Part 1 of 2
In this episode of Career Club Live, Bob Goodwin interviews Emmy Award-winning journalist Hilke Schellmann about her new book "The Algorithm" and how AI is transforming hiring and the workplace. They discuss how AI is used in applicant tracking systems, resume screening, and video interviews, as well as the potential for bias. Hilke also shares insights into how companies are using AI to monitor employees and what regulations may be needed to ensure fairness and transparency. This thought-provoking conversation provides valuable perspectives on both the opportunities and risks of AI in our working lives.
Part 1 of 2
In this episode of Career Club Live, Bob Goodwin interviews Emmy Award-winning journalist Hilke Schellmann about her new book "The Algorithm" and how AI is transforming hiring and the workplace. They discuss how AI is used in applicant tracking systems, resume screening, and video interviews, as well as the potential for bias. Hilke also shares insights into how companies are using AI to monitor employees and what regulations may be needed to ensure fairness and transparency. This thought-provoking conversation provides valuable perspectives on both the opportunities and risks of AI in our working lives.
Hello everybody, this is Bob Goodwin and welcome to another episode of Career Club Live. Before we begin, we've got a couple new things to tell you about at Career Club. If you're a job seeker, we are now offering some free resources, including a free weekly coaching call every Thursday at 1 o'clock Eastern. Just go to career. club, click on for job seekers free resources and you'll see it. And if you're a company, we're starting something new to add to the candidate experience and help build your employer brand by changing rejection letters into read direction letters providing free career resources to people who will not be moving forward in the hiring process. It's a great way to build your brand and have a differentiated candidate experience. Again, you can learn more about that at career. club under for employers and then under candidate experience.
Bob Goodwin:So, with that said, commercial over, I am extremely excited to welcome our guest today, Hilke Schellman. I'm going to read a little bit about this because her background is phenomenal. So is an Emmy award-winning journalist and the insightful author of the recently published book the Algorithm how the Rise of Artificial Intelligence Will Change Everything and what we Can Do to Protect Our Future. Her groundbreaking work has been featured in prestigious outlets like the Wall Street Journal, time Magazine, the New York Times, the Guardian, the MIT Technology Review, and it delves into the profound impact of artificial intelligence on the workforce and society. Besides her writing, is also a professor at NYU, where she shapes the minds of future journalists with her deep understanding of AI's ethical implications and transformative potential. So today we're going to explore the depths of AI's influence on our world, navigating the complex interplay between technology and human rights. And with that, let me welcome .
Hilke Schellmann:Oh wonderful. Thank you so much for that kind introduction, bob. I'm so delighted to be here.
Bob Goodwin:No, likewise and, look, I love all my guests. I am particularly over the moon today because you know, in all seriousness, you know, , your topic, ai. Obviously that's dominating headlines, but our core audience is both job seekers and HR executives, and so this is like the perfect intersection of all of those things, and you are a global expert on the topic, so it's going to be super, super fun. But before we dive into all that, as we are want to do, we'd love to just learn a little bit more about you as a human being. So, just another robot, exactly. Where do we find you today? Where are you?
Hilke Schellmann:I'm in Brooklyn, New York. I'm in my home office. It's you know, our four year old is off from daycare, so we all home during spring break.
Bob Goodwin:Yes, oh, that's fine. I'm not sure it feels like spring break yet, but okay, now you were born, and born and raised.
Hilke Schellmann:New Yorker. No, I'm born and raised in Germany. I went to high school all the way up to high school there, got my bachelor's and master's degree at the Humboldt University in Berlin. But I got a full bride to go to NYU in 2003. And that started all of this. You know, great American adventure for me. I started a documentary art collaborative and then I went back to Berlin and studied investigative journalism at Columbia State School and I somehow got trapped into staying.
Bob Goodwin:I don't know how you figured out the accent, but it's spot on. It is absolutely spot on.
Hilke Schellmann:Oh, I will tell all my friends to make fun of my German accent.
