#45 - Unfiltered: AI, Bias, and What HR Keeps Getting Wrong - with "The Evil HR Lady"

Speaker A: Foreign.

Speaker B: Hello, everyone. I'm Tim Gloa, your host of the State of Work Today podcast. I have a guest, uh, joining me today that I've wanted to have on this podcast for quite some time. Uh, Suzanne Lucas, welcome to the State of Work Today podcast.

Speaker A: I am flattered that you said you wanted to have me for a long time, so thank you.

Speaker B: So Suzanne Lucas is perhaps widely known, and maybe better known, uh, on social media, as the Evil HR Lady. Um, she is, in real life, a globally recognized HR consultant, keynote speaker, and prolific writer. Uh, with a background in political science, Suzanne transitioned into HR through a temp agency before launching a pioneering HR analytics initiative at Wegmans in 1999. She went on to hold senior HR roles in the pharmaceutical industry, specializing in labor and employment law, severance and compliance. Now based in Switzerland, she operates independently, running workshops, keynotes and webinars on HR, uh, management, and AI tools like ChatGPT. Suzanne blends HR expertise with humor and improv, making complex people issues both accessible and entertaining. So, again, Suzanne, welcome. Or perhaps I should call you Ms. Evil HR Lady. Welcome to the State of Work Today podcast.

Speaker A: Thank you. And Suzanne is just fine.

Speaker B: So let's start at the beginning. How did a political science major end up becoming the Evil HR Lady?

Speaker A: Well, you know how it happened is that I had a master's degree in political science before I realized that I didn't want to do politics. Like, I don't like politics. And so I needed a job, though. Um, that dang need to, to eat and to have a roof over your head. And so I tried to figure out what I could do with my degree. And what I really wanted to do was train. That was why I was actually in a PhD program in political science and realized that I didn't want to. I didn't want to go forward, um, because I love to teach. And, um, but I decided I didn't want to teach that. And so I went to a temp agency and I could type 100 words a minute, which back in the 1900s was a really important skill because you didn't have, um, senior leadership, didn't type their own stuff. Right? So I said, it's pretty crazy just

Speaker B: thinking about that right now, isn't it?

Speaker A: It's just. It's a huge shift. It's a huge shift. I mean, computers entered the workforce in the 80s, like, on a regular basis, but it really has been in the 2000s since the. The concept of.

Speaker B: Of everybody can type.

Speaker A: Everybody can type. Like, it's not even question now. Anyway, So I went to a temp agency and I said, I want to do anything in an HR department. And so they placed me into a comp and benefits department as an HR admin covering for maternity leave. And I did that for three months. And then they placed me in a second, um, HR department as an HR admin covering for yet another maternity leave. And at the end of that six month period I could speak HR like, and, and I really got experience that I'm so incredibly grateful for. And the comp and benefits thing, uh, they had me fill out a, um, one of those comp surveys, you know, that you send in and, and evaluating this is how much we pay this person, match up the job descriptions. That was incredible. I had to go into, into my boss's office and say, I don't know what the word exempt means. Like, like I didn't know. Um, and then in the second one, it was for a small credit union

Speaker B: and

Speaker A: um, my boss there was delightful and she's like, listen, I'm going to train you on everything I can possibly train you for. And so she trained me how to interview, um, she had me doing job interviews and it was hiring bank tellers, um, which is an entry level position, but I learned how to do that. I learned how to screen resumes. Um, you know, I just, I did a little bit of everything. And then at the end of that six months, I got my first big girl job at Wegmans. And they hired me, um, to start their analytics program. And my, my boss said to me, um, he said, you are not qualified for this position, but you are the only person who applied who could do statistics. Ah. And because statistics, statistics in HR wasn't a thing. Uh, because the previous to this you didn't have, there weren't computers for all this. There weren't the analytics. As a matter of fact, in my, the first temp job, they were in the process of implementing their very first HRIs. They hadn't had an HRIs before. It was a small pharmaceutical company. It doesn't exist anymore. Um, but it was the small pharmaceutical company. They kept employee records, I am not kidding, in shoeboxes, handwritten cards in shoeboxes. It was their very first hrs. Um, and this was in 1999. And so you see today like now like doing turnover reports and, and, and looking at things on race and gender and all that, that's just standard intern activity. But in 1999 nobody knew how to do it. And somehow I got thrust into as this person with a master's Degree in political science. But there's a lot of statistics on political science. So I knew statistics, um, into these meetings with these executives, with these HR executives at, uh, Wegmans. As I am teaching them how to calculate turnover and giving them, for the first time in their lives, reports, they. It was all like gut feeling before, you know, um, but let's look at this and look how it differs in departments and all of that jazz. It was, it was a tremendous opportunity. That's how I got into hr.

Speaker B: So you started one of the earliest HR analytics programs back then. How has HR data use evolved since then? And what do you think is still being overlooked today?

Speaker A: It has evolved so much in the past 26 years. Um, since. Since I started. As I said, I was the only person that applied that could do statistics. And now so much is automated. Back then I was having to, you know, I used a program called, um, spss.

Speaker B: I love spss.

