“Organizational justice is about ensuring that every individual feels they are treated fairly and with respect in all aspects of their work. It’s not just about the outcomes they receive, but how those outcomes are decided and communicated. Fair processes and respectful treatment are fundamental to maintaining trust and equity within any organization.”
-Stephen Gilliland
Summary:
In this episode of “Psych Tech @ Work,” Steven Gilliland, a distinguished professor and expert in organizational justice, joins me to explore the profound impact of fairness on hiring and the psychology of the workplace.
Stephen was my professor when I was in grad school at LSU, so I know him well and was lucky to have exposure to organizational justice theory during my most formative years. After taking a stroll down memory lane, we have an amazing conversation about the fundamental principles of organizational justice theory. We discuss how perceptions of fairness in outcomes, processes, and interpersonal treatment shape employees’ attitudes and behaviors.
We talk about how organizations can ensure fair treatment during hiring and how these practices influence applicants’ decisions and organizational reputation.
We also dig into the broader implications of fairness in the workplace, emphasizing how companies can navigate challenging decisions, like layoffs, while maintaining their commitment to justice.
Finally, we discuss the evolving role of technology in shaping justice perceptions in the workplace. Stephen provides insights into how AI and digital tools are transforming the landscape of organizational justice, offering both opportunities and challenges.
Take Aways:
- Treat Applicants as Customers: Consider the hiring process from the applicant’s perspective. Fair treatment during this phase can significantly impact their decision to join your organization and their perception of your brand.
- Understand the Role of Fairness in Employee Engagement: Perceptions of fairness in hiring and workplace practices contribute to overall employee engagement and satisfaction. Ensure that decisions and processes are consistently fair to foster a positive work environment.
- Adapt Organizational Justice to Technological Changes: As workplaces evolve with technological advancements, continuously revisit and adapt your organizational justice practices to address new challenges and maintain fairness.
- Respond to Difficult Situations with Empathy: During tough times, such as layoffs, how you handle the situation reveals your organization’s commitment to fairness. Strive to treat affected individuals with empathy and respect, maintaining open and honest communication.
- Align Actions with Psychological Contracts: Be aware of the unspoken agreements between employees and employers. Violating these expectations can lead to perceptions of unfairness and affect employee loyalty and engagement.
- Future-Proof Your Fairness Practices: Stay ahead of emerging trends by integrating fairness into your organizational strategy. Anticipate the impact of new technologies and societal changes on your justice practices to create a resilient and equitable workplace.
Take it or Leave it Show
On this week’s show we vote on these articles. Tune in to hear our takes!
“ChatGPT and the Rise of AI-Driven Conspiracy Theories” (Source: USA Today)
- Summary: This article explores how advanced AI technologies, like ChatGPT, are fueling the spread of conspiracy theories. It discusses the potential for AI to amplify misinformation and the challenges in managing these effects. The article suggests that as AI becomes more integrated into everyday life, there is an urgent need for radical transparency and robust measures to combat the spread of false information.
“AI Hiring Tools May Be Filtering Out the Best Job Applicants” (Source: CNBC)
- Summary: This article addresses concerns that AI-driven hiring tools may unintentionally filter out qualified candidates due to biases in the algorithms or lack of transparency in decision-making processes. It highlights the growing reliance on AI for managing large volumes of applications and the need for regulations to ensure fairness and accuracy in these systems.
Full transcript:
Charles: So welcome, Steven. It’s really great to talk to you. I think it’s probably been before we did the little pre call. I’ll get thirty years maybe? I don’t know.
Man, it seems like so long ago. Right?
Steven: Absolutely. It I think it has been, like, early early nineties, early to mid nineties or something like that. That’s a that’s a while ago.
Charles: Yeah. So and for for people who don’t know, Steven was a newly minted professor at LSU and IO when I was there during grad school, and I had the pleasure of being able to have him as a professor. Learned a lot. Learned a lot. This the particular topic we’re gonna focus on today around organizational justice and and how that impacts all kinds of things.
Is something that you were just kinda rolling out at that time.
Steven: Yeah. I was just getting started, looking at it, and really kind of at that time focusing on the organizational justice in the in the hiring process and the applicants. And kinda over the the last thirty years, I’ve just expanded to look at all sorts of injustices and ways that we can create greater justice and organization. So it’s it’s it’s been a consuming interested, had it seeds really planted in Alethia?
Charles: Yeah. Well, you know, that’s important work because the the injustices tend to abound, honestly. Right? And And we we’ll talk about the AI aspect of that, but that’s that’s absolutely, you know, something that’s gonna continue to get sticky. So And I think it’s a really enduring, you know, idea and concept.
I mean, it’s something that you’ve I see it mentioned all the time, you know, by by folks that may not be in our world. So that tells me it’s got intuitive appeal and and it’s very kinda logically makes sense to people. And we’re looking to explain things. It’s good to have some some theory, some research behind that. So I look forward to talking tea about that.
But before we even get into that, I wanna put you on the spot, you know. Thirty years ago was a long time ago. You might have had a privacy effect because it was your first real group of students, maybe when you were student teaching or something. But what was I like as a student. What do you remember about me?
Steven: Wow. We’re gonna deep dive right off the bat Charles and Yeah. What I remember about you. Yeah. You were in there with a group of students that yeah.
I’m I’m yeah. I I remember, finally, the the this classes we would have, the seminars we have, But but Charles, what really stood up to me? Is you or a student who was interested in the practical and the applying this stuff? What does this mean for the real world? You know, there are others in the class member, you know, Mark Nagy, who ended up, like, the Zinc University.
Yeah. Best of there. More more interested in kind of the theories and stuff and but but you wanted to as interested in the practical applications in it. You know, how does this really work? That and that that’s struck me.
Got it. This is a guy who he’s not gonna end up in academia. He’s gonna end up doing something like this stuff.
