights reserved. You must provide recent consumer mobile bill in the name of the person redeeming the deal. Additional terms, conditions and restrictions apply. So do you understand how two truths. And do you understand it now?

[Eugene Koza]

I understand that you didn't have to lie first before telling me that Verizon is the best.

[Trevor Noah]

No, I wasn't lying, Eugene. It's not a lie. I wouldn't lie to you. It's a game. Okay, I'm sorry.

[Eugene Koza]

I lied.

[Trevor Noah]

Ah. You based here? Where you based?

[Hilke Schellmann]

Yeah, based at nyu. Training. Cooper Square. I live in Brooklyn, Okay.

[Trevor Noah]

Oh, what part of Brooklyn?

[Hilke Schellmann]

Greenpoint.

[Trevor Noah]

Greenpoint.

[Hilke Schellmann]

It's the oldish neighborhood.

[Eugene Koza]

Why did your voice go down when you say Greenpoint? Greenpoint.

[Hilke Schellmann]

You caught me.

[Eugene Koza]

Greenpoint.

[Hilke Schellmann]

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

[Trevor Noah]

But isn't it becoming cooler and younger?

[Hilke Schellmann]

Yeah.

[Trevor Noah]

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

[Hilke Schellmann]

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 know, I don't really know Polish. The only thing I know is, like, one line that's like. And that is really bad in Polish, saying, I don't understand Polish. But I kind of like that.

[Trevor Noah]

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

[Hilke Schellmann]

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.

[Trevor Noah]

Yeah.

[Hilke Schellmann]

So that's pretty cool.

[Trevor Noah]

Yeah.

[Hilke Schellmann]

Maybe I'm just getting old.

[Trevor Noah]

I've never understood why people learn the phrase, I can't speak your language in another language because you want to be polite. And I think, but just speak your language.

[Eugene Koza]

A test on yourself to see how much you can learn.

[Trevor Noah]

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

[Eugene Koza]

Yeah.

[Trevor Noah]

You've said to them in their language. You can't speak their language to me. What it shows me is you just don't wanna speak my language because you've learned enough to say you can't speak it and then you won't learn the rest.

[Hilke Schellmann]

No, I think that's, like being really polite.

[Trevor Noah]

You're, like, visiting them and, like, you

[Hilke Schellmann]

wanna be next to them.

[Trevor Noah]

You've literally walked up to somebody and you. Someone came up to you and they were like, I don't speak English. And then you're like, well, you did a great job there. And they're like, mm, that's enough for me. Think about it.

[Hilke Schellmann]

I think we've done enough for them.

[Trevor Noah]

You're like, nah, that's enough. That's good. Well, Hilka, welcome to the podcast.

[Hilke Schellmann]

Well, thank you for having me.

[Trevor Noah]

Thank you so much for joining us. This is, like, you know, sometimes, and 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 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 like, ominous and it feels like it's promo for a movie, but it's not, I think.

[Hilke Schellmann]

So what is on this QR code? Did you check it?

[Trevor 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

[Eugene Koza]

I was like, yes, I wish I did.

[Trevor Noah]

Yeah, 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?

[Hilke Schellmann]

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. Society and maybe who are the winners and the losers. But also like, you know, I really think about, like, what. 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 and how we can maybe save journalism or a factual based society when everything can be generated. So those are kind of things and questions that I think about.

[Trevor Noah]

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

[Hilke Schellmann]

Yeah, I mean, you know, like violence against women in, in Pakistan. I went to Pakistan, I looked at like South Asia. I did all kinds and I don't know, I had like one lyft ride in 2017 in the fall I was in Washington D.C. 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? Job interview with a robot? And 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. 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 down the rabbit hole I went and somehow it never, it doesn't let me go. I'm thinking about the next four books on AI, the next research studies on AI, it just doesn't. I don't know how, I don't know. I'm very bad at predicting the future. But I could tell that this is a transformative technology that we need to pay attention to and not only how the technology work, but it's societal implication. What does this mean if we use AI in hiring? 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 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 and job interview could be predictive of his 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 are like, what emotion? Like that doesn't Exist to predict how good you are at a job.

[Trevor Noah]

And I was like always I was

[Hilke Schellmann]

like, oh, that's too bad. 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. Sorry. When I'm. When I'm in a job interview and I smile and people, you know, facial emotion scanning algorithm would say like, oh yeah, she's totally happy, she's smiling. And I'm like I'm not happy in a job interview. Who in the world been happy in a job interview? So that's kind of like, you know, is a prediction but we're using it to like sort of select people.

[Trevor 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?

[Hilke Schellmann]

Yeah, totally. And 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 take it on. It's like when the 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 one way video interviews and the companies use the recording, run them through a transcription service like speech to text transcription, like you have on your phone. 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. 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. But yeah, so that's kind of the work that I do.

[Eugene Koza]

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.

[Trevor Noah]

But you send them very well.

[Hilke Schellmann]

Very well.