Speaker A: I haven't touched it in many, many years. But nobody has that anymore. Now you would just punch a button in Workday or what? I haven't used Workday, but I assume you just punch a button and it would give you your time to hire and you're all that, whatever it needs. Right. Um, and Workdays actually was on my mind because how far has it come when we look at computer analysis? Workday is currently in a lawsuit because as people are claiming that Workday, um, well, this one man is claiming that Workday itself is discriminating against him as a black man because he's using Workday to apply and he's not getting interviews. And Workday is theoretically, allegedly. I'm not stating this as fact, this is what he's alleging, um, is making the decision whether to advance or reject candidates without anybody in the company looking at it. And so we start out with. We had some spreadsheets and literally my very first year, I got asked to speak at the New York State Society for Human Resource Management convention, which I didn't realize was a big deal, but I was literally the only person that they could find that knew anything about turnover. Right. So. And now I worry that we're on this workday end where we're having AI do things and automated reports. One of the things that scares me about automation, and I'm not saying this because I'm an old Luddite, you know, is that if I just push a button and the report comes out, I can't critically evaluate. Mhm. Whether that's correct or not. I don't know what went into It, I don't know how to make it myself. I don't understand the math behind it. I just push a button.

Speaker B: You know, it's very similar, I think, to you said, the, uh, you know, the, the workday challenges. It's all applicant tracking system challenges. Um, I believe it was Korn Ferry who came up with a statistic that said 80% of applicants are rejected without a set of human eyes even looking at them. It's all just based on computers and algorithms. Um, and to some degree, I mean if, if you know, a recent college grad is applying to be CEO of ups, I mean, clearly they're not qualified. I mean, you don't need human eyes to, you know, to make that determination. Um, but when you're lacking that understanding of, of what some of the metrics mean and how they're calculated, um, you know, that's really the same side of the coin. Right. We're producing a lot of data, but we're not always able to interpret it correctly. Um,

Speaker A: yeah, it's absolutely, it's absolutely an issue. And, and, and to be fair, when an, when an applicant tracking system rejects you, it's rejecting you based on the criteria that a human put into it. Um, but today I'm telling you, and I know this for a fact because I teach people how to do it, is people are using AI to create the job descriptions, candidates are using AI to write their resumes, and then AI is rejecting or advancing the candidate. And, and that's scary. Um, and it ends up with us favoring. If I'm hiring someone to do AI work. Yeah. Then they should be good at manipulating ChatGPT or Grok or Gemini or whatever into writing a good resume for them. Great. But if I'm hiring you to do something else, what you're getting judged on is your AI skills.

Speaker B: Mhm.

Speaker A: And, and that's not what, what we should be looking for in a candidate. And you know, that's always the fear with using interviews as well. Interviews are the worst way to hire people, except for all the other ways. Right. Like, and it's, we can do those like skills based. And there are companies that, that create skills testing and that's great and I love it. But I also have been in HR for 26 years and I know that those tests are not carefully calibrated. You can have the company that creates them carefully, carefully, carefully calibrating them. But then miss 22 year old with a bachelor's degree in gender studies who just got this job as a recruiter because a lot of companies think that that's a great entry level. She doesn't know how to match it. And not that she can't learn it, but she doesn't know because she has no experience. And. And so you're like, oh, here's this. And I had, uh, a woman at a conference come up to me and tell me a horror story. I mean, it had a good ending, but she had applied to be, literally, a chief human resources officer, and they sent her tests to take. One of them was a spatial relationship test, like the skills you need to parallel park a car, which, by the way, I would, I would flunk. I, I just, you know, that is

Speaker B: really, that's really important in hr, right? To be able to parallel parking, parallel park. You know, if, you know, if you can't parallel park a car, um, you know, especially in the UK and in the us, left or right side of,

Speaker A: uh, the car, you're right, Failure. But she was taking it home. Her husband's an engineer. She said, hey, come take this for me. And he did. And when she went into the job interview, they said, wow, you got the highest score on that ever. And she got hired, but she's like, that had absolutely nothing to do. Yeah, nothing. Nothing.

Speaker B: Yeah, nothing yet. I also see, um, a tremendous opportunity in hr. Um, I've said before on this podcast, uh, and I've written about it, that HR is sitting on the largest untapped resource in business history, which is in the HRIS data. Our ability to mine that is just. We've just touched the tip of the iceberg. Um, I remember one study I did when I was consulting was, uh, to be able to use machine learning to predict. I mean, this is kind of before ChatGPT was commercially or widely available, but to use machine learning to forecast with scary accuracy the probability that an employee was going to leave in the next six months. Um, and then it allowed a client to make a conscious decision as to whether they wanted to intervene or not. For those with high flight risks, in some cases, you're better off just opening the door and letting them leave. But if it's a high performer, critical talent, hard to hire, you know, a future leader, um, you know, what can you do to entice them to stay? Um, you know, and I think that's just, that's just one example of the massive opportunity with this HR data that I think to your, to your earlier point, that a lot, unfortunately, a lot of HR leaders don't have any of that statistical background. And it's not just a matter of trying to boil the ocean and start analyzing data and see what, you know, see what rises to the top. Because nothing ever will. I mean, you can analyze it for days, unless you've got kind of that training in statistics or social sciences and analytics where you use the data to make, to try to solve a problem. Um, but I think it is untapped.

Speaker A: It is untapped. And I think there's a little bit of fear of tapping into it as well. Um, because when you're looking at it, okay, let's use predictive analytics to figure out who is most likely to succeed and what happens when your predictive analytics predict one race or gender over another. And, um, then you have a decision to make. Like, do, is this because of illegal bias entering into the system, or is it because people in this group, whatever that group is, are better at this job and.