Charles: Cool. That’s awesome. Well, I guess that makes that that makes you very much a profit, you know. And, yeah, I I didn’t really see it any other way, but boy, the only way to get that foundation is, you know, to to be there. I remember a couple things about you.
So the first thing I remember is I went to some kind of a little get together. I house. I think really early in the first year you were there, but your neighbor made probably the best jumble I I ever had in my life. And he gave me some tips about it, like put it in the oven at the end, kind of bake off some of the extra liquid, which I still use today, not that I’m making that stuff a whole lot. But I don’t know why, but you know, I’ll never forget that particular time that I ate that that I ate that.
It was burned in my in my brain. And I think that you probably showed up in my second year or maybe my third. And then I remember the Woody Woodpecker thing, which, you know, I are you are you still are you still guys still into that? Is that still happening?
Steven: Sadly, no. So my wife was a was a huge Woody Woodpecker collection. At the time, we had an entire room in our house devoted to Woody Woodpecker collection. Oh, yeah. And at that time, she had the second largest woody woodpeaker collection in the world behind Walter Lance who who invented woody.
Yeah. Yeah. Stadly, as as we developed a family and had to got a son and daughter, we had to force to make a choice between giving our kids bedrooms versus woody woodpecker. And and woody woodpecker ends up losing out. So so that so, like, we took them as to about two shelves in a in in a room now.
Charles: Do you still have Walter Lance’s phone? I think that’s the only thing I remember where you’re like, we had the phone that he used, and I think it was a woody woodpeaker phone wasn’t it?
Steven: We still have the woody woodpeaker phone, and and and we still have a hand to sign note that Walter Lance wrote to Cindy he wrote Walter Lance at one point and and sent him a picture of her collection, and he wrote back he actually, at the time, he sent to his assistant this is a woman who’s just as crazy as you or look at all the stuff she’s collected. But he wrote a nice note back to her and and hand drew a woody wood background. So that’s brain behavior how we
Charles: Oh, very cool. So how does she feel? What’s the collective thought about the the CGI? I was just set up beach trip with a bunch of kids and they repeatedly watched the two, you know, I think there’s only two movies where it’s people, but then they got CGI, Woody Woodpecker running around. How did that go over?
Steven: You know, I I’m there’s there’s an embracing of the new, but but there’s there’s also a little bit that old person syndrome of of, you know, the kids don’t know these days, just the the the good old stuff that we used to have. Yeah. Yeah. Yeah. Something about that.
The old the animation quality wasn’t as good. The the the humor’s outdated. But but it’s still what we grew up with.
Charles: Oh, yeah. Absolutely. For me, I’m just glad that it allowed me an opportunity to teach my son about what do you went back here? Because he wouldn’t have known, otherwise. Not like he’s gonna discover that.
So then we watch some of the cartoons and stuff. So that that’s always that’s always good. Right? And and I remember that a lot because I was collecting, like, toys and memorabilia and stuff at the time. So there was there was some sympatico you know, there.
Well but to the serious stuff, I reckon, tell me a little bit about the like, how did you get started with the ideas behind these these principles, was it obviously, you’re in grad school, but but how did that kinda come together for you? And allow you to decide, hey, this is this is important stuff.
Steven: Yeah. Interesting story, Charles. But it was in grad school, and I was actually doing consulting project with my adviser, Neil Schmidt. For for the motors, and we were developing a a new selection system for their administrative employees. And in one of our update presentations, I remember the VP of HR coming to me after, you know, the update and said, you know, Steven, regardless of whether we hire these people, we still want them to buy forwards.
Yeah. And it was like this crystallizing moment in my brain. It was just like, yeah, we look at selection from the perspective of can we build a better mouse track? Can can we predict that or who’s gonna be a good person, you know, a a good employee? But what he was saying to me is, what are we doing to them in the process?
Are we teaching them connected to Ford. Are we turning them off of Ford in that process? And that just blew my mind because that was a whole other side of selection that we haven’t been looking at. And and I just we’ve gotta look at this. We’ve gotta look at applicants’ customers.
Yeah. I just got hold on this.
Charles: And again, that’s kind of clairvoyant in terms of now. I mean, who could have imagined the technology that’s available now for people to to be able to complain or share good or bad things. It’s it’s magnified a million times over. I have a Ford story. I tell a lot of stories.
I think that’s, you know, that’s just part of the whole deal here. Why not entertain? While we’re doing this, although I don’t know how entertaining it’ll be. I I applied for an internship at Ford. Right?
And I’m really into cars. That’s a big thing for me. So I was like, wow. If you so cool to be able to work here. It was the most rigorous thing I’ve ever gone through for any job that I’ve ever gotten.
We went there for a full day assessment center We had a statistical interview. I remember being grilled about different types of factor analysis rotations, and we had to They they put us in a room and they gave us a stack of output and they set a hostile confederate in who’s a plant manager to start complaining about you know, problems and we’re supposed to use these numbers to convince him of something. I thought that was really cool. And I didn’t get the job, but they gave us feedback. They were like, here’s what you did well and not well.
And I blew it because this is why I blew it. Situational interview. They asked me a question about a situation. You know, tell me about a time x y or z. I have no work experience.
I didn’t know how to answer the question. I was like, oh, that’s never happened to me. Let’s move on to it. Like, now you you gotta say something. So I guess they they were saying I needed to make something up.
So that’s the that’s the moment. I had the moment of you gotta bullshit sometimes. To be able to make it in this world.
Steven: Yeah. You know, great great story, Charles. My first interview like that was when I was in college, I was in field for job painting houses, and then gave me a sit somewhat situational interview Like, you you you left the paints. Everything’s all cleaned up. The next day you get there and there’s stain the paint, stain on the carpet.
You know that you didn’t do it. And the customer’s complaining to you about it. What do you do? And and I, you know, I guess now I know the the right answer is that customers always right. But I was just like, It wasn’t me.
No.
Charles: I’m I’m dead. You’re right.