[Eugene Koza]

Sometimes I send pictures as well with those texts and an emoji. Don't get me started.

[Trevor Noah]

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

[Eugene Koza]

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 it?

[Hilke Schellmann]

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

[Eugene Koza]

Nyx, I specifically said to you,

[Hilke Schellmann]

Well, 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 now 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.

[Trevor Noah]

That's crazy. You, 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.

[Hilke Schellmann]

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

[Eugene Koza]

Speak English.

[Hilke Schellmann]

Yeah. Okay. You do not have to emulate the answer. I have nothing.

[Trevor Noah]

You know, 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. 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 AI is fundamentally going to 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 know, like, it meant using your hands and people like, that's not a job. And the first people on a computer are thinking, 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 your investigations on, like how AI is changing what jobs actually are or aren't, like in different fields. Lawyers, doctors, et cetera.

[Hilke Schellmann]

Yeah, I mean, I think we already see some of it coming down. You know, we already see some of the consequences of like AI infiltrating our daily lives. We see a lot of way less like sort of early career hiring. Because 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 that we.

[Eugene Koza]

Maybe we're going to give my calendar book my flight.

[Trevor Noah]

Yes.

[Hilke Schellmann]

Yeah.

[Eugene Koza]

Remind you of stuff.

[Hilke Schellmann]

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 still are working on that, but it can definitely help you, like generate research, doing math problems, all kinds of things. So I think 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 going to break of people doing like early entry jobs? How are they gonna get the expertise and the wherewithal to like move up? If we sort of take out the first layer of jobs, maybe you just have to like, upskill people and.

[Trevor Noah]

But how do we. How do we. 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 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? Because we say upskill, but then who is doing the up of the skill?

[Hilke Schellmann]

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 is 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 as, like, very human things. Like, if. If AI can write better than I do, how can I express myself? And what does it mean for humans in a world of AI? What do we bring to the table now that AI can do so many things for us?

[Trevor Noah]

Don't go anywhere because we got more. What now? After this. All right, Eugene, let's play a little game. You know, make something fun. Two truths and a lie. Here we go. One. One, I've had to tell a world leader that their fly was undone.

[Eugene Koza]

2.

[Trevor Noah]

When getting dressed, I don't do sock, sock, shoe, shoe. I do sock, shoe, sock, shoe. Three, I've been a Verizon customer for 11 years. What do you think?

[Eugene Koza]

Very confused. First of all, why would a world leader own a fly? Because those things just come uninvited. Secondly, lying to your friends is not cool. There's never been a game.

[Trevor Noah]

No, Eugene. Fly is for, like, the zip is what? And then it's not a lie. It's a game where I'm trying. It's like I give you information. Okay, I lied. All three are true, Eugene. And in case you were thinking, you know, Verizon isn't as expensive as you think. In fact, if you bring in your ATT or T mobile bill, they'll give you a better deal. And the reason I've been with them for this long is just because I travel so much. I need a network that's reliable. That's right. A better deal on the best network with the most ways to save on plans, streaming and phone deals. Take your AT&T or T mobile bill to your local Verizon store today. Get your better deal and start saving for real. Based on root metrics, Best overall Mobile Network Performance US Second Half 2025 all rights reserved. You must provide recent consumer mobile bill in the name of the person redeeming the deal. Additional terms, conditions and restrictions apply. So do you understand how Two truths. And do you understand it now?

[Eugene Koza]

I understand that you didn't have to lie first before telling me that Verizon is the best.

[Trevor Noah]

No, I wasn't lying, Eugene. It's not a lie. I wouldn't lie to you. It's a game. Okay, I'm sorry I lied. Ah.

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[Hilke Schellmann]

a month on auto insurance when they switched.

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[Kaitlin Coleman]

Hi, I'm Kaitlin Coleman, winner of Target's HBCU Design Challenge. This challenge moved me closer to my dream of becoming a fashion designer through mentorship and support. You can find my design, along with creations from other black founders, in Target's Black History Month collection. In.

[Trevor Noah]

In the job space. Actually, I would love to know, like, yeah, 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. Is there. 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. Yeah, Nothing.

[Hilke Schellmann]

Yeah, sorry. So we think about, how do you

[Trevor Noah]

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

[Hilke Schellmann]

If I looked at your.

[Trevor Noah]

This was AI,

[Hilke Schellmann]

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

[Eugene Koza]

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

[Hilke Schellmann]

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, to the company I'd like to work for. 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. We call this, like sort of a big funnel. And some companies, this is a couple of years old. When I talked to Google, they get over 3 million applications. IBM gets over 5 million applications a year. So it's a lot of resumes that come into this funnel. So what we now see is a lot of companies, and usually large companies, a lot of Fortune 500s, use AI to reject people, to sort of call the herd of all these applicants. 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.

[Trevor Noah]

Just, just break down what is a one way video interview? Because I think a lot of people, I didn't know what that was until I totally.

[Hilke Schellmann]

Yeah, I hear you. I've done so many seconds ago.

[Eugene Koza]

What are you talking about?