Speaker B: Mhm.

Speaker A: And do we want to open that Pandora's box? I mean, we had Amazon years ago in the teens, I guess, do we call them the teens? Um, using AI to, to do their hiring. And it was so biased against women that any indication that you were female just got you rejected. Now we, we know that women as a whole are not so awful that they should 100 be rejected. Right? 100. Rejection of women is a sign of, of bias. And to Amazon's credit, they stopped the program, waited until the statute of limitations was up on their illegal hiring processes, and then they went public with it. But what I say, um, which is unpleasant, when I go to conferences and I talk to vendors and they're like, oh, our thing is eliminated bias from hiring. And I say, Amazon, which has more money than God, could not do it. How was your startup with $7 million in funding? Mhm. Mhm. And of course the, the salesperson there

Speaker B: has some snappy answer.

Speaker A: No, they have no clue because no one has to send them. No one asked them that. They just say, oh, yeah, well, we use this. And they'll say something like, well, we remove the name of the person off the, um, off the resume. That's a great start because names tell us so much. But before we started recording, we were talking about my name being Suzanne Lucas, and I live in Switzerland, right on the border of France. And Suzanne and Lucas are both French. I am not French. Uh, so people assume that my name is pronounced Susanna Luca. Um, and that's how people always speak to me. And if I say my name first, they're not going to spell it correctly. And like, I'll go to the pharmacy and I'll Say I have a prescription for Lucas L U C A s. And they'll start typing. They're like, I can't find it. And I'm like, l U C A S. Because they hear Lucas and they immediately start typing in L U K A s. You know, it's like that bias thing going on. Just what it is.

Speaker B: So why do we still have, with all this technology, um, if we're not even looking at prescriptive analytics? Um, we're still getting, in many cases, many companies around the world are getting descriptive statistics wrong. Um, globally, women still make 80 cents. 80 years. I guess it sends it for the euro as well.

Speaker A: That is one of those wrong.

Speaker B: That's 80% of what men make globally. Um, it varies between 78 and 82% in literally every country in the world. In Switzerland, in Canada, in the US in the uk, Singapore, Australia, um, we're still not even able to pay women equally and fairly for the work that they do. And that should be.

Speaker A: We do pay women equally and fairly. That figure is a result of bad analytics. That is taking. Here is the average salary that men make, here's the average salary that women make, smashing up against each other and go, ooh, men make more. But when you account for experience, number of hours worked, number of years worked, degrees, all of that, the difference is like 98 or 99. And in some professions, women make more than men. It is looking at bad data I make. This is, this is, uh, I will admit I make less money than I could have. Uh, because when my oldest child was born in 2003, I switched to part time work and I worked part time from 2003 and until 2019 I worked part time. Does that, ah, completely lower my earning capability? Um, yeah, yeah. My ex husband who worked all the way through, he was able to build, um, that I wasn't. Is that because of discrimination against women? No, it was a choice. I wanted to be with my kids. And I said that to him before I agreed to marry him. I'm like, I am not, you know, I'm, I'm not the career woman. I'm gonna stay home with the kids. And I ended up working part time because babies are boring anyway. They're so adorable. But I needed, I needed something else. Um, not to say that women that don't, don't, but those are choices that, that we make. Um, you know, I had for three and a half years construction going on outside my, outside my window, on my street. I never saw a single female construction worker. Not one, not that they Wouldn't have hired them. But women don't want to do that. You know what they want to do? They want to work at the preschool, they want to do daycare. You know what pays more? The construction work. Uh, in today's environment, if a woman walked in and said, I want to do construction, every company would be hiring them because it is good for, you know, they want to put you on your brochure. You know, um, we choose those things. And you see in countries where, like Scandinavia, where salaries are flatter, like, there's not a huge differentiation between doctors and kindergarten teachers. Like, there's. That you have more sex segregation in the professions. In countries like India, where there's large histories of, uh, discrimination against women, you see women's salaries right up there, and women are doing I T and tech and all of that. Because when women are given the choice, you're going to make the same amount as a school teacher as you are as a doctor. They're going to choose school teacher.

Speaker B: Mhm.

Speaker A: That's what they want to do.

Speaker B: You've consulted across the US and now are in Switzerland and throughout Europe. Um, how do cultural differences shape HR challenges and opportunities?

Speaker A: Culture is so critical. And we talk about company culture and cultural fit, and that's. Nobody knows what that means. Um, because we shouldn't hire based on, hey, Tim's gonna be my bestie. We're gonna, you know, revive. Right. And. And people do that. And recent research from Texio shows that's exactly how people are hiring. They're hiring on that. But culture has this tremendous impact on every aspect of our lives. And you don't know. It's like a fish doesn't know what water is because they're always in it. You're always in your culture. And when we are looking at different cultures, just little things. One of the most important things, should you ever have a business meeting here in Switzerland, you have to shake everybody's hand when you come into the room. And you better shake everyone's hand when you go out of the room. Doesn't matter that you've worked together for 10 years. You got to shake those hands or you're rude. I, I mean, when I interviewed for jobs in the US I would shake hands, but, like, if I went to a meeting with my co workers who I saw every day, I wouldn't shake their hand.

Speaker B: Mm.