Bob Goodwin:You don't have one, so you anticipate one of the questions Tell me a little bit about your family. Is it a four-year-old?
Hilke Schellmann:Yes, she just turned four. You know she's four, going on 15. She thinks she, you know she's ready to move out and, you know, conquer the world. We are just, like you know, little helpers on the way. She's fabulous. So, yeah, I live with a partner. I have a really cute daughter who was born three weeks before the lockdown and the pandemic started. So she's, like you know, we will always be with my every birthday and like, oh yeah, that, that that happened, yeah, and so I'm. You know I work as a journalist most of the time. So I do like two days of the week and I teach usually two classes at NYU and sort of divide my time in like the best possible way. I get to do awesome journalism and I get to teach journalists. So it's, you know, I found, I found my dream job.
Bob Goodwin:Well, which is awesome, and we love people finding their dream jobs at Career Club. I mentioned the Emmy Award. I mean, that's not something that you just get to kind of say all the time. Do you mind telling people just a little bit about what that's?
Hilke Schellmann:totally, I'd be, I'd be, I'd be delighted to. So I think you know, in my previous life as a journalist there was always a journalist but I did a lot of documentary work and one of the documentaries we did was that was my co director and I went to Pakistan and followed a case on sexual assault and sexual violence in Pakistan and sort of film for like three, three years, this girl's story going through the legal system and and all of the pushbacks you see from society and especially men, and we did a film out of that and you know we got lucky that Sundance showed it at the film festival and frontline jumped on the chance to to broadcast it on PBS and you know we got an Emmy for that. So that was really, really fantastic.
Bob Goodwin:That is very impressive, and obviously you didn't rest on your laurels. You moved on to a new topic of interest to you, which is what we're going to talk about.
Hilke Schellmann:Yeah, you know, sort of founded by by chance, a little bit right like I've doing. I've been doing like more or less social justice documentaries and podcasts and then one day in 2017, november 2017, I was at a conference in Washington DC talking to consumer lawyers, had no idea about AI and you know, I had nothing to do with hiring and I needed a train ride from the conference to the train station and I talked to the lift driver and I just, you know, I asked him like how was your day? And he was like you know, my day is really weird. And I was like what you know how? So? And he said that he was interviewed by a robot for for a job as a baggage handler.
Hilke Schellmann:And I was like what robots doing job interview? Never heard of that. So I think you know what it was is like sort of a pre recorded voice asking him three questions. But you know, I was really interested in that. And then I, you know, went down the rabbit hole. But you know and learn how, like how much we use AI and hiring and at work, and you know, now also we see signals of AI results being being used in firings. So that was sort of like the beginning that I was like wow, I met someone who did a job interview with the corner called robot, and I had never heard of that. And lo and behold, there's a whole world out there.
Bob Goodwin:Side note for listeners this is like a really interesting example to me of networking. Right, you meet people, you engage them in conversation that you never know the way it's going to break. It's always kind of this weird fractal of like I wouldn't expect that, but that's cool and but you have to put yourself out there, ask questions, be interested and you never know what you're going to. You never know who knew right, like you know.
Hilke Schellmann:and then I went to a conference on AI and you know the topic came up again and in a sparsely attended presentation, and I was like, oh, somebody else was talking about similar things. This now somebody who had just left the Equal Employment Opportunity Commission and she said that she can't sleep at night because companies use like basic algorithms to check for absenteeism and people's calendars of their workers and she's really worried that this might hurt mothers and people with disabilities, who often have, you know, longer absentee rates than others. But they're protected classes. You're not allowed to fire them or do anything against them if, if them is more time than others. So she was really worried about that.
Bob Goodwin:She should be. I want to take back here a little bit because I want to, you know, dig into it, but just to kind of completely level set, because the book just came out, at the beginning of January, right.
Hilke Schellmann:Yeah, January 2nd is like the new year.
Bob Goodwin:So I mean the first question. I don't mean for it to be completely obvious, but why this book and why now?