Steven: I I didn’t get that job either.
Charles: Yeah. And, you know, I think in both situations that I haven’t bought up for, but it’s not because of that experience. You know, I I left with a pretty a pretty good feeling about the whole thing. So, yeah, signals. Signal in theory.
Right? I mean, is that the first place you went on your pursuit now of, okay, how can we how can we actually make some kind of organized rationale for, like, what happens and why and what the outcomes are. Right? Where where did you start that part of it?
Steven: Yeah. So then there were the two two sides of it that I really wanted to look at. One was what is it that people react? And what drives people reactions? And and it is things like, you know, by bias in the process.
It is things about daily get the job. You know, just that that’s is things about what am I told in the process? How was I treated? How long did they they take to give me an answer? Or did they ever give me an answer?
Yep. All those different aspects of that hiring process. And and so a a big chunk of my early research was was trying to study one of those different elements that drive our reactions. Drive me to say, wow, that was amazing. Or, wow, I hated that.
I I’m never gonna do that with this one. Yep. The other half of it was what do we do when we have those reactions? Right. Because I had this theory back then that our first encounter with an organization helps us former heuristic or you have some sort of impression.
It’s gonna be lasting. And there’s a lot of research in social psychology suggesting that our early impressions are our lasting impressions. So I thought that if I am turned off of this company and I still end up taking a job with them, that experience in my hiring process is going to influence me as a worker in that company.
Charles: Absolutely. It does.
Steven: And the answer is no. Really? It doesn’t. And after this about fifteen years of research, I I ended up concluding, I think I was wrong in that initial thing. It influences me as an applicant, and it influences what I tell other people, and it influences am I gonna accept that job?
All that thing is an applicant, it influences me. But it turns out once I’m hired, it’s almost like there’s a reset. And it’s like that was the hiring process, but now I’m I’m part of Yeah. It’s h r. You mean ring on Right.
Right. And and so that was it was kind of a disappointing. You know, when you when you get something wrong, you know. So Yeah. That that feeling of, okay, have I been spending my time going in the wrong direction?
And I even wrote a few papers about that, but Now I kind of conclude, no, these applicants reactions are really important. Just not maybe as important as I thought once we’re hired. But they’re important in a lot of other ways in terms of what I tell people in terms of oh, do I accept the job? You know, most importantly? Yeah.
Yeah. Yeah. Yeah. If if I’m a good applicant, I’m gonna have choices. And and so we gotta make sure that we’re presenting our best for, you know, when we’re hiring people.
Charles: Yeah. For sure. That’s interesting because I it is counterintuitive to me. I think there’s a few slides I probably have to go back and change. And probably because I don’t get enough time to dig into research.
But one thing that I realized I just kind of made a little mistake here is we’re starting to talk about all this stuff, but maybe there’s some listeners, viewers that don’t really I can’t assume that everybody knows what we’re talking about. So how about a quick refresher or overview of the ideas behind, you know, organizational justice theory? And I know there’s a lot of flavors of it and etcetera, but I’m sure you’ve done this a lot. But take a few minutes to explain, you know, what we’re talking about here. Before we dig into it in in some other ways.
Steven: Yeah. Absolutely, Josh. So big picture organizational justice is is the perceived fairness of what we experience at work. So it it fundamentally is a perception. And and it’s my perception and my perception might change, you know, vary from yours.
And that’s fine. And and so the first thing to recognize with organizational justice is we’re not talking about the system and how fair the system is. We’re talking about how Fair Steven perceives the system to be. How Fair enough. Uh-huh.
Now it turns out that that perception of how fair is is my boss or health care is my organization. That’s driven by really three fundamental factors. One is What did I get? Did I get my fair share? Yeah.
Number two is when you decided what I got, did you use a fair process for deciding? Did I get a you know, were you consistent? Were you biased?
Charles: Procedural? Right? It sounds procedural on you.
Steven: And then the three is how did you implement that decision? Did you offer me an explanation? Did you treat me with respect and so on? Those three and that’s, you know, the interaction, the entry, the implementation. Right.
Those three end up forming our overall perceptions of what well, how fair was it? So just a quick example here, and this is a student of mine, was laid off in the tech sector last year when Mhmm. Yeah. A bunch of the these old and two which one. She found out she was laid off because her email no longer worked for the company.
She could no longer log in to her email. And then she did some search online and she read a newspaper headline that her company had just laid off ten thousand employees. Yeah. That was that was how she learned about it. So now think about that from an unfairness perspective.
She lost her job, which feels unfair to be. Sure. She had no idea why they chose her So the perceived Right. Of the fact that And then she got no explanation. She didn’t even get a a phone call or something.
Number three, the interaction feels unfair. There’s somebody who’s really pissed off in that. Right? I don’t Yeah. Do me upset with my company and and is going to now share the experience with other people, the the bad experience in that case?
Yeah.
Charles: Well, just from a humanistic standpoint, that’s not very nice, you know. There’s reasons. I mean, it made me think of the time I I got laid off one time. Well, it made me think of of three three things that I feel personally everybody should have to do or have happened to them once in their life. One is you gotta spend the night in jail I could check that one off.
Two is you gotta work in the service industry, serving other people somehow. And And three is you gotta get laid off or fired from a job. These are all, like, important life experiences. For me, I got I was at monster dot com in in Silicon Valley there while I was in San Francisco, but I was doing like sales consulting in Silicon Valley. Nine eleven happens, you know, and I wouldn’t sell it anything because I’m always buying anything, and I was the new guy.
So all of sudden, somebody never comes in my office, came in, sat in my office, they closed the door, and then, yeah, they that the boss lady from somewhere else told me. They gave me a cardboard box. They walked me out. But at least I knew why. I forgot to give a prospect a digital CD with you know, that was a bullshit reason, but at least they gave me a reason.