Speaker A: It's not that the Swiss way is right, the American way is wrong. There's no moral thing over should you shake hands or should you not shake hands? But it's Gonna be the difference between landing that contract and not landing that contract. Um, because they're like, is there something wrong? Um, you know, like, why didn't she shake my hand? And it's just, it's just those, those little tiny, tiny things that can really throw everything off. And you know, for, if I were queen for a day, queen of the universe, I would say everybody needs to live outside their home culture. For everybody. It just. And, and you can have different culture within the United States as well. I mean, I grew up in Utah and I went to graduate school on Long Island. Holy culture shock. Because not only did I grow up in Utah, I grew up in southern Utah where it's warm in a small city. It's now a mid sized city. But when I was there it was a small city where people would retire. So I learned to drive in a small retirement city in Utah. Then I moved to Long Island.

Speaker B: I, it's a full contact sport.

Speaker A: Full contact sport. I was not prepared. No one prepared me for that. I had to change how I drove or I was gonna die. You know, that's just one of those culture things, um, that you don't, you don't think about. And smart companies. Look at, look at that. And there are, are things, oh well, this, these people are lazy. Well, it's a different culture. In Spain you eat dinner at 9 o' clock at night. Is that because they're lazy and can't get around to make. No, it's just that's how they do it, you know. Whereas in, in my home culture in St. George, Utah it's 5pm man, that's when you eat dinner. What are you thinking about? You should be in bed.

Speaker B: So that is a nice segue into my next question. Um, your writing often blends humor with serious HR topics. Um, how can storytelling, um, and I want to talk about improv a little bit later on, but how can storytelling improve communication between HR and employees?

Speaker A: Stories are what we are wired to understand. Um, if you have, if you have little kids, what do they want before bedtime? They want you to read them books. Um, they want that story. We want the beginning, the middle and the end, right? This is what we are wired. This is how society pre written language passed things down. Information is through, is through stories. Um, if you need to memorize something, you know, lists of something, we'll use mnemonic to, to come up with a, you know, my. What is it? My very lovely mother delivers pizza. I can't remember. Anyway, it's just a little tiny story. So That I can remember the planets, which clearly didn't work because I don't remember the planets.

Speaker B: Many, many very early men just set uh, up near I guess Pluto, but that Pluto was the last one.

Speaker A: No, we got to keep Pluto because

Speaker B: I agree, I agree we got to keep Pluto. But we're all about inclusion. We're all about inclusion in hr.

Speaker A: Just because it's small, small and, and

Speaker B: distant and on the outside, you know, I'm distant.

Speaker A: I'm often distant. Anyway, um, it's that beginning, middle and end. And when, when you know, going back to our discussion about analytics, um, if I just throw up a chart. Mhm. With no background, no understanding, it's not going to click in your head. You're going to look at it and you're going to say thanks and then you're going to go to the next one. It's not going to lead you to any action. But if I can put up that same chart, explain what everything means, what the implications are, tell the story behind it. Um, you know, if you're, if you're looking at, you know, going back to my grocery store days, if we saw a store in my analytics that was very, very different from the others, then I would go find out the story, what's going on at this store that makes it different. And if it's a positive difference, then let's take that story, teach that story to this store and this store and this store so that we can all do it. If it's a negative story, then okay, let's figure out what's going wr, then we can fix it. If we just put up the chart, turnover is up in a house, anything. So it's that, that communication, it gives

Speaker B: you the so what, what do you do with it?

Speaker A: And, and one of those things and I'm just going to jump a little bit of improv. I, I teach improv in two ways. One is as ah, leadership and one, I just teach improv. Um, I'm part of an improv team. We perform and I teach improv classes and at the beginning of each class we do what I call an ad info lineup where we establish scenes. And at the beginning of each scene you have to establish who we are to each other, what we're doing, where we're doing it and why we're doing it. And I make them do that in three to four sentences. And then after they do a scene, like a regular scene at the end to evaluate, I'll turn to the class that wasn't doing it and say who were they to each other, what were they doing, why were they doing it, and where were they? And if they can't say all those things, then we know it's not a good scene. And so the same thing with data. If I can't tell you what these numbers are to each other, what it's doing, where it's from, and why we're looking at it, it's not a story, it's not a good. It's not a good thing.

Speaker B: So improv comedy and HR usually don't mix.

Speaker A: Uh, because we are not.

Speaker B: How does your improv background influence your approach to leadership training?

Speaker A: There is this fundamental principle in improv, and anybody listening to this who has ever done any improv knows precisely what I'm going to say. And it is this concept of yes, and this is the beginning, foundational thing of improv. You take an improv class in Switzerland, you take one in Chicago, you take one in Hong Kong, it's going to be the first thing they say is yes. And, and that's where you accept whatever is thrown at you and then you build on it. So if I was doing an improv scene with you and I said, put that gun away, you couldn't then respond, I don't have a gun. What are you talking about? You would immediately say, no, I'm robbing the bank, you know, um, because you're going to accept what I've just said. You have a gun, you're robbing me. This is probably not the best example for hr, but probably not.

Speaker B: Uh, even though I live in Texas.

Speaker A: You live in Texas, but you don't. Uh, or if I said, here, this is, you know, better for hr. Oh, what a lovely pink and purple polka dotted ball gown you're wearing.

Speaker B: How did you know? Suzanne, I know we're doing this on video, but it is just an audio podcast.