[Trevor Noah]

No, but I didn't know me. Yeah, yeah.

[Hilke Schellmann]

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. Like, you know, you kind of log 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 minutes to prepare and then you tape yourself like saying like, my strength and my weakness is this. 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 watch 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 retail companies, fast food, like it's called high turnover. High. No, high volume. High. I don't remember. So it's jobs, jobs that generally have

[Trevor Noah]

people where people are coming in quickly and leaving quickly like they're not going to be there. It's not a career job. So people are going.

[Hilke Schellmann]

Sometimes it's a career job.

[Trevor Noah]

Oh, but it's just like high turnover.

[Hilke Schellmann]

But it's a high turnover. Or you have like lots of candidates that you have to go through. So for example, like Goldman Sachs said a few years ago for their summer internship, they had like over 100,000 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.

[Trevor Noah]

You can use games.

[Hilke Schellmann]

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. But that's sondering.

[Trevor Noah]

But this is the conundrum though. So this is the thing that's like weird now just for this part of it is my reflex when I hear something like that is to go, oh no, this is not good. How can you have AIs screening people's interviews? But then on the other hand, I go, if you have 100,000 people applying to a job, let's be honest, I don't think there's any human who's gonna get through those a hundred thousand applications. 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, you know, you wanna get them when they're fresh, you wanna get them when they're in the mood.

[Hilke Schellmann]

Yeah.

[Trevor Noah]

Not when they, I wonder, is there a world where like, does the AI make it better then?

[Hilke Schellmann]

You know, I wish I could tell you that that.

[Trevor Noah]

So we don't know.

[Hilke Schellmann]

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 and how do they say run at both times and then sort of double check like, you know, the people that the AI 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 a lot of turnover in hr. These processes don't work 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 2,000 in Germany, the UK and the US when they ask them if your company uses AI tools, do they reject qualified, do they reject qualified candidates? And almost 90% of the leadership said yes. 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 humans are very biased in hiring and even the best anti bias training is not going to get out of it. And we all Know the shortcuts. If you see somebody on your resume that they went to Harvard, you're like, oh, they might must be smart.

[Eugene Koza]

No, they're not.

[Trevor Noah]

I feel like you just end up going down a rabbit hole. This episode, Eugene Koza learns about the world.

[Eugene Koza]

She's like, wait, what are you telling me?

[Trevor 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.

[Hilke Schellmann]

Yes.

[Trevor Noah]

Right. Algorithms like predictability. That's what an algorithm is fundamentally sort of trying to do. It finds like patterns and a pattern is a predictability. 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. Yeah, the outlier. So I wonder if companies, in moving all of their resources towards efficiency and pattern recognition, might go the opposite direction of innovation. Cause it's like, it's almost like the misfits and the mistakes are sometimes the ones who give you the biggest blips.

[Hilke Schellmann]

Do you know what I'm saying? Yeah, yeah, totally.

[Eugene Koza]

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?

[Trevor Noah]

That's interesting.

[Eugene Koza]

Would have 100,000 people from all over the world show up at the address to put in their resume. So I think technology also allowed easy access because 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.

[Hilke Schellmann]

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 sad for a lot of applicants until sort of LLMs and ChatGPT and other AI came around, where now it's like, much easier for me as an applicant to generate a resume. There's actually.

[Trevor Noah]

So now it's AI warfare.

[Hilke Schellmann]

Yes, it is AI because I'm going

[Trevor Noah]

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. Then they're going to, I mean, try

[Hilke Schellmann]

to use AI to like, outsmart the AI. There's actually AI programs that now apply for you, so you don't even have to do anything. So there's all kinds of stuff. But, like, the question is like, well, what are we then doing here? Like, yeah, like, what are we. Yeah, in fact, that is a good question. That is a great question.

[Trevor Noah]

That becomes the question, what are we doing? Because. 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 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. You know what I mean? It's just. It's wrong. And then people don't do well and they go like, well, that didn't work. But the prediction is wrong. You know what I'm saying?

[Hilke Schellmann]

Yeah.

[Trevor Noah]

And so now I almost feel like we forgot what the whole point of an interview was. Like, 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.

[Eugene Koza]

It was a vibe check.

[Trevor Noah]

It was a vibe check.

[Hilke Schellmann]

Yeah. But it turns out, like, vibe checks not so great, actually.

[Eugene Koza]

Like, because you predicting who's a good employee.

[Hilke Schellmann]

Yeah, but also, like, a vibe check is like finding people who, like, are often have the same background as you. They speak like you, they vibe with you, so you find the same people again, which, you know, we kind of know that, like, diversity is good for companies also. Like, I mean, I think that's why we have, you know, fewer women, people of color, and leadership positions, because we have underestimated them as humans in hiring for decades and promotion decisions. So we have, like, sort of a Lack of diversity already because of human bias and sort of the vibe, you know. You know, 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 teach? Oh, boy, you like this? You like this? This sports team, yada, yada, yada. And that chitchat feels like very good for humans to make a human connection, but it's actually really bad because that would 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 what are the capabilities and your skills that you need for the job. Not if we went to the same school, but we as humans do that. And that's where a lot of the bias comes in. And 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 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, an AI vendor and a company may use their tool, sometimes they bring in lawyers and do their due diligence. Like how you do, does this tool work? And what they found out is when the lawyers looked at it, that the tool used. Some of these tools used kind of problematic keywords.