It kinda hurts. Right? But I can imagine if if, like, that happens But there’s on the other side of that, there’s a lot of companies that offer transition assistance and, you know, all kind of really good stuff. And I wonder you know, that’s gotta speak to something deeper in the ethos of the company or or something. Right?
Steven: I I think I think so. And and part of what I’ve become convinced of is is you really tell what a company is made of when they go through hard times like that. Yeah. You know, it’s easy to give lots of goodies and treat people amazingly when you’re making money. Yeah.
It’s need to be a good employee and a a fair employer at those clients. Yeah. But, you know, when you have to do something hard, like, lay people off or terminate, you know, you what whatever after Spirit, demote somebody or you know, any of those hard decisions, how do you do it then? And that’s it’s become my litmus test of Yeah. Yeah.
What is your company in the core?
Charles: Yeah. Yeah. So when you apply those things to hiring, but they really apply to anything. Right? And that’s where you get into psychology of the workplace.
Right? I mean, we’re people. We’re in an environment. We can’t help. Like, we’re why psychology is our wiring, like, how we perceive things.
We have individual differences, which are, you know, what keeps us going. And, right, not everybody is the same. It makes it fascinating.
Steven: Very Charles, one of one of the latest ones that they did advise too. Beyond you’ll buy on hiring and and terms the one that does come up since the pandemic is where I work. Yeah. Yep. Absolutely.
Do I get the flexibility to work from home or do I have to come in? And and that has become an unfairness, you know, type of thing as well. Why am I being treated differently. Why am I the one who has to come in when this person can show up whenever they want? That’s become a new source of unfairness for people in work.
Yeah.
Charles: Or, hey, I was hired for curing the pandemic to work remotely. And now they’re saying, I gotta come in two days a week, but the office is in Poria and I’m in Maine. You know, like, that doesn’t make any sense. Right? So there’s I’ve heard people actually say that.
Like, you know, I had to lead the job because they they said you had to be there two days a week or whatnot. I think that the, like, the it’s hard to get that toothpaste back in the tube once you get people the the opportunity to work from home, but It is great having, you know, having coworkers that you can be in the same room as and stuff. I will say, I’ve missed that a lot, you know, being being more of a of a single or small company guy most of my most of my time. Well, you know, in the psychology of the workplace then, right, we’ve got we’ve got these things that people are perceiving, what a organization, which is an entity, is doing. Talk a little bit about one one of my favorite.
There’s a few enduring concepts that, you know, kind of guide me and everything I think about. And one is that psychological contract. Right? So so this stuff has gotta be foundational. Talk a little bit about, you know, how the let our let our listeners and viewers know a little bit about what the psychological contract is and and how does the the things that you’re working with here, you know, have an impact on that?
Steven: Yes. So the the idea that psychological contract is it’s that that feeling or that perception that we have got to deal with the organization. And this doesn’t have to be a spelled out deal. This is not something that, you know, has been written down and and and and we signed or anything. Right.
This is just that feeling of maybe x for you and and I can expect why in return. I can expect certain things in return for me being a good employee. That’s the basis of our psychological contract. When that gets violated, that’s where this sense of unfairness comes about. You know, did they Yeah.
I I was supposed to be treated with respect. I was supposed to at least get a phone call when you’re laying me off.
Charles: Yeah.
Steven: You know, now you’ve violated that that sense of psychological contract. And we get these psychological contracts around a whole bunch of things that sometimes as a boss, as an employer, we don’t even understand their employees have that sense of psychological content. But maybe it’s because of they’ve experienced that same sort of war. Maybe it’s because I was hired during the pandemic that my sense of psychological contract is that I should be able to work from home whenever I want. Yeah.
Now you you have to come in two days a week. Don’t violating that contract for me.
Charles: Yeah. I’ve often thought about it like this not to be overly simplistic and certainly not scientific, but if you just keep rising to the highest level of this to me, it’s it’s the golden rule. Can’t you just think about how treating someone like you’d wanna be treated? Would you wanna get laid off and have no? You know, would you wanna be told that you you could be a remote worker?
And then not, I mean, it’s it’s pretty simple in that sense. It’s not as easy, I guess, for a lot of people. And that that’s where I think you also have you know, there’s so many facets of this. Your boss, your individual boss, I mean, you know, one of the things, again, these are these things you hear? Do I have the research to back it up in my head?
No. You know, the number one reason people leave their job is because they don’t like their boss. You know? Yes. Yeah.
Steven: It was an interesting story, Charles. So with that with regard to that that golden rule aspect of Jerry Greenberg late Jerry Greenberg who did a lot of the foundational work and organizational justice and got this field going. I remember talking to him for a long time. And and he said, if you boil it right down, he said at one point, his mom said to him, Jerry, you spent your whole life studying this. And is it isn’t it doesn’t it come out to just be nice.
Charles: Yeah. Exactly. Right? But it’s it’s hard for people to do that. And then corporations, you know, there’s this there’s in some sense, there’s a there’s a wall or a disconnect between the business of the corporation and the individuals who were there sometimes making that happen.
Right? So so they’re you hope that doesn’t happen. And there’s so much variation in in corporations and how they handle these things. The ones that do it really well get a lot press about it. Right?
I mean, they get they get recognized and people wanna work there. It seems so simple even if you’re not doing it. Through, you know, through your true intentions of doing good, which you hope you would, at least notice that it it makes a difference in a lot of areas.
Steven: It’s kinda led to yet another area of research for the business area of organizational justice is why do people get it wrong? Why do organizations get it wrong? Why do the managers get it wrong? If it’s that simple, if it’s the golden rules, why did they get it wrong? And in the answers that I’ve found through my research, and then through research of others.
Part of it is the more I feel responsible for what went wrong Right. The less I want to tell people about,
Charles: yeah, So you shouldn’t have responsibility. Right?
Steven: If I can blame it on something else, you know, that’s right. Keep the pace with you and all, you know, we’ll we’ll both about most of that situation or whatever. You’re the pandemic. You understand how it is. But if I messed up, it’s a lot harder for me to sit across the table and look at somebody and tell them they lost the job I messed up.