Hilke Schellmann:You know, I've been working on this for like five years or so now. Right, like researching this, but I felt like there's really like the world is really changing here and we now have all these indications that almost all Fortune 500 companies use these kinds of AI tools, like hiring tools, somewhere in their hiring funnel, right from like resume screening to even finding folks to reach out to, to like ask them to do one way, video interviews, right when there's no human on the other side, to playing games. It really felt like a real sea change. And also we see that, like for workplace monitoring and surveillance, we see eight of out of the 10 largest companies in the US do monitor some of their workers and we now see that, like really really large companies use some of these AI vendors to check for sentiment analysis and check all of our writing. So it feels like you know, like AI has taken over the world of work and how into some of these, a job conference, and it's like all these hundreds of vendors are all AI, all AI.
Hilke Schellmann:And I think when I talk to job applicants, I was surprised that they just didn't know that this has happened, that somewhere, maybe vaguely, I knew that, maybe if they post something on LinkedIn. There was a, maybe screened by AI, but I think no one knew how vast this industry has mushrooms and we didn't see a lot of that. So when you do these conferences, there's like 10,000 people go to HR Tech every year in Las Vegas and I was like, wow, there's a couple of reporters. There isn't a whole lot going on here, but it feels like we are changing so much. We're trying to quantify human beings in a mathematical way, much more so than we ever could. Obviously, the field of psychometrics has tried that for a long time, but it felt like this is a real sea change and we need to talk about it now.
Bob Goodwin:No, I think that's right. And so, again, we're going to get into a lot of this more so, as you think about how AI is being used, let's just start at the start. Somebody does a job posting. They've got their applicant tracking system in place. I think most listeners would know the term ATS. So there's an ATS and its job is to read the flood of resumes coming in and at least start to have an in and an out pile.
Bob Goodwin:Yes, yes, While you apply for this job this is a brain surgeon and you're a bricklayer probably not a good fit and in theory you shunt the right ones over to town acquisition or a hiring manager or wherever. That's the theory. How's it work?
Hilke Schellmann:I mean, we don't know a whole lot about this world. Like we know, I talk to all the large job platforms like LinkedIn and Indeed, and all of them use some form of AI. So if you submit your resume via them, your resume will, in all likelihood, check by AI. And we know that companies use these applicant tracking systems and I think they used to be sort of glorified Excel sheets, so just check where is a candidate in the hiring funnel. But now we know from all of the largest vendors that they have AI built in, but there's no central place where companies need to tell anyone the government or anyone what they're doing. So we don't actually know. What do the companies turn on and off? Which AI tool are they using? How is it being trained? What's the training data which is really important in resume screening or in AI tools in general? So what I know is I talk to a bunch of employment lawyers and others who were sort of there at the moment when maybe a vendor has their resume screening tool and they want to sell to a company and a company is doing some due diligence, they may bring in employment lawyers or folks in that space to do their due diligence and what they have found is a little bit worrisome sometimes. So one person I talked to, dr John Scott. He said that he found he checked five resume screeners and all of them had problems in their bias variables. So one of them had learned that the first name, thomas, was a predictor of success. Another one had that, like Syria, and the word Syria and the word Canada on a resume was an indicator of success. So when I talked to employment lawyers they were like this could be discrimination based on national origin, like it's not allowed to take locations into consideration. We saw another employment lawyer found the word Africa an African-American on resumes as a predictor. They also found one other resume screener that had predicted that if you had the word baseball on your resume you got more points, so it was a predictor of success, and if you had the word softball on your resume, that you would get fewer points because it was a predictor that you wouldn't be successful at this company.