[Trevor Noah]

So, for example, there's the Amazon story that you wrote about.

[Hilke Schellmann]

Yeah, the Amazon story is one of them.

[Trevor Noah]

That's pretty insidious.

[Hilke Schellmann]

So this was like if you had the word woman or women on your resume, you got downgraded because, you know, the tool had learned over time. You know, 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? If the people who are in the role, if you 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.

[Trevor Noah]

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

[Hilke Schellmann]

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

[Trevor Noah]

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

[Eugene Koza]

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

[Hilke Schellmann]

There's no input. This was, this was a. 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 let 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. So, yeah, so it looks at like patterns in the resume la that you give it and I guess it scans all of the words and 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

[Trevor Noah]

if you had the word what?

[Hilke Schellmann]

Thomas.

[Trevor Noah]

Thomas.

[Hilke Schellmann]

Thomas. Like the name, like the name Thomas. Or like, in another case, it was like words like Syria and Canada. What?

[Trevor Noah]

Those got you up or down?

[Hilke Schellmann]

That got you up actually.

[Trevor Noah]

Syria.

[Eugene Koza]

And the combination, you were higher.

[Hilke Schellmann]

Yes.

[Eugene Koza]

Wait, wait, wait, wait.

[Hilke Schellmann]

But now, but now if your name is Thomas on top of that.

[Trevor Noah]

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?

[Hilke Schellmann]

Syria, Canada.

[Trevor Noah]

Passions Reading about Syria, Canada. I like it.

[Eugene Koza]

Maple syrup.

[Trevor Noah]

Thomas. You know what it is?

[Hilke Schellmann]

Thomas. Thomas, Thomas, Thomas. Thomas and white.

[Trevor Noah]

Thomas, Thomas.

[Hilke Schellmann]

Thomas. And then, well, so I think the problem is that like most tourists also like, individually calibrated to each company. So.

[Trevor Noah]

So I could only get hired at Amazon by doing this.

[Hilke Schellmann]

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.

[Trevor Noah]

But no one would say that it was 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, you know, the more you guys

[Eugene Koza]

talk, the more I realize are we, Are we under. You are 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?

[Hilke Schellmann]

Yeah, yeah, yeah. So. So you think in generally or in the hiring process?

[Eugene Koza]

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, what? Now we are going. Because I think bias is 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 decide that 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?

[Hilke Schellmann]

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 a job interview or you send in your resume and most likely is you get rejected, right? Because there's only so many jobs 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. Cause 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 in your resume, you got more points. If you had the word softball on your resume, you got fewer points. So that's probably gender discrimination, right? Cause most.

[Trevor Noah]

I would give you zero points for both in my company. Be fair. You say baseball, you say softball. I would detract points.

[Eugene Koza]

Trevor, do you see how it circled back how those.

[Hilke Schellmann]

It's not a baseball position. You know what the question is? Like, you know, like baseball.

[Trevor Noah]

But no, you know, you know, one.

[Hilke Schellmann]

In a.

[Trevor Noah]

In a way, I know this. This is going to 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 why they've made a mistake here. And they can rectify but there are some examples that you've given that blow my mind. For instance, there's one story that you go into of a guy I think by the name of Mike and he's working for Bloomberg or he's trying to get a job at Bloomberg or something. And please help me understand this. Cause 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

[Eugene Koza]

like

[Trevor Noah]

Candy Crush type stuff of popping balloons and then he got fired because of how he popped the balloons.

[Hilke Schellmann]

He didn't get fired, but he did apply to a job. Okay. He was based in Barcelona and he was based in Barcelona and applied to a job in London and he got a link immediately after applying saying like, hey, go to this link. And you know, I sort of feel like we as job applicants, we sort of force consumers of this tech, right? Because if you want the job and you get an email with the link saying like, hey, you have 48 hours. Click on this link, play this game. What are you going to do? You going to do it? Even though you were like. And he was like, while he was doing it, he was like, this is weird. Why is this Asking me sounds like

[Trevor Noah]

the beginning of a horror movie. Do you want to play a game?

[Hilke Schellmann]

Why do I have to do this? Like, it sounds great. And I think a lot of applicants technically like it better than answering 100 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 criterium I'm going to be judged on how well I like pump balloons. Or like in one of the games I had to hit hit the space bar as fast as possible. And while I was doing that, it's like you get like 15 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 space bar as fast as possible?

[Trevor 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, yeah, 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. Cuz you can't just press return. You can't just press. Come on, come on. And then that boss was like, you know, we need, we need people can press the space bar. Get me the fastest space bar presses in the world.