Yeah. Yeah. Part of it too is that as managers, as leaders, we get busy. Yeah. Yeah.
And if you think about a layoff, that’s a time of this a whole lot going on. We’re gonna have to be doing, you know, a a lot more with fewer people. There’s all these things to coordinate and we just kinda lose track of the human aspect because of all the other things we’re dealing with. You know, some of my research just found that the more people we lay off the worse we treat them. Well, that kinda interesting.
Because you you got you with more people on lane, not just a couple I I can sit down with them. I can have that conversation. Right. But if I’ve got five hundred I’m laying off, now I’m leading the landscape of Nick and telling them all at once and it’s Yeah. Right, ma’am.
Charles: You can’t fly George Clooney in to everywhere at once. Right? I’m sure you saw that movie that put in the air or whatever. So gray movie, you know, there’s only one George Clooney go around to be the hatchet band or whatever, you know. So, yeah, that that’s interesting and that’s where you get into kind of a blend of social psychology, how humans react in these kind of situations.
I like to think, boy, one of the things I’ve really learned and have incorporated in my in my daily goings and comings and goings is is to stand up and be accountable when I mess up something or when there’s something hard to do. It’s not easy to do. And, you know, I’ve never had to I have had to lay people off actually, but I feel like I did it. You know, with some class.
Steven: He served for a number of years in administration with the business school at Aratana. And and when I was by steam, we went to a number of years of budget. Cuts. And I have to lay off quite a few people. And what I found, this was completely subconscious, and I didn’t know I was doing it until I looked back on I what I found is it, every day when I hit the lake nobody else, I worked high.
Really? Interesting. Yeah. Yeah. It was so interesting.
And I side tri figure, why am I is it, like, is it body armor? Is it or does it make more official? Or, you know, does it strengthen me as a but it was just subconscious of every day it was gonna be something else. Wearing Yeah. Yeah.
Interesting.
Charles: Wow. And maybe it was just sort of stuck. I don’t know. I can’t come up with that one. Maybe you need to do some research more
Steven: than that. Maybe. You know what I mean?
Charles: Yeah. Already. That’s what I thought. Right? Or just it’s a formal it’s a it’s a pretty serious conversation.
Yeah. You’re you’re showing what your role is in the conversation as the authority. Person, you know? I’m assuming you didn’t wear ties a lot of other times. I haven’t worn a tie in a long time.
Steven: Signaling. Like, yo, Steven’s walking in with the tie and people out of the go.
Charles: Oh, yeah. Shit. Exactly. Oh, nothing good. It’s gonna happen.
Nothing good. It’s gonna happen here. Cool. Well, I wanna talk a lot about the the the modern problems here in technology, but let’s play a little, take it or leave it here. But I’m gonna switch the scene here.
So let’s see.
Steven: Got a
Charles: little music going on. Alright. So take it or leave it. It’s pretty simple. Have two articles and we’ll we’ll each take a look at the article and give our commentary and then we’ll we’ll at the end of each article where we got two articles, we’ll we’ll say whether we take it or or leave it or not.
So the first thing I’m gonna do here, I’m gonna get this first article up, and then I am also and there’s something weird with the CSS here. I’m gonna add your camera. Let’s see if you show up. Here’s the article. I’ll show just the the actual Like, just to show it’s a real article.
Right? You can’t even really barely see it. Because something with the CSS on some of these, they don’t show up and other ones, they don’t have try it and try it. So this article, I’m just gonna actually go to the little TLDR card for it. There we go.
Alright. So The on chat, TTP, conspiracy theories are here. Don’t believe everything you read. Right? So this article is essentially and it’s in the source of truth and excellent journalism USA Today.
So you know it’s it’s gonna be legit. But basically, you know, technologies are are making conspiracy theorists come out of the woodworks and and go nuts, and it can mislead people. I think that big tag you know, back to this is why I wanna tie this into some of the stuff we’re talking about. Right? Big people think Big Tech are shaping the future of the planet.
They may not be wrong, and it can definitely I think it’s a, you know, can I’ll hold my commentary. I’m just going through here. Right? So are we weaponizing this information? Are we, you know, how do we how do we deal with this.
That’s basically this article is is saying, you know, maybe there’s maybe there’s some considerations here about good and bad from these things. Anyway, so what do you think about it?
Steven: I kinda like this article because it it did highlight this this problem that more generally is a problem of rumors. Right? You know, if Yeah. Before those AI, we had rumors. And rumors would spread, and sometimes they were right, and sometimes they were wrong, but they would spread.
Well, now we have AI and and technology that helps spread these rumors in, create these rumors far faster than we ever could in the past. From what I studies per perspective, the way you deal with rumors is through radical transparency. You know, let’s let’s share as much information as we can to try and take care of those rumors. I don’t know if that worked today. You know what?
How do you offset that, Scott?
Charles: Exactly. Yeah. I think that what they’re saying is is absolutely spot on. And I’m actually I’m glad to see a little bit of balance in saying that there are all these problems, but, you know, here’s things we can actually do to to combat them. I think that, you know, big big technology represents right now there’s a lot of uncertainty and they’re shaping things.
They’re shaping people’s perceptions. They’re not always good because they seem so in control of this. And and there’s a lot of trepidation about, you know, the future and where is this stuff leading in it. It’s probably more unknown, I guess, In the first industrial revolution, people didn’t know, people were freaking out. It turned out to be okay.
This seems just so much bigger and you could take a steam engine apart and see how it works and understand the the principles of physics, you know, behind it getting into a crazy giant neural network, that’s something like a like a, you know, an LLM that’s powering some of these things. Is nigh impossible. So we don’t really know what’s happening and it seems so humanized too. Right? So we start thinking about the fact that this stuff is is starting to act like us.