Hilke Schellmann:So probably where this all coming from is from the training data right that companies maybe use resumes of the folks that are currently in the job or have applied and have gotten an interview with the last year or so and then they hand it over to an AI tool, put it ingested into the system and then the AI tool looks for statistical significance. So maybe there are lots of people at the word Canada on their resume that were successful at the company. Good for them, but that's not. Any human knows that there's actually not a predictor of success. Neither is the first name, thomas, and it really shouldn't be about hobbies, because, as you can tell, with baseball, softball, there's probably a gender discrimination that comes into play here. Right, like most men in the United States, they like and maybe play baseball and women prefer often play softball. So that's sort of the problem. And if you have a company that is not diverse, that maybe has some gender hiring biases or problems in the past I mean you know it's a company who has, like gender disparities with more men you know this kind of stuff can easily creep in into the system if it's not closely monitored. And you know it's kind of a little bit interesting that maybe the vendors didn't find that out themselves, like somebody from outside have to come in to find these problems.
Hilke Schellmann:And we see a lot of these tools. You know they're bought by companies because they're overwhelmed by applications. You know the beauty of job platforms is like I get so many jobs as a job seeker and I can just apply, apply and it's wonderful. But I think on the other side it has led to companies feeling absolutely overwhelmed with millions of applications, like I think IBM gets 5 million applications a year, google, I mean it's just like staggering the numbers. So they want to buy a technological solution that is efficient, you know, saves the money, saves them labor, finds the most qualified candidates and is bias free. So it's definitely efficient and I think it saves a lot of companies, a lot of labor and money. But we haven't really seen any evidence of finds the most qualified candidates and that is not biased. And that's really problematic because now we're using these tools at scale.
Bob Goodwin:So wow. So yes, the thing is like when it's the opacity that you're talking about, it's just a black box, so like I can't see what's in it. Therefore, Like that's not healthy. Correlation and causality are not the same.
Hilke Schellmann:Ah, it's a huge problem, right. It's like you know like how long Thomas Really? Yeah, it's, you know it's probably correlation, right, like it's statistically as significant. But we all know that if your name is Thomas, that doesn't qualify you for a job, right, it's not causally related to a job Any human would know that. But obviously a AI tool doesn't know that. It just looks for a statistical significance. So you know there probably were some Thomas' in the pile that was successful. Good for them. But if you don't, you know, monitor these tools and like sort of really critically, skeptically, look at them and keep supervising them, these problems can easily come in, because you know you usually keep giving a training data of new people and then this kind of stuff can keep coming in.
Bob Goodwin:Well. So I mean it's like one is the quantity of data it has access to. So company X and company Y may have very different data pools to be pulling from, and then there's the quality of the data. There's the historical as you kind of pointed out earlier, the historical biases of their hiring practices, such as a microscope.
Hilke Schellmann:They're all embedded into the machines.
Bob Goodwin:I mean it's almost like we're going back 40 years to like one of the most foundational computational principles. Garbage in, garbage out, like if you give it bad data and then you analyze it in not a great way, you're going to get not a great result. But the good news with AI is we can do it at scale right.
Hilke Schellmann:Yeah, and herein lies the problem, right, that like I do think, that like you know one hiring manager and you know, I'm sure you know we have unconscious bias of humans, like we're not very good at hiring either and in fact we often feel like we are very objective and fair and in reality we like people who compliment us, and you know people went to the same school and yaddy, yaddy, yaddy.
Hilke Schellmann:So that is a huge problem too, but like one human bias hiring manager can maybe discriminate against so many people and I'm sorry, you know they, those people are being discriminated against in one year. But an AI tool that is used on millions or hundreds of thousands of resumes that has a problem with, like, downgrading mostly women and upgrading mostly men, I mean you could have gender discrimination against hundreds of thousands of people. And I think you know companies do like to use this technology. They're a little bit afraid what might happen if they come forward saying that the technology didn't work, that they are employed.
Hilke Schellmann:So you know, I've talked to a lot of HR managers said like, oh yeah, we had, like, we did this for a couple of years. We use this tool and we found out it doesn't work. So we quietly, you know, let go of it. The problem is like we are not the wiser, right? We don't know that that there's a problem. The vendors aren't being pressured to change their tools and make them better, and so this is the next company that buys the tool, right? So I think that's really the problem that companies are so afraid of class action lawsuits, because you know if they come forward and say like, oh yeah, we've been discriminated against for years.