Speaker A: Yeah, right. And you then build on it. And within leadership, within HR specifically. HR is very rarely the decision maker. We may write the policy, but the ultimate person that decides if it goes into effect is the CEO. Um, and CEOs will always make dumb changes. Um, sometimes that's wrong, Sometimes they'll make very smart changes. But sometimes we have to do things that we don't personally love. And then our options are to whine and complain about it and ultimately destroy employee morale. Any HR professional that does that needs to be fired. Um, and there are hills to die on. I have my list. Um, I learned some new ones every once in a while. But those hills to die on are. I'm not going to do this. And if you want me to do this, you're going to. You're going to have to terminate me. Like, that's it. We can take that kind of stand. But if it's not a hill to die on so much, though, that I'm willing to quit, then I need to be on board. And, and so I've got to accept my reality. This is the policy, and now I've got to build on it. What's the best way to do it? And one of the things that a lot of HR leaders are afflicted with now is CEOs are drawing this hard line. Return to work. Wall Street Journal just had an article about real hardline CEOs, right. That are like, we don't care about work life balance. And, and guaranteed they will care about work life balance as, as things shift and it becomes an employee market rather than an employer market. But it's an employer market.

Speaker B: Yep. Yep.

Speaker A: Um, and, and there's a lot of HR people that love remote work. So if I'm the HR Chief Human Resources mag. Chief Work Services Officer from, like, JP Morgan, he's one of the people that are like, gotta be back in. I can say, I hate this, you suck. And I can go tell all the employees I think this is dumb, but we have to do it anyway because the boss, whose name I don't know, um, said we have to do it, or I can figure out a way to make return to work work. And that is the key to successful hr. And there are so many things that we have to do that on. Um, the government comes down with things. The Supreme Court makes a ruling that we disagree with. Okay. How are we going to make it work for our employees? What can I do to implement this and be in compliance with the law and still do what it takes to make my company function? What can I do when the CEO says, everybody returned to work and I think it's a bad option? Which actually I don't. I love return to work. Um, that will get me. I love working from home.

Speaker B: I love working from home.

Speaker A: I, I work from home too. But that would be a different discussion. If you want to have that, I'm happy to have it. But if I'm the Chief Human Resources officer for JP Morgan, I've got to get on board or I've got to get out. And there are, and there are other companies that would hire me if I was that, because, you know, that's pretty cool job. There are other companies that would hire me, but what I Can't do is undermine. It's that. Yes. And building upon. And so that's one of the skills that I teach is like, this is how you identify and how you build and how you look for the employee. First we look to finance to understand the money. We need to look to HR to understand the people. And if I can't understand what my people need, then I am not a good HR person.

Speaker B: I think there's probably some other parallels with improv that would apply directly to leadership or leadership training. It's certainly about comedy, um, but it's also about listening, reacting, processing, and speaking on your feet.

Speaker A: Absolutely, absolutely. And one of the skills we teach with listening, um, is how to actually listen. Because in a normal conversation, you. I haven't said very many shocking things. Right. It's. I'm not gonna. You don't ever expect. I'm gonna start singing Billy Joel. Um, please, no, Nobody wants me to do that. Um, I'm gonna stay in this HR realm. You know, the language, you know, that fits pretty expected. And that's how most conversations go in improv. Because anything can happen at any time. It's all unexpected. So you have to learn to listen so well, and you never know what's going to come.

Speaker B: You don't literally.

Speaker A: So I teach those listening skills that are not like that reflective, uh, listening that you've heard about, or maybe if you've been through marriage counseling, you've experienced where the counselor says, suzanne, tell your. Tell your husband what you understand he said, and you say, I understand that what you said is. And you repeat it back, and then you hate each other more. Um, that whole reflective l. Listening. So what you're saying is. It's just. It's icky. Everyone hates it. I don't know why it's a thing. I can teach you how.

Speaker B: Especially that voice.

Speaker A: That's right. That's how much my therapy voice. I could have been a therapist, except, no, I couldn't be a therapist because I'd be like, what. What are you doing? That's a dumb choice. That's why I'm a therapist.

Speaker B: You teach HR pros HR folks.

Speaker A: 90% of what I say is expected. And then there's that 10% when it wasn't Billy Joel.

Speaker B: It wasn't Billy Joel. But I didn't see. I didn't expect therapist, uh, voice either. That was, uh. Um. You teach HR folks how to use ChatGPT and other AI technologies. What's the most powerful way AI can support HR teams? Today I saw a stat from October. So it's a little bit outdated, um, but it came from the SHRM website or uh, I'm sorry, it came from a study that SHRM had done in the US and um, it was kind of shocking. Um, so first of all, McKinsey says that 63%, almost 2/3 of CEOs characterize implementing AI as a higher, very high priority. No surprise there's um. Yet 2/3. This is the SHRM data from October. 2/3 of HR leaders say their teams lack AI understanding and that only same study, only 1% of HR teams have an advanced AI implementation.

Speaker A: Now see that is something that I think is interesting. Um, because I just literally, and I just pulled it up on my computer screen. I, I literally ran a survey um, last week, I'm putting the data together now of HR professionals and this is our sneak preview of uh, this is, I'm presenting this next week in London at a disrupt HR, um, about AI in HR and, and 63.7% of uh, my respondents said that they use AI. The, the commercial AI, you know, ChatGPT, perplexity, whatever. I'm not talking about AI within your applicant tracking system regularly and 25% use it rarely. And that compares to 38 of the general population using it regularly. Uh, 44% of the general population never uses AI at work as compared to 11% of HR that never uses it.