And so we are seeing a ton of, you know, a ton of emphasis on transparency and looking at how do we manage this? I don’t know how much I think we’re always gonna be behind that though, and I think that’s again, a reason why we have distrust going on. I was listening to something where you know how much it costs to to deploy a giant large language model is in the billions of dollars and it consumes so much energy. A lot of people say that to advance the technology, we don’t have the energy supply or the resources to actually be able to move of course, AI will figure out how to do it more efficiently. So we don’t have anything to worry about.
So how do you feel are your your thumbs up on this? Thumbs down?
Steven: I’ll leave them on thumbs up. Yep.
Charles: Yep. Yep. Me too. So I guess we’ll give that some some flaws. Good deal.
And now we’ll move on to the second one. And that one is gonna be this one here. AI hiring, we’ll just go again. Just wanna approve to everybody. This is a real article, and then we’ll go here.
AI hiring tools may be filtering out the best job applicants. Right? So what we’re talking about here is the idea that hiring is hard, especially at scale. Right? So we we’ve had a lot of automated things and and those things who knows how fair those things are and candidates may not really understand, you know, why if they get any message at all back.
About how this is happening. And that increases fears, I think, of unfairness. Right? And again, second article need for regulation. Is there a theme here?
Right? So so what are your thoughts about this one?
Steven: So so this one, maybe I young some good points and it made me a little frustrated. Okay. For a hundred years, we’ve been studying how to select people. You know, that’s that’s a basis of industrialization psychology. Yeah.
How do we go about selection people? And we know we develop these concepts of validity, that whole selection. There’s better ways to predict. That’s what this article is talking about. It’s in terms of stuff.
And and and it it frustrates me because, you know, every ten years or twenty years, somebody comes along and say, let’s look at this. Yeah. We’ve been looking at this forever. And and so AI may be screening out the the wrong people if you have a, you know, a predictive that’s not valid. But we’ve, you know, we’ve been using bio data.
We’ve been using all sorts of things for decades to do this. And and so what I wanted to do is it’s like, okay. If we screen out their own people, is it because it’s not a valid predictor or it’s because even with a valid predictor, sometimes we get it wrong. Those are two critically different questions.
Charles: Yeah. And, you know, if you’re if you’re getting if you’re getting a twenty five percent hit rate on accuracy and hiring you’re the greatest hero that ever lived. Right? It’s just that scale and certainly certainly, it still has value. You don’t want it to be flipping a coin, you know.
But so that’s a great point. I didn’t think about it that way. Because I’m so triggered by seeing AI that immediately what I thought is, oh, they’re talking about, you know, complex neural networks, you know, the kind of stuff that you don’t know why it works, but but really they’re not. If you if you look through this, they don’t really say anything about what the AI is doing, For instance, candidates face rejection without clear reasons. That isn’t, hey, we don’t know what the algorithm was doing.
That’s exactly what we were talking about before. And I’ll tell you one of the things from the from the practical trenches, you know, where I am is, Nobody gives in the UK, I just was working for a UK based company. I think candidates have the right to requisition their assess results, but it’s very common to say, here’s a short sheet of developmental things that based on what we saw here, these are your strengths, here are some things you can work on. Thank you very much for applying and spending the time to take this test. In the US, I haven’t ever seen that.
I there’s so much fear of telling somebody you didn’t get the job because you’re not a good enough team player and that person running screaming to the EOC or someone. Right?
Steven: So sometimes it’s proprietary too. Right? Like, you know, so I I do work with an integrity testing company. And and then that, you know, people will sometimes wanna know, well, Well, what questions did I answer wrong? Well, that’s the secret sauce.
You know, that’s Yeah. You’ve got a a a a bag of questions and you have the secret sauce that kinda determines the pass field. Right. Specific questions without revealing the secret sauce. So it it is frustrating to people if they’ve taken a test or something.
They don’t know why they failed. But it that’s part of hiring.
Charles: Yeah. That’s true. That that lead that triggered a little story for me. So before I ever even knew anything about industrial psychology, before I came to grad school, I applied for a job at a ski resort and they gave me an over an integrity test. And I looked at it and I’m like, you know, how many times have you associated with people who’ve stolen how many times have you associated with people that have you ever stolen anything?
And, like, what person in the right mind applying for a job would answer this Honestly, the reality is they do work. I think people who who truly do that stuff a lot don’t even they’re so disconnected with the fact that it’s the wrong thing to do. Sometimes they’re proud of it, you know. And so those tests do work. They work really well.
I’m sure you I’m sure you know that, but You buy it too. From a candidate perception standpoint, that’s not always so great. Oh, you’re accusing me of stealing. Why would you even ask? You know, I would never do that.
So there’s there’s that side of it, and we face that a lot of times in in different in different measures, you know, one of my golden rules whenever I look at a lot of employment tests and I give a lot of feedback in. One of the things I’ll always say is, you know, you ever ever want an applicant to look at something and say why are they asking me this? This has nothing to do with the employment. I guess, with an integrity test, it makes sense you don’t want someone who would steal. So maybe that’s not as, you know, relevant, but it’s an important thing as we’re talking about signals and that kind of stuff.
And applicants really do like there’s some I don’t know if you’ve ever looked at the research from the talent board. They do the candidate experience research. Basically. They have the candies award and everything. They put out some pretty good research because they they essentially survey applicants.
Thousands of applicants. The preponderance of that is applicants love the opportunity to demonstrate their skills on the job. So, you know, you’ll you’ll sit for I would hope anyway. And that’s the other thing I tell people who say, our candidates aren’t gonna do this, etcetera. I’m like, would you really wanna hire somebody?
Who really wants a job and isn’t willing to give you twenty minutes. You know, come on. I don’t know. But but I’m not a talent leader in dealing with shortage of talent. So So who knows it?
Anyway, so on this one then, you know what? What’s your vote? Tell me your vote.
Steven: I’m gonna have to give it a thumbs down because too much old wine and new bottles Yeah.