[Hilke Schellmann]

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 economies, companies.

[Trevor Noah]

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 space bar?

[Hilke Schellmann]

And that's one of the many things 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 space bar. 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 space bars, any order that

[Eugene Koza]

you're giving and I'm sure even the time between you deciding are you going to press the space button or not actually maybe counts. Did you really think about this instruction?

[Hilke Schellmann]

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

[Trevor Noah]

Called it Touch My Feet Cold.

[Hilke Schellmann]

It. You called it? You did call it, but so we don't know exactly. But you know, all of these, like every space bar hit and everything that I do obviously 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. I tried. 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 going up to them. It's like 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 make games. What did you do?

[Trevor Noah]

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

[Hilke Schellmann]

You win. Nice to meet nice to meet you.

[Trevor Noah]

I'm Hoa. We can be friends.

[Hilke Schellmann]

This is, this is my research. That would be. I. I should have done that. That would have been much more interesting. But what were the game?

[Trevor Noah]

What did you do?

[Hilke Schellmann]

The game was that I have to approach strangers and like, say yes. Yes. My reward was just like, well, getting to know people and like learning about them.

[Trevor 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 speak what happened?

[Hilke Schellmann]

That's what I tell my journalism students.

[Trevor Noah]

What happened when it didn't go well?

[Hilke Schellmann]

Well, I'm still here, so I was afraid I was gonna get decapitated. Right. People are nice and they're like, what the. But you know, I'm still here and you know, sometimes people were just like, eh. And like, just left me standing there

[Trevor Noah]

and I was like, as bad as you thought?

[Eugene Koza]

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.

[Trevor Noah]

Oh, that's interesting.

[Eugene Koza]

So if I walk to into a random room, then there's a bunch of women there and I'm like, hey, guys, you're playing a game where I'm trying

[Hilke Schellmann]

to be social, like stranger danger, psycho.

[Trevor Noah]

Oh, man.

[Eugene Koza]

But for, for, for a woman, it's much easier. So the biases kick, kick in again. If I go to a Midwest town as a black man from Africa and I walk in there and there's truckers and I go, howdy, folks. No one's gonna say hi to me.

[Trevor Noah]

That was a good howdy though.

[Hilke Schellmann]

Yeah, you like that? You nailed that. You nailed that.

[Trevor Noah]

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

[Eugene Koza]

Close your eyes now. Howdy, folks.

[Trevor Noah]

Aye, who's that?

[Hilke Schellmann]

Okay, that was not bad. That was not bad.

[Trevor Noah]

I'm in.

[Eugene Koza]

Darn.

[Trevor Noah]

Once I look up, things might change.

[Hilke Schellmann]

Yeah.

[Eugene Koza]

So you see how biases is informing how the. What the outcome ends up being, cuz.

[Hilke Schellmann]

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.

[Eugene Koza]

You were not biased. 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, let's threaten.

[Hilke Schellmann]

That's True.

[Eugene Koza]

Exactly. So the biases 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. But then, but then six at night.

[Trevor Noah]

Yeah, but then that raises the question then, is there ever going to be a world without bias? And is that what we should be looking for?

[Hilke Schellmann]

I mean, look, we can all wish, but we know that that's. That's never going to happen. Like, we hu. We humans are biased machines.

[Trevor Noah]

Yeah, but. But now that the. But now that the machines. You're right, but now that the machines are doing the job.

[Eugene Koza]

Job.

[Trevor Noah]

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 here's what I think about in what you're talking, in what you're saying. 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.

[Eugene Koza]

Social settings.

[Trevor Noah]

Social settings said bias exists. Right Now AI has gotten involved, and we see the AI mirroring many of our biases. Yeah, 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 women or because they said black. But now you can, you can actually look at the data and. 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.

[Eugene Koza]

We'd be like, oh, my God, AI.

[Trevor Noah]

Look how racist the racist AI was to use. I'm sorry, my friend.

[Eugene Koza]

AI is a Trojan horse. You're right.

[Trevor Noah]

Do you see a world where that's possible?

[Hilke Schellmann]

Yeah, yeah, yeah. I mean, I wish companies would actually look at these tools more closely. I think the general notion, though, 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'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 or something like that. Right. 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 parsers use to predict if you're gonna be good at the job, they would find those keywords that are learned from lawyers and other places. 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. You know. And I came to this as a human. I remember like for the first time 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?

[Eugene Koza]

What?

[Hilke Schellmann]

He's like, it's a pattern machine. It does a statistical analysis for whatever reason, like playing lacrosse in high school. A bunch of people who were in the job have that criterium.

[Trevor Noah]

Lacrosse?

[Hilke Schellmann]

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, as a same game, just a bigger field.

[Trevor Noah]

Hilker's on my team, minus points for both.

[Eugene Koza]

Like how you saw pickleball and oh, beach ball.

[Hilke Schellmann]

We call it beach ball.

[Trevor Noah]

Don't, don't bring pickleball to this. Please, please, let's not bring.