Speaker B: So we're a little more advanced is what you're doing.

Speaker A: We're more advanced. And one of my concerns, and I'm not saying that this is, this is true because I haven't seen the McKinsey study, but I will look it up as soon as, as soon as I'm done is that one of the errors that is often made by people like McKinsey and um, this is, I'm not saying McKinsey did this, I'm saying this was a common error is they speak to the leaders, they speak to the VPs and above who have no freaking clue. Mhm. How people are using it. As I said in the beginning of this, I know people are using it to write their job descriptions. I'm teaching them how to. Right. But they are also not sending an email to the VP of HR saying I just wanted to let you know that I am now using ChatGPT to write our job descriptions. They are just turning out high quality job descriptions in a, in a timely manner. The leadership doesn't necessarily know how the day to day is getting done. So with AI and with those commercially available things, not your custom whatevers, that are being used. It is so good at getting people started. So much of what HR has to do is those tasks, like getting the job descriptions ready to go. Yes, the hiring manager should have a big role in it, but we know that they're not doing that work. We know they're not. And then they're going to put dumb things in there that you have to remove because they're illegal or whatever. And occasionally one of those seeks through. Like there was a couple years ago I saw one where it was for a doctor, a hospitalist position and it said in it, this job is for men only. Women are not successful in this role. It snuck through, right?

Speaker B: Yeah.

Speaker A: Uh, so we're using it to do those tasks. Like one of the things that's going to come up every year is open enrollment. Every HR person hates doing open enrollment. It's a pain in the neck and things change every year. And so you've got to redo your list of frequently asked questions. Well, now I can take last year's frequently asked questions, this year's policy, put them both in the chat GPT and say update.

Speaker B: Mhm.

Speaker A: And in two minutes I will have an updated thing. Now is that going to be perfect? No.

Speaker B: No.

Speaker A: Do I need to read it and make sure it's accurate?

Speaker B: Absolutely not. AI doesn't make mistakes, Susan.

Speaker A: Nobody listen to him. Yeah, it's gonna be.

Speaker B: No, don't listen to me, don't listen to me.

Speaker A: But that is so much faster. Editing is so much faster than writing from scratch. You know, those types of things, those, those beginnings. It just gets you to that next level. And that is something that AI is really, really helpful. And I think because we have so much of that work within hr, that's why we're using it at a higher, higher rate than other people.

Speaker B: And that just, I think that's, I, that's fascinating. I'd love to, when you release your, your study, I'd love to um, see it. Maybe we bring you back for, for another discussion and ah, and sharing of those results.

Speaker A: I will make one caution about my results because I do know how to do statistics. This was not a random sample.

Speaker B: Okay.

Speaker A: It was voluntary based on um. I put it on my website, I put it in my Facebook group, I put it on LinkedIn. So is it a randomized sample? No. Is it statistically valid? No. Is it interesting? You bet it is.

Speaker B: You bet. Yeah. Um, you know, I, I did and often do um, AI training in, in the United States here as well. And I spoke to the, I gave a Day long training session to HR Houston, the Houston chapter of shrm.

Speaker A: Oh, amazing.

Speaker B: And I was surprised and there was a lot of younger folks in the audience, um, you know, for this session, who had literally never touched chatgpt before. They were intimidated by it, they were afraid of it. Um, and I know there's a little bit of a fear in, in AI replacing people. And you know, there can be some reluctance there. But, um, at the end of it, at the end of the session, being able to do things like you suggest, uh, you know, starting with a policy manual or updating, um, job descriptions, I mean, it is such an aid for making our lives easier. Um, you know, it's, it's almost, you know, it's even more so than, you know, going back to the old days of typewriters instead of word. Right. I mean, it's, you know, it's, it's, it's the same thing, but even more so.

Speaker A: Ah, absolutely. And using those things and learning those new tools and as long as we use them as tools, that's great. I do have that fear though.

Speaker B: Push the button and spit it out.

Speaker A: If you don't understand it, if you don't understand what's coming out. I mean, this is, uh, we, we keep seeing this and it makes me laugh every time because I'm a horrible person, um, that Lawyers are using ChatGPT to write their briefs and the judges are busting them. And it's like you guys, the, the, the judge knows that you guys are idiots, so he's going to have his clerk check every one of your references. So you need to check every one of your references. And, and yesterday, yesterday two days ago, I was using ChatGPT to write a bio of one of my upcoming speakers who incidentally is, is, um, is going to be speaking about AI. Um, and so I was like, well, this will be fun. Then I'll say I wrote Keith's bio by putting in his, his LinkedIn profile. So I put his LinkedIn profile into ChatGPT and it wrote this beautiful bio that was completely fake. And I was. And, and I said, did you even read. Oh, sorry. You know, it's like Keith spent 10 years at Sherm. I'm like, Keith never, never worked for Sherm. Like, where did you get that? So it's, you know, but if, if I hadn't checked it, it looked great and I had given it the source material. I had given it the source material and, and it had done it. So I'm, I am going to still use that when I'm my promotional materials, but it's going to be, you know, talking about, look, this is the cautions that we need to do. Um, you know, it looks, it looks great, but it looks great.

Speaker B: There's a Google recently, in the last year kind of made a switch where when you do a search, it often is an AI generated answer to whatever you're looking for. Uh, you know, as a first response. Right. And when they released this a year ago, there was, it was plagued with errors.

Speaker A: Right.