Charles: You know what? That’s great. I’m not a yes man because I was coming into it going, you know, AI is difficult and we need to we need to talk about this, but you’re right. I tell people all the time. We’ve been looking at adverse impact and test fairness since the sixties.
It’s not a new thing people. So I’m gonna give it a thumb down too, and and we’re gonna gong that thing right on out of here. And that’s it. So cool. So thanks for doing that.
That was a lot of fun. Let’s get back to the to the fun stuff. And as we kinda wind it, down here. We got a little bit more time, but let’s talk about technology in this stuff. Right?
I mean, it’s super easy. To it’s easier to think about it in simpler times. Now we’ve got all kinds of crazy stuff happening. Have you done anything or, you know, any research or any thinking about what changes in this stuff? I’m assuming it’s immutable, but what’s the what’s the impact of technology on all this?
On AI, a large language mix, etcetera.
Steven: You know, they’ve asked me a huge question there, but I I I have been because I think technology changes the speed at which we have to deal with things whether it’s challenges at work, whether it’s rumors, whether it’s people unhappy with our hiring process. I mean, people have so much more ability to to share their opinions now and to gather information. Yeah. And just what we were talking about with the first article are sources of valid information of trusted information are getting fewer.
Charles: Yeah. You
Steven: know, we we we used to all turn to the six o’clock news to find out what’s true in the world. Now everybody has their own source of of truth, of knowledge. And and with that, our side starts to fracture apart, and our challenge is in in in in is organizational psychologists, I think, become greater. Okay. This is something that we really we haven’t even we’re at the we’re at the tip of it.
We we haven’t even started to see how big this problem’s gonna grow yet.
Charles: Oh, yeah. So there’s so many dimensions of it. Right? So you’ve got you’ve you’ve got, hey, what information can you trust? Right?
And it’s as we’ve start and see, like, deep fakes, all these things are just, believe me, a couple years. Anybody will be able to make a video that looks like us do in this podcasts when we didn’t do it. Again, regulations thinking about how do we watermark this stuff, etcetera, but I don’t think we’ll ever be able to fully keep up. And then there’s the, oh, the one thing that I’m super interested. I’ve read a little bit of research.
I I don’t do much academic stuff, but I’m I’m a I’m a reviewer for the, you know, international Journal of Selection, and we’ve seen a pretty interesting ones about articles about AI based interviewing and and being able to understand why, what was going on in that interview, what the signals are. So, you know, and a lot of times, stealth assessment, you don’t even know you’ve been assessed. Right? And there’s there’s rules and regulations that are that are speaking to giving notification. But have you have you looked at anything around the use of AI and hiring process and candidates perceptions and how that’s going you know, what’s that’s going on?
Steven: You may have. And let let me dig just from from two perspective. Well, you know, first of the AI and hiring, I think this has the opportunity to completely change it. I I gave my students this past fall, an article, a new article that looked at basically using AI to assess personality. And and with a you you you you the AI AI does a basically an interaction with with people Yeah, man.
This is big five personality. Mhmm. And pretty valid predictor of personality. Yeah. So now think about all these things that we’ve developed, these selection tests and so on.
What if AI could do that without even interviewing. They just go through all the information that they have on you on the web, and they come up with a better predictive than any of the tests we can write. Yeah. That could be the future. Now from an applicant perspective, not only do I want to be known be treated fairly, but I wanna know why that decision was made, how the decision Yeah.
I want procedural justice. When it’s a black box, there’s no procedural justice there. Yeah. Alright. So I I see radical changes to our field over the next ten to fifteen years.
I’m exciting and scary.
Charles: Yeah. I agree completely. I feel like, at this point, we really don’t want those things. So the human and loop idea. Right?
So where you see that now, is, yeah, the the look, IBM Watson ten or more years ago already had a a thing where it could look at you know, just your stuff on the web and tell you your big five profile. They use it more for marketing, believe it or not. It didn’t really get put into hiring. I’m assuming they still have it, but, you know, there’s a lot of NLP just looking at text that can do that. I’ve been somewhat skeptical about it.
But, like, I just did one the other day and, you know, was I’ve taken so many tests. I know my big five profile pretty well. You know, I can be pretty accurate. I would say, I’m not a fan of just using personality alone and hiring decisions anyway. I I feel like it’s it’s worthwhile, but it’s not the whole story.
It does give you some some decent signal, but it is gonna change completely. It already is starting where I would like to see it go, and I’m doing my fair share here to to to be part of it is, it’s gonna allow us to simulate jobs much better, right, and and more accurately. And that’s never been easy to do at scale. Some jobs haven’t been good to simulate. You’re gonna be able to get into these interactive experiences that are gonna be scored, you know, while you’re doing it based on things that hopefully humans have had some, you know, role in creating and setting up scoring, etcetera.
And I even see it as, like, which it gets hard in the selection paradigm because it has to be kind of controlled. But but I’d even see it as just your daily travels and your interactions and what you’re doing and then collecting that data. There’s privacy issues. So I think technologically what we’ll be able to do and realistically what is ethical to do and you know, honors privacy and all that stuff are gonna be two different things. And that’s one of these things that we we find out with AI.
But yeah, I always imagine this future scenario where you’re just you’re looking around on the street and your glass will say, oh, that person. Yeah. They’re they’re gonna be a really good project manager, you know, go over there and and hire them. I have some AI glasses. I really like them, but they’re the best piece of tech.
I gotten a rabbit, a humane pin that those things are garbage. But my Ray ban meta glasses are great. And they will not identify a person now now. Like, you can’t you because you can look at something and just say, hey, madam, what am I looking at? And it’ll take a picture, and then it’ll go to a lama large language model and give you some information.
But if you point it out, a person, it’ll be like, I can’t tell you that is kind of thing.
Steven: Interesting.
Charles: But yeah. They’re they’re that kind of stuff, man. It’s it’s definitely coming, and we’re not gonna be able to stop it.