Hilke Schellmann:It was. You know there's a gender bias against most, mostly women, that I mean there's a huge problem. So I think you know I need to talk to these, you know sort of whistleblowers or folks who are in the know to tell us what, what is happening. And that's just not good enough because these are like you know, as you all know, it's like it's high stakes, decision and matters. If I get a job right, I'm nervous before a job interview because it could literally change my life. Right, I need it.
Hilke Schellmann:Most of us need to work to make money and put roof over our heads and feed our children. But also, if I have a job that, like, makes me happy, fulfills me, that is a big deal Our identity is tied to. You know, I spend so much time at work. You know hope, it's like somewhat rewarding for people, so it does matter. I know we get. You know a lot of people get rejected all the time, so it feels like, oh yeah, it's another way to get rejected. But if I get rejected for my dream job because I'm not the most qualified candidate, I'm not qualified enough, I get it, you know, would I be sad totally. But if I would find out that I was rejected because at the word softball on my resume and I was discriminated because I didn't have the word baseball, which has nothing to do with the job. I would be upset Like that is not fair.
Bob Goodwin:Okay, so let's talk for a minute about solutions. The problem seems pretty profound. If you were in front of you know, shirm, or some large HR organization and say guys like we can all agree that, like these are some of the issues, what are the top one, two, three things that you recommend to them?
Hilke Schellmann:Yeah. So I mean, I think there's there's there's a bunch of things that we should do. I think first is like radical transparency and explainability. You know it's a problem when companies use deep neural networks and you can immediately forget what that means. But it means that we use training data to train an AI tool, but we don't necessarily know as humans what the tool then infers upon. So we don't know does it use these and these keywords? And not all vendors check, like there is a complicated way to check. So I think that's a real problem. If we build tools where we don't know how the tool sort of, you know, judges applicants, that is a real problem. So I think that that would be the first thing like transparency and explainability.
Hilke Schellmann:How was somebody judged? Not only were they judged by AI, you know, was there an AI tool in the in the mix? Because I do feel that most consumers are sort of most job applicants. I call them like forced consumers, because if you want the job and I send you a link to do a one way video interview with AI, you're going to say no, no, you want the job. So you don't really have a way to say no to this. So I mean, I'm glad if the company tells you that AI is used, but it's actually not super helpful. But explaining how were you judged by the AI or how was their results inferred, I think that could be really, really helpful for researchers and others.
Hilke Schellmann:I also think we need, like some sort of regulation here that like puts like guardrails up for like some of these high stakes decision makings that companies need to make sure that they don't do any harm, and more than what we see maybe right now in New York City, which is like kind of one of the only places that has a pretty strong law here, or strong ish law. I wanted to have a strong law to say that you know, companies who use AI hiring tools need to be audited once a year. So there's a lot of you know. It's like it's a very loose law, so a lot of companies, I think, get out of it and the audits are not very aggressive either. So that's another problem and I think in general, I think we need to have a much, much larger discussion like how should we hire people? Like we know, resumes are not very predictive. Like should we actually use them in hiring? Like what are some of the ways that we should hire people Like, for example.
Hilke Schellmann:We see a lot of personality tests. They're also not very predictive. They may be 5-10% predictive. So that means that 95 to 90% of your success on a job has nothing to do with your personality. Because you know we are humans, like we get to sometimes overcome our, you know our problems. Maybe my personality is X, but you know I can work hard against that. But you know these tools can't really obviously, you know, like, see that or understand that in a way, like you know no one can take that into account. So I think we really need to think through, like what do we need to? How can we do this better? Can we have virtual reality to test people on the job? Maybe that is a good way to test folks. Maybe have a more holistic approach. We have different assessments. You have look at the resume, you look at a job interview, so it's not just one screen like either you have the personality or you're out Like we need to have a much larger discussion here that I'm, I hope, to push a little bit.