Speaker B: Um, you know, and some of them are, you know, quite funny. And if anyone, you know, is skeptical about the mistakes that AI can make, um, one of the interesting ones is if you asked Google a year ago for the health benefits of nose picking, they got a very interesting answer. Saying, saying that eating mucus may help prevent cavities, stomach ulcers and infections and it may also boost the immune system. Right. So AI is clearly very smart.

Speaker A: Um, but, you know, how healthy are toddlers? Right.

Speaker B: Well that is true. They had another one that was, um, how do you prevent, uh, cheese from sliding off your pizza? And response was an eighth of a cup of white glue, um, will usually do the trick. Which is factually correct. Right. If you glue the cheese onto your pizza, you know, it will, that cheese isn't going to slide, it will stay.

Speaker A: That's a really good point. Yeah, Yeah. I mean that's, they're all, are those things, but if you don't recognize it. One of the things that I emphasize is that the people who should be using ChatGPT are the experts in their field. Mhm. It's not something for the industry.

Speaker B: You can tell. Yeah. So you can tell when something.

Speaker A: Right. So if I'm right or wrong, if I'm writing an article and I'm like, um, oh, I want to put in what the qualifications are to be eligible for the Family Medical Leave Act. I can go to ChatGPT and say, what are the qualifications to Be Eligible for Family Medical Leave Act? You know, no more than one paragraph and then I can read it, I know whether it's accurate or not. I can copy and paste. I, I don't actually do that. I just type out the Qualifications for Family Medical Leave Act. It's in my blood. Um, but an intern wouldn't, wouldn't know thoroughly. And, and then of course you also have, you know, case law changes things, um, on a daily basis. And ChatGPT doesn't know that because the way large language models work is that it's based on the stuff that's been fed into It. So unless you tell it to search the web, if it doesn't think it needs to search the web, it won't. And it won't give you the most

Speaker B: up to date information you've written. We've talked a lot about your writing. You've written for cbs, Money Watch Inc, and more. What HR trends or leadership blind spots do you think are under reported?

Speaker A: You know, uh, there's so many things that are underreported and one of the things that drives me insane as, uh, somebody that, that writes in this area is that if I write something dumb but catchy, you know, then it'll take off like wildfire. If I put really important information that you need to know that is not sexy, catchy, whatever, nobody sees it and LinkedIn suppresses it. LinkedIn, uh, the people that control LinkedIn, they have things that they don't like. And if you happen to write on one of those subjects, no one will see it. Literally no one. Um, and so there's a lot of things that we don't talk about and there's a lot of things that aren't, are too scary to talk about. Like when we talked about the data, right? Um, somebody should be doing those studies and using those predictive models. But like I'm telling you, we don't want the answers because what if it comes out of something that we don't want to know? And then if you, if you report on that, then you're branded, uh, a racist, sexist, whatever is, it's, it's the data, right? How dare you even ask that question? If men are at this job than women or women are better at that job than men, like, we can't, we can't study that because it would just destroy your career to do so. Um, we don't look at that, we don't look at the little things. We do look at the sensational stuff. And I'm guilty of this because I like to get paid, and I do honesty, I do, I like to get paid. So everything I write is going to be accurate. But what I'm going to select to write about, ideally are things that you're going to click on, um, and want to read. So those boring things, the compliance stuff, which I do talk about a great deal and I try to make it exciting and use examples and all of that, and then sometimes that backfires. Um, this week I published an article about the shift in the Social Contract. The way this is boring, right? And, um, this is my political science coming back with the years of philosophers, uh, with locks and hobbes and um, and how we're having the shift in what a boss is, what an employee is and what, who can stand up to it. And when I shared it on social media, I used the example of Starbucks employees striking because of their new uniform that caught like fire. Everybody had an opinion, most of them. But I suck, um, because I didn't understand Starbucks and I'm like, did you read the article? No, of course I didn't read the article. Um, it, they, they didn't, they didn't go beyond that surface. And one of my all time favorite April Fool's jokes I, uh, believe was done. I should know because I'm saying it's all time favorite is my all time favorite. I believe it was done by npr, um, where they put a Facebook post where they said, you know, people aren't reading anymore and then if you clicked on would say April Fools. Shh, don't say anything in the comments. The comments were full of people just like real. This is wrong. This is of course we're reading. And anybody that clicked on it just peeing themselves laughing because mhm, they didn't click right. And we do that. So yeah, I use the hot topic of Starbucks to get people to read. It didn't even work. I mean they argued about it, but they didn't read.

Speaker B: You've had a strong voice in SHRM and disrupt HR circles.

Speaker A: Yeah.

Speaker B: Uh, what's one you're speaking, uh, next week in London. Uh, what's one belief about HR leadership that you think needs to be disrupted?

Speaker A: Oh boy, that's a tough question. Um, I'm going to say I would love to see more operations people moving into HR roles. Um, one of the things going back to my first big girl job for Wegmans and if you, if you look, Wegmans is always in the top 10, if not the top, um, company to work for and Fortune's top companies to work for. This has been for M for as long as I've worked for them before too. So like it was 25 years ago the I started working for them 26 years ago that I started working for them. So they've been there for at least 30 years in that top 10. Right. One of the things that they do, at least they did when I worked there. I don't know if they still do, is that in order to be a director level at any job, any job, accounting, finance, HR warehouse, whatever, you had to go into the store and be trained and work as a store manager. And because of that you don't have any dumb policies you're, you're never gonna have. When, When I was in college, I worked at Kmart, which is a company that doesn't exist anymore. One of the rules at Kmart, I was a cashier, that we had to wear dress shoes, we had to wear hard bottom soled shoes shoes. I was a cashier, I stood behind a cash register. No one saw my feet.