[Hilke Schellmann]

Trevor doesn't want to talk about pickleball.

[Trevor Noah]

Don't press anything. We've got more. What now? After this,

[Hilke Schellmann]

Choose to show up with the bold styling of the Mazda CX30.

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[Eugene Koza]

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

[Hilke Schellmann]

How's that going?

[Eugene Koza]

Very well. Because I'm, I'm just. Because I've worked in retail before in South Africa and, 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 when do you come from, come from first. Then when you get let go, you do what they call an exit interview. 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 or 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, 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. 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 the job?

[Hilke Schellmann]

I was going to say like that, you know, like when you think about it, like how these kinds of statistics and prediction works, it's, it precedes AI by a long time. Right. Like we know statistically that if you have a longer commute to your job site, 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 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

[Trevor Noah]

at it, it only says something about your situation.

[Hilke Schellmann]

Yeah. And you know, and also like, well, first of all, like, there are people who do a 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, 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 redlining. So if you like start taking out zip codes, you might actually take out huge swath of African American population or Asian American population around the world, to be honest. Yeah. And I think 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.

[Eugene Koza]

Again, ability to enforce.

[Hilke Schellmann]

Oh my God, how did you know that? I think it's plausible deniability of the companies that use it and buy it 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 YouTube was biasing women and there's like, 2 million people that apply to this, 2 million women that apply to this company, and you use the bias algorithm on that, so suddenly you have potentially 2 million claims. That's why we see what I think is sort of a cloak of silence around this, because companies obviously don't want to come out. I've had so many people who work in HR tell me after the book came out, oh, yeah, we used that tool that you talk about, and we stopped using it. 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 talk about this? They're like, oh, absolutely not. But we need to learn. Like, we'll never get better. We never. We. We can't put pressure on the vendors to build better tools if we don't know how the tools work. And. 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, you know, like, sort of saves the 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 and now start, 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.

[Trevor Noah]

So when you look at what they're doing, you know, it seems like. And maybe I'm going to a dystopian conclusion, but. 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, was like, like your Uber rating is a possibility in the future. Which sounds like something China was doing or trialing, by the way.

[Hilke Schellmann]

Yeah, yeah. With us, with the social.

[Trevor Noah]

Yes.

[Hilke Schellmann]

Remember that we're like, basically you have a high social score, you get to travel and you get like certain benefits of society. But if you like jaywalk, Grandma, that's me.

[Eugene Koza]

No, really.

[Trevor Noah]

And so, but now when, when I think of that, I'm like, like, are we heading towards a world where, where a company can hire you or fire you? Looking at your Spotify playlist going, oh, this.

[Hilke Schellmann]

Oh no.

[Trevor Noah]

Oh no.

[Hilke Schellmann]

Oh 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 big finding a few years ago and I think it was like that. A lot of computer scientists are really into manga consciousness. So the question is like, well, if you look at then resumes, should you hire the people that like mangas? 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 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 leave 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?

[Trevor Noah]

Like if you 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. Yeah, 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, Eugene.

[Eugene Koza]

We know you better. We know you better than you know yourself.

[Trevor Noah]

So job. And you're like, what are you talking about?

[Eugene Koza]

Yeah, 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.

[Hilke Schellmann]

Oh, yeah, totally. And some of them use this kind of technology, like to find out one way. Video interviews, like. And yeah, I mean, I think, I think what fundamentally comes down to. It's kind of funny what, 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 were. It sort of filters out the people who are good about talking about doing

[Trevor Noah]

the job as opposed to doing the job.

[Hilke Schellmann]

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. No, never. What? So you know, As always, not all men, but a lot us little old

[Trevor Noah]

men acting like we know more than we do us. Come on, Hilka.

[Hilke Schellmann]

Ooh, mansplaining. What?

[Eugene Koza]

Wait, I think, I think this is highlighting yet again the same point again of saying that biases have gotten it 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? So we have an idea.

[Hilke Schellmann]

I never heard about this talkative lawyer, but I'm sort of.

[Eugene Koza]

You are someone who goes razzle dazzle. We've seen the lawyers that, that represent rat.

[Trevor Noah]

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

[Hilke Schellmann]

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 because, you know, like, 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, you can't find, like, things like teamwork. Are you a good collaborator?

[Trevor Noah]

Yeah, you don't know.

[Hilke Schellmann]

How are you going to know that from a resume? How are you going to know that from a job interview? You can ask, like, questions like, well, tell me how you overcome, you know, really 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. That is.

[Trevor Noah]

Yeah, look at that.

[Hilke Schellmann]

Totally doesn't work for most companies to hire 100 people and then let 99 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, see

[Trevor Noah]

how they actually are at the job.

[Hilke Schellmann]

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

[Trevor Noah]

Have you suggested this to companies? Because this is. I like this idea.

[Eugene Koza]

You.

[Trevor Noah]

I really do.

[Hilke Schellmann]

You.

[Trevor Noah]

I really do.