Bob Goodwin:No, no, I think it's great. And then you know, on the first, first all, I did an interview with a CHRO of 130,000 person company recently. They hate resumes, right? Because? They are desperately trying to find what is the next version of. You know candidate identification and qualification. You know where they're way more interested in things like your desire to contribute, your ability to be an agile learner, your ability to be resilient.
Bob Goodwin:I mean things that really are going to impact your ability to survive, not survive but even thrive through kind of everything that's going on in the world these days and what your job will be and how quickly things change. So I love all that stuff.
Hilke Schellmann:But we would, we need to like, really have a scientific discussion like how to actually test for that the hardest thing to to measure. Technology is easy to build.
Bob Goodwin:If it's any good. It's a completely different question. That's the problem right now. It's a technology is out in front of its ability to promise what it really says it can do. Yeah, yeah, it's really nice.
Hilke Schellmann:Well, I mean, my hope is that maybe we'll see like a large startup or something that can do maybe some technical assessment or some skills-based assessment on sort of hard skills, because I do think teamwork and agility is actually really hard to test and we're not there yet. But maybe if you're a software developer and you say you know Python, you put it on your resume as an hiring manager. I have no idea, are you a beginner? Are you a master developer? Like where are you at? It doesn't tell me anything about your skill level. So maybe we can do one assessment and then it gets like written into sort of the blockchain with a ledger and you have an appeal process as a job seeker and you can like send this assessment to many companies. So you don't have to redo all these different assessments all the time. It's such a drain on job seekers and I'm sure HR managers are not interested in kind of facilitating that either. If there was like sort of a larger system.
Bob Goodwin:Are you familiar with some of the tools? We're going to move on from ATSs in a second, but are you familiar with some tools that it's basically the ATS in reverse, like Job Scan and Tealhouse One?
Hilke Schellmann:Oh, yeah, yeah, yeah. I think they're very helpful for some job seekers to get like a general sense. We never know which company has the. You know how is their AI tool calibrated Like? Is it calibrated on folks in the company or is it like an off the shelf solution? So you know. But it gives you a good reading of like OK, if you have this job description, here's the resume. How much overlap do you have, right? And I think this sort of general consensus is like maybe 60 to 85% is a good overlap.
Hilke Schellmann:Don't do 100%, because then some AI tools might think you just copied the job description and like throw you out. But I think they give you a good sense of like what is actually being ingested. I think another good signal is like if you need to upload your resume to some company's website and you see that maybe your work experience isn't in the right column on the side when you upload, you know it usually tells the hears Like what we thinking, what you put in these different columns and fields, that might be an indication that your resume isn't as well machine readable as it could be. So I think Job Scan and all these other tools can be really helpful because we even see like really, you know, these are semi-structured data resumes, so computers don't always get it right to get it in the right field, and I mean some of this is very basic, some of it is very sophisticated where problems lie. So I think that might be one thing for job seekers to think through.
Bob Goodwin:Yeah, and we do encourage people to do that. One is your last point around having an ATS friendly resume. So it's not complicated, it's not a piece of art, it doesn't matter.
Hilke Schellmann:Computers are running. In a simple example.
Bob Goodwin:But then you know, when we're using tools like Job Scan or others, we encourage people back on the opacity problem. We don't know what drives the score, but the diagnostics are helpful. Right, so you might say customer success and they say client success. It's like all right, well, what's used to saying vocabulary? I mean like if you want to be understood by somebody speak their language, so let's at least speak the language. You make a really good point about not being like. So yeah, you did kind of copy the job description.
Hilke Schellmann:And now you should definitely copy the most important keywords, and I would also suggest not to use synonyms, because not all AI tools are trained on synonyms.