Speaker B: Nobody saw your feet. Mhm.

Speaker A: No one at Wegmans is ever going to make that rule. Because anybody who has the rulemaking ability has worked 40 hours, 60 hours a week on the floor of a grocery store. They're never going to say you have to wear hard sold shoes. Like they're never going to.

Speaker B: So important, so important to have that experience of what day to day customer facing employees see every single day.

Speaker A: Yeah, yeah, it's absolutely important. And one of those things, you always hear the stories of the people that complain and the manager comes in overrides, which um, makes employees hate their managers and it encourages bad behavior of employees. You need more frontline experience. Um, and that isn't to say that HR isn't a specialized field. It is, it requires a lot of knowledge. But I would like to see more rotational programs. Dump your HR people into operations roles, send your ops people into shadow recruiters. Mhm. You know, let's see how this goes. Um, because when we don't have that experience, when we don't have that understanding, that core understanding of the business, you end up with the. You have to wear hard sold shoes. Mhm. Because somebody in Kmart HR said we want our employees to look nice. Mhm. No one saw my shoes. And even if I had been a floor employee, no one would have said I'm not buying at Kmart because that girl in women's was wearing sneakers. Was wearing sneakers. No one's gonna do that.

Speaker B: So looking ahead, what advice would you give HR leaders to stay competitive? Resilient, whatever. Resilient. I guess in time of change, we're seeing massive change globally, socially, technologically. How do you adapt to that?

Speaker A: One of the biggest mistakes that I see HR leaders doing is assuming that they are right about everything and that people agree with them on everything. And we are in a time of massive social change, political change, um, political upheaval. And I see every day, every day on LinkedIn I will see HR professionals talking about their political beliefs and how the people that disagree with them are evil and stupid and, and all sorts of other bad things. I'm going to tell you a secret. 50% at minimum. At minimum. 50% of your employees disagree with you. At minimum. You want to be an HR leader. You want to conduct an investigation. Well, I've seen your post saying that you think I am a racist. Snowflake. Whatever it is, it doesn't matter which side of the thing. I've seen your posts that have said you think I am not worthy of respect. Well, you know what? You're not worthy of respect. I'm not going to be honest with you. I'm not going to take you my problems. I'm not going to go and allow you to fix the issue. I'm just going to sue you and I'm going to win. Right, um, setting those things up. We're in this time of change. If HR leaders want to lead, they need to consider that people that disagree with them have good reasons for doing so. Way back in the, in the dark ages, I did, you know, debate. Um, and when I did debate in school, you didn't know, you knew what the topic was, but you didn't know what side you were arguing until you stood up and then they would say, team A is, you know, pro and team B is con. That was, that was all. And I've made the suggestions many times. I'm like, if you cannot articulate why people believe different than you are, then you don't understand it. And I have been told I am racist for doing that. I'm like, mhm, I don't need to agree with it, but I need to be able to articulate it. And if you cannot articulate it, if you as an HR leader cannot understand where the CEO is coming from when he says return to work, you're not a good HR leader. You can disagree, but you need to be able to understand the CEO's thought process. And if you can't do that, you are. You suck.

Speaker B: Suzanne, this has been a wonderful discussion. If any of our listeners want to get in touch with you, um, follow you on social media, learn about improv, um, maybe get some counseling advice.

Speaker A: But then I'll go into my, my therapist voice.

Speaker B: What's the best way to do so?

Speaker A: I'm really easy to find. If you Google evil HR lady, I will pop up. Um, but my website is evilhrlady.org and you can find me on LinkedIn. Please feel free to connect with me on LinkedIn. Um, happy to connect with you. You can email me at ah, evilhrladymail ah.com. um, and if you're in need of a webinar, you can check out my HR training company, which is called HR. HR learns@hrlearns.com wonderful social media.

Speaker B: Um, are you on.

Speaker A: So I, I am on X at, uh, Real Evil HR lady. But I, I follow me on X. It's. I mean, that is what it is. Um, but I have a Facebook group called improve your HR and we've got 34,000 HR professionals in there. So if you want to join, you're welcome to. If you're an HR or HR adjacent profession. So if you're an HR or payroll or employment law, um, something like that, you're welcome to join. Um, as said, follow me on LinkedIn. I'm Suzanne Lucas, um, and the one in Basel, Switzerland. I am not the midwife. Suzanne Lucas, do not contact me for the delivery of your child. I would love to see your baby after it's all cleaned up, but that whole. No, I'm not that person.

Speaker B: Suzanne, thank you so much for joining me on the State of Work Today podcast. Um, we talked about improv, uh, and humor. Uh, we talked about your insights on global HR and culture, the rise of AI in HR analytics, and I think, really how to humanize leadership, uh, in today's workplace. So thank you so much for joining me on the State of Work Today podcast.

Speaker A: Well, thank you for having me. And I hope that my random thoughts, uh, weren't too much.

Speaker B: This was fantastic. Thank you so much. So I'm Tim Glow up, your host of the State of Work Today podcast. Thank you so much for listening and join us next week for another great episode. Thanks, everyone.