[Hilke Schellmann]

I do. I mean, I think it turns, you know, I do think. 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 different capabilities and different things that you have to test for.

[Eugene Koza]

Right.

[Hilke Schellmann]

And some of that 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 and you to get, to get

[Trevor Noah]

picked, obviously everybody 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 gonna say to people, yeah, random number. Just bring the person in. Yeah, I don't.

[Hilke Schellmann]

If they have the basic capabilities.

[Trevor Noah]

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

[Hilke Schellmann]

I'M down. Yeah, try that. I'm down.

[Trevor Noah]

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

[Hilke Schellmann]

Yes.

[Trevor 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 what we see.

[Hilke Schellmann]

The surveillance at work.

[Trevor Noah]

Yeah. Like for instance, and I know there was an explosion of this during COVID once people were working remote and then companies were 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 and 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.

[Hilke Schellmann]

Yeah, I mean, I think it's often like, you know, it's called like a, 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 they might be a vice president of sales in Europe and one of them might be more successful or not. That's actually kind of vague and hard. But for the sake of this example, we'll assume, okay, maybe the European person is better at their job. And so then an AI will 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? It can kind of assess a lot of different things and then tell the person in the us, like, hey, the person that has 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 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? But we sort of. And you know, what does it mean to be successful? Like, we had this like, whole thing. Probably don't remember this. And I might be dating myself, but they 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. My teacher is. Well, it turns out like, these algorithms were terrible, and a lot of teachers were, like, put in rubber rooms because their students didn't gain enough knowledge in a year. But it could be that they were already at the top.

[Trevor Noah]

Wait, the teachers were put in what

[Hilke Schellmann]

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.

[Trevor Noah]

Rubber rooms, yeah.

[Eugene Koza]

Oh.

[Trevor Noah]

Cause in my head, I was like, picturing a room.

[Hilke Schellmann]

Is there to go somewhere to a

[Trevor Noah]

room made out of rubber?

[Hilke Schellmann]

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

[Trevor Noah]

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

[Hilke Schellmann]

I don't actually know the history of that. Good question. Yeah, I want to know. You want to know about the rubber room? Yeah. No, no.

[Trevor Noah]

If someone's taking me to a rubber room, I want to know what a rubber room is.

[Eugene Koza]

I would actually. You would love to take you to the rubber room.

[Hilke Schellmann]

Oh, wow. Oh, my God. I don't. I don't. I don't know if I want to go there.

[Trevor Noah]

Wow.

[Eugene Koza]

You're going to get paid for free. You don't have to do nothing. At 2, wouldn't you want to be in a rubber room at Playbo? Play squash play in a rubber room?

[Trevor Noah]

It used to fall in a rubber room.

[Eugene Koza]

I still can't believe how digital Peeping Tom and the digital Tell Tales is just everywhere now.

[Hilke Schellmann]

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

[Trevor Noah]

Yeah.

[Hilke Schellmann]

And then we see when people realize, oh, everything gets recorded. We see sort of what we call productivity theory theater, you know, that people,

[Eugene Koza]

like, slow it down. Do you say productivity theater?

[Hilke Schellmann]

Yeah, it's like. Like sort of gaming the algorithms.

[Trevor Noah]

So you're sort of acting like we're busy.

[Hilke Schellmann]

Exactly. So, like, in the morning, like, you check in on Slack and be like, hey, everyone, Good morning. Like 7:45 crazy. And then you turn around and take your dog for a walk. And then you don't show up at your desk at 10. But. But smoke and squeens. You were like, you were productive at 7:45. Well, you know, an algorithm will now be able to understand that you haven't said anything.

[Trevor Noah]

Let me 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

[Hilke Schellmann]

people

[Trevor Noah]

were just constantly sending emails and messages. And I always felt like they were unnecessary. And they were always at random times. Sometimes on a weekend, some I was like, what? But now when you put it that way, I go, they weren't working. They were trying to maintain the appearance of working productivity. So you're just like, yeah, you send a message at 6:00am and people are like, man you up at 6:00am yeah.

[Hilke Schellmann]

Wow. Wow. Emails at 3:00am what the.

[Trevor Noah]

Well, you just don't stop working.

[Hilke Schellmann]

Yeah. And you know, I do think that

[Trevor Noah]

meanwhile you just left the club.

[Hilke Schellmann]

Send, schedule, schedule, schedule, send, schedule, send.

[Trevor Noah]

Oh, schedule. Look at this.

[Hilke Schellmann]

Yeah, but, you know, think about it like the, the, the office was like sort of always a place to look for productivity. Right. Because you had a manager look at everyone who's working, and if you left early, that was not so good. Even though we know that some people just sat at their computer, surf the Internet and didn't do any work, but they were physically at their seats, we didn't have the technology to actually 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 the question is, 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? And what does successful in this job mean?

[Trevor Noah]

Those, those computer systems you're speaking about? I remember reading about how warehouses also using it like, 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 typing, see what you're doing and how you're doing it. But in warehouses, 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.