Steven: And and just a quick example of of how, you know, this it’s not really selection, but you can you do you see how it’s a selection. One of my colleagues at University of Arizona when I was there was using machine learning to try and predict which freshmen are likely to drop out of college. Uh-huh. Interesting. And and she got access to basically, they they had the, you know, student cards that were called BRAC cards.
Yeah. I was there. Okay. From cat card scan, she could predict with pretty good accuracy. I can’t remember what it was eighty five percent, you know, something like that accident.
It was going to be withdrawing, dropping out of college in the freshman year, based on how they were swiping their cat card in different parts of campus. Really? That’s that’s pretty interesting. When when you start to think about using the machine learning. Yeah.
We’ve got a whole field of
Charles: oh, yeah. It’s really
Steven: really exciting where we can go with this.
Charles: So what was the I mean, what do you does she know what the reasons were? Like, you got these features or you’ve got these things that are showing statistically what’s happening. Then you’ve gotta kinda rationally say, okay. Well, what is that data telling us? What logically is going on?
Were there I’m sure there were some things. Right? Like, how much of beer you bought? It’s
Steven: like, I’m jable with engagement really. I’m really excited. This is Steven interpreting it. Right. Yep.
But my interpretation was engagement. So people who are more engaged, they’re going to the gym, they’re going to the, you know, getting their their Right. Right. Sure. They’re not gonna drop up.
It it’s it’s you can see of though of those who are dropping up this DITS engagement, they were no longer connecting with with the game.
Charles: So let’s take that into a selection scenario because these people, they’re already in. If they’ve already gotten in, So is there anything about what they’re doing that you could could flip over the wall and say as a predictor evaluating applicants how can we tell disengagement? Because this is a it’s a selection scenario as well for a company. Yeah.
Steven: And and I think that we could. Right? I I I seems to me that if we figure out what are the right, you know, what are the indicators of people who are likely to engage or whatever we’re looking for. Are we looking for engaged people in this job? Are we looking for dependable people?
Right. And we’re we’re a temp agency. We’re looking for people who just show up Yeah. We should be able to predict who’s gonna just show up.
Charles: Yeah. That’s true. And I think at a temp agency. Yeah. But but across the bigger picture, I mean, you wanna know more stuff about people.
I do say that about about the whole about the whole g thing. Right? Which is a whole another podcast of, you know, is is general intelligence the best predictor? My opinion said it’s it’s not But I always say, well, you know what? The smartest person in the world, if they don’t show up for work, you’re not gonna get anything out of them.
You know? Or they’re a jerk to their coworkers and nobody wants to collaborate with them or whatever. So it’s a multifaceted thing. I I think just saying, you know, what’s the one thing? It’d be great if we could know that.
I think people are too complex.
Steven: For that. I I think so too. And and to me, the future is not show is is not predicting who’s gonna show, but is predicting how much of that person, are we gonna get a Yeah.
Charles: There you go.
Steven: If you’re Steven, are you getting a hundred percent of Steven? Are you getting twenty percent of Steven? How much are you gonna get, Steven, if you hire?
Charles: Yeah. And then from a justice standpoint, I got a lot of pirate things going on down here. It’s conventions and stuff. I don’t know. I remember people have the t shirt that says, you know, the beatings will continue until morale improves.
Right? So, like, if you’re a if you’re a manager, who is using levers that actually disengage people. You could have people with good. So again, that kind of justice thing. How are you getting me to to do my job?
What are the rewards or penalties I’m getting? The sometimes managers are the ones that are the arbiters of that rather than the organization. You know?
Steven: Yeah. Yeah. Exactly.
Charles: So to your point about, are we gonna be as we kinda wind down here? Are are we gonna be obsolete? As I as psychologists, I would say, all the technology in the world we still have people that are responsible for getting things done in an environment, assuming that it’s not all robots at some point, which it might be. Right? But but realistically.
Right? I mean, there there’s not gonna be a shortage of reasons for us to be around. I’m not just rationalizing that. I think when it comes to, you know, creating some of the the systems that are that we’re working with, that might be harder. But it’s it’s all about what’s impossible to know.
I guess that’s what’s so exciting about it. Yeah.
Steven: And I think it comes back to the the article we gave the thumbs down to. You know, they if if we’re not there, as I was psychologists, then people are gonna be reinventing stuff. They’re gonna be looking at stuff without considering the implications of what about adverse impact with this this, you know, machine learning language model you put together. Yeah. What applicants reactions.
What, you know, all those things that we add to the formula that we add to the higher taxes. I think the real advances come from us teaming up with the AI experts and and figuring out what’s the future of collection, but it’s got one bomb us yet.
Charles: Oh, one hundred percent. And I would say that it has already happened. And, Steven, if you look at the top of the funnel stuff with, you know, there’s a lot of companies that are that are using all kinds of AI stuff to parse apart resumes, to look across the web and pull information, and look at a job, and say, here you’ve gotta match. But there’s no substance behind that. There’s no real measurement.
It’s just a it’s just a big soup of words that align together and and then people make assumptions based on that. And that’s how people are entering the hiring funnel. Right? And hiring is nothing but a game of probability. So if you’re putting the wrong thing at the top of the funnel, it’s a lot harder to get it out the bottom.
And I think that’s you know, that’s the area where I just hope some of these companies are saying, well, you know, what about couldn’t we make this better if we added some psychology to it. They probably think, oh, that makes it more complex and people are still spending millions of dollars of lining up to buy this stuff. So why do we care? I feel like that might be more of the the attitude. But anyway, we shall see.
Well, great conversation, man. It was really good to to speak with you and to talk about some of these issues and hear from a perspective of somebody who’s been thinking about this stuff for a long time. It’s more relevant than ever. So that’s good stuff.
Steven: Thoroughly enjoyed this. Yeah. I got a wonderful podcast you have here and so glad they have the opportunity to share this time together. Yeah. Thanks.