Hilke Schellmann:We see, sometimes they understand, sometimes they don't. And I think you know if you want to have like a really cool, exciting resume, you know maybe your machine readable isn't that exciting, but if you have, then have an in-person job and if you can always bring you know resume that you love, right with the colors and the two columns, and you can give that to a human. But you know, machine readable, if that is your first encounter it has to be machine readable. If it's not, you kind of already reject it. And you know, like some other folks who have surveyed companies also found out, that some of the ATS tools are calibrated to throw out. People have a six month and longer gap between jobs, right, and I think that's a really insidious problem because you know who knows why you had a six month job gap. Maybe you moved, maybe you're a spouse in the military, maybe you had a kid you had to take care of, forced parents or whatever Right.
Bob Goodwin:You know there are three kinds of things.
Hilke Schellmann:So I think you know, knowing that and sort of like you know, and I think sometimes you just need to just literally cover this gap with, like maybe you did do some freelance work, you know, maybe you took care of family members just to put it in there, so that a machine will put you on the yes pile if you're qualified right, because you could be the most qualified person. If you have that gap and the ATS is calibrated to throw we out, it will reject you, so it's like one and out. You don't get to, like, check with a human being and explain why this may have happened, and no.
Bob Goodwin:So think about benefits, like there are some tools for job seekers that allow you to do like a video interview.
Hilke Schellmann:Oh yeah, yeah, I think that's a great training.
Bob Goodwin:I mean you drop in your resume, you drop in the job description and then it goes okay, you want this directive marketing role at a consumer package goods company, great. And then it says, bob, can you walk me through your experience and bring you new products to market or whatever. And what I do like about them is what we know from our clients is that there is great value in hearing the words come out of your mouth, like in being able to practice and again what the exact math is on the back end of the virtual tool to say, hey, you really crushed that interview or that was a great answer. But the ability to practice and get some feedback we do find helpful. I'm curious are there other tools, maybe that one or other things that you've seen, that where AI is being used for the good, whether that's from the company's side or from the candidate side?
Hilke Schellmann:Yeah, I mean I think that some job seekers are now using Generative AI, right, chat GPT and others to help them. Maybe help them with writing cover letter, polishing their resume, especially if English is in their first language. I think could be absolutely helpful. It's like sort of a Grammarly on steroids. You just have to always check that it doesn't invent something, right. So you have to be very closely monitoring Chat GPT. But I think it actually helps also with kind of like interview questions, right, you can ask Chat GPT what are the most commonly asked interview question and maybe also prompt it for some answers and sort of you know, maybe you'll find great answers to like what are your strengths and weaknesses and you know sort of those cliche questions and you can prep for that with these video interview tools. So I think that could be really really helpful to get over this like maybe pretty unnatural setting to like talking to your camera and there's no one there, but you want to sound excitable and you know you know excited about the job and it's kind of like okay and I think you know. Another thing is that, like you know, if there's an AI involved, like actually longer answers are better than shorter for AI to actually like calibrate a result. So I think that's helpful to actually sort of like maybe tell a little bit of a story about. We know that also from behavioral questions like you know what is an obstacle you've overcome, like I think you want to talk about that in depth for for a tool to work with you. But we know very little how to pull out personality, like teamwork, out of these questions. Like I'm not 100% sure what the what the science is behind that, and I think that's a place for me to dig a little deeper for the for the next journalism series. But yeah, I think those, those tools are really great and I do think that there's also some things on the company side that is like really exciting.
Hilke Schellmann:So we see some companies that vendors that help companies sort of career lattice or career ladder more like a lattice, not a ladder any more, because people change jobs and function so many times. But we see how you know AI tools. You know kind of like LinkedIn could actually help you like your plie for one job. But then the company says the company's AI tool tells you like hey, you know you have these other five key skills. Would you also be interested in this job and this job. So you know it could like open up your possibilities. And it also inside the the company for employees.
Hilke Schellmann:What you often see is like sort of this career lattice that it tells you okay, you're a director now. People in your position five years have done this and this and here's like the skills that you need to learn, and I think that can be really helpful. I think the problem is a little bit that all of this is based again on resume data, which we know is like very limiting. You know we don't know how how well you actually are. You know how good you are at this particular skill, but I think gives us good indication. So I think it's actually a good use case for big data.