[Hilke Schellmann]

And they look at different algorithms. How many, like, items do you put in a box per minute, per hour?

[Trevor Noah]

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

[Hilke Schellmann]

Technically that would be illegal, but.

[Trevor Noah]

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

[Eugene Koza]

Yeah.

[Hilke Schellmann]

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

[Trevor Noah]

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

[Eugene Koza]

As a conspiracy theorist, I'll always say who, who help is benefiting from, from this. Who is? Because I, I look at, at Covet and you explained to me how tough Covet was in the city. Yeah. 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 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 this. So how about we give them a hand and make money out of them?

[Hilke Schellmann]

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 going to buy company, like success AI? Like, we don't really see, it's not really a market. Right. Like this. 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 he like vastly outnumbered AI for like vendors, the, 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 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 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 they jump and look at that and be like, the way you talk to your kid? No. Good. Like no one wants, you're not fit

[Trevor Noah]

to be a parent. We'd love to hire you as a manager at our company.

[Eugene Koza]

How's your bladder?

[Hilke Schellmann]

You have the personality to enforce the algorithm.

[Trevor 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, how AI is affecting who gets hired and how you get hired, who gets to stay in the job and how they get fired. 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 something, let's break it down. Is there something lawmakers can do? Is there something that companies can do? And then is there something that just workers can do?

[Hilke Schellmann]

Yeah. So I do think there's room for improvement in all levels. So I do think that there could be better loss here, for example, what we see, you know, the funny thing is like I am originally from Germany, but I remember talking to the former head of talent acquisition at Vodafone, which is a huge telecommunications company in Europe and other parts of the world, not so big in the US and he was laughing, he's like, you know what, like, we use AI in hiring now. And when you want to upload your resume, there's like Germany and the rest of the world 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 have a workers council. It's not a union. Sounds like it, but it's different. And the workers council, there's actually a law and they get to co decide technology in the workplace.

[Trevor Noah]

Oh.

[Hilke Schellmann]

So some of the surveillance technology we don't see happening in Germany because the, you know, this worker's council has been notified. And I think a lot of companies shy away from using some of this, like very intrusive AI tools. But in the United States, for example, anything that happens on a work computer belongs to the company. So don't do it like private slack messages, like private surfing, all of that can be recorded by the company and it belongs to them. 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 use in them. So for example, some of it is very basic but like if you suddenly print a lot that might be an indication that you are at flight risk. So maybe the company lawyer should be looking into what you're moving away from your computer. Like those kinds of like sort of digital tell tales, you know, I think companies should tell us and maybe there should be a way for like employees to co decision making some of the time. You know, if you work in a nuclear power plant, maybe you do want AI to scan for like exposure to radiation. I would want that. Like so you know, there might be cases where this is like actually really helpful 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 won'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 in them and they don't even know it. And I think, think that's really unfair and there's no way to push against that. I think also like 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 show me, show me the evidence, show me how it works. I'd be happy to look at it and I'd be open to it. 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 what is out there and like try some of the tools. Like you know, there's definitely better ways to like have a machine readable algorithm and there's things you can do. Yeah, but you know when like 5,000 people apply for one job and they close the job description after you know that they, they, they close the job portal after 24 hours. Yeah, 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. 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. So he got a settlement. He actually started a case. So that was like a gold mine for me. I call him patient Zero because he's sort of the first person who encountered these kind of AI tools in the hiring for face and then actually got the data on himself. Right. That's like gold to me. So we could sort of unravel 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, I think we talk a lot about sentencing guidelines with AI to send people to prison, should you get a mortgage. And I think those are all, 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. It matters if I can put food on the table. Also, happiness is tied to our jobs. For many people. We spend enormous amounts of hours at our jobs, so 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 systems. 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.

[Trevor Noah]

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

[Hilke Schellmann]

Because, I mean, 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 facial expressions 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 they're only like, you know, more men than women in the data la la. Yeah. 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.

[Trevor Noah]

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

[Hilke Schellmann]

Let's do.

[Trevor Noah]

Oh no. Yeah. Thank you very much. You know, from, from me, you know, from Syria, from Canada. And Thomas, we just want to say let's, let's. Thank you very much.

[Hilke Schellmann]

Let's do it and see how it works.

[Trevor Noah]

Thank you very much.

[Hilke Schellmann]

Thank you.

[Trevor Noah]

What now with Trevor Noah is produced by Dayzero Productions in partnership with Sirius xm. The show is executive produced by Trevor Noah, Sanaz Yamin and Jess Hackle. Rebecca Chain is our producer. Our development researcher is Marcia Robiou. Music mixing and mastering by Hannis Brown. Random other stuff by Ryan Harduf. Thank you so much for listening. Join me next week for another episode of what Now.

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[Kaitlin Coleman]

Hi, I'm Caitlin Coleman, winner of Target's HBCU Design Challenge. This challenge moved me closer to my dream of becoming a fashion designer through mentorship and support. You can find my design, along with creations from other Black founders, in Target's Black History Month collection.