“We talk about the effect of technology on everything, but ultimately, it’s the people that matter. This theme has shown up repeatedly, emphasizing that technology doesn’t have uniform effects; we have to consider the psychology of implementation, how it’s used, and its context.”
`- Tara Behrend
Summary:
Technology is making the study of psychological safety in the workplace more important than ever. I can’t think of a better guest to help me kick off the new direction for my podcast than Tara Behrend, professor of HR & Labor Relations at Michigan State University, founder of the WAVE lab, and current president of the Society for Industrial/Organizational Psychology (SIOP). Tara embodies the spirit of a scientist practitioner. Her research into the impact of technology on the psychology of humans in the workplace has profound implications for our ability to understand themes that are critical to ensuring the future of work is both prosperous and meaningful.
Tara and I have a great time exploring a raft of topics centering around the psychological implications of emerging technologies in the workplace, the role of AI in learning and connection, and the significance of career and technical education in addressing evolving workforce demands.
Ultimately we both agree that the golden rule and the psychological contract are the forces that impact humans’ perceptions of psychological safety in the workplace .
Listen to this episode and explore the depths of Psych Tech @ Work through Tara’s research and ideas!
Take aways:
Balancing AI and Ethics in Hiring: The discussion reveals that while AI can streamline the hiring process, it requires a careful balance to ensure ethical application. Tara stresses the importance of transparency and continuous oversight in AI systems to mitigate biases and uphold fairness, providing a blueprint for organizations to follow.
Adapting to Remote Work Technologies: Insights from the episode illustrate that successful remote work depends not just on the technology used but on how it’s implemented. Strategies for maintaining communication, fostering collaboration, and sustaining engagement in remote settings are crucial for preserving company culture and employee well-being.
Innovating Learning and Development: Tara points out that technology’s role in learning and development extends beyond access to information. It involves creating adaptive systems that tailor learning experiences to individual needs, promoting more effective skill acquisition and career growth.
Understanding the Psychological Impact of AI: One of the pivotal learnings is the nuanced psychological impact of AI on employees, including feelings of trust or mistrust towards automated systems. Companies are encouraged to foster an environment where technology serves as a support, not a replacement, enhancing job satisfaction and productivity.
Navigating Technological Change: The episode underlines the necessity for both organizations and employees to remain agile amidst technological advancements. This involves fostering a culture that values upskilling, reskilling, and continuous learning as essential components for thriving in the evolving workplace landscape.
Addressing Surveillance in the Workplace: Through her insights, Tara highlights the increasing use of surveillance tools in monitoring employee productivity and behavior. A key learning from her work is the critical need for ethical guidelines and transparent communication about the use and purpose of surveillance technologies. Organizations must balance efficiency and privacy concerns, ensuring that surveillance practices are implemented with respect to employee autonomy and trust, thereby preventing potential negative impacts on morale and workplace culture.
Full transcript:
Charles: Alright. Welcome to the show, Tara. How are you doing today?
Tara: Not too bad. Thanks for having me. I’m excited.
Charles: Yeah. Absolutely. Well, I’d love for you to introduce yourself to our guests. I’m looking forward to a civil leading fun conversation, but let us know a little bit about yourself, your current role, and kinda how you’ve gotten to where you are now? What’s your journey been?
Tara: Sure. So I’m an industrial and organizational psychologist. I am currently the president of SCIO, which is our primary presidential professional association. Yes. Very exciting. I’m wrapping up my term in a few weeks doing. So I’m also looking forward to retirement. In my work life, I’m a professor of human resources and labor relations. I’m Michigan State University City. Before that, I worked up Purdue and George Washington University. I also spent a few years at the National Science Foundation as a program officer where I oversaw feature of work program. My research has two main buckets. The first bucket is about the psychological implications of new technologies in the workplace. How we learn, how we connect to each other, how we think about our work. And the other has to do with how people learn about their jobs in a broader sense.
And so lately, I’ve been working on a number of different projects related to career and technical education and how we get more people thinking about more kinds of jobs as we think about the evolving workforce and evolving demands of that workforce. How do we respond to those changes?
Charles: Awesome. Thanks. Yeah. And so couple of notes here. Well, president of Sayap, that’s awesome.
You’re the second I believe Saia president I’ve had on with our dear friend, Fred Oswald, and the other one. So you’re in in really good company. And You know, I think it tell me, like, what’s your favorite thing then about that?
Tara: About leaving Zayo. Yeah. What is it? Sure. Well, we have Siap is a really special organization because there are so many critical functions of the organization that are run by volunteers.
We have something like seven hundred volunteers supporting everything from building the conference with five thousand people attend, to organizing all of our professional development offerings, to organizing our federal government relations efforts. And so these are really exciting projects and they’re all that big people who just have a passion for iosecology. So for me, it’s incredibly exciting to sit in a position where I can learn about all of those different activities, support them, help make sure we’re also growing in the same direction. Towards our strategic plan and our strategic initiatives. But the breadth of what SCIOP does is really just kinda dazzling, and so it’s been so fun to see it from this from this seat.
Charles: Yeah. So I have let’s see. I have missed one sign up since nineteen ninety too. So I’m like in a thirty year veteran here. And I love it.
And what I’ve seen about it, and I’m sure you’ve noticed probably even been a part of it is just the expansion of the focus or kinda areas that people are coming from. So a lot more commercial looking at technology and startups, a lot more international. I just feel like it’s grown. Right? I mean, so much.
And there’s so much more unique and interesting stuff going on. It’s it’s a conference where I go to a lot of conferences where the content is really just kind of secondary or not that great. But from a content perspective, it’s been amazing. And I’ve I’ve enjoyed contributing to the program a good deal, and I think that’s another piece of it. People are very active and wanted to contribute, like you said, even on on the content side.
So
Tara: Yeah. But to your point, there there are not very many organizations or conferences that I can think of where science and practice are both represented and they’re both integrated. You know, ordinarily, it would have something that sort of exclusively incorporate like a trade show feeling or exclusively academic where people are just sort of presenting their research to each other in a very a very sort of close community, but Siob has to serve both of those audiences, and I think it does it really well where people are learning from each other. And if you look at the program, there are so many sessions where there’s a mix of scientists and practitioners presenting even in the same session. Right?
Different angles on the same problem, which is so unique. And I go to a lot of conferences, and I’ve never seen it done quite that well, which partly reflects our field. Right? Our field is a science practice field. But I think it also reflects this really intentional choice on the part of the conference organizers and the program committee to make that we are that we are speaking to all these audiences.
But I will say too that, you know, as the conference grows, like, almost and thousands and thousands of people. It’s really easy to feel lost and it’s harder to find your people. So that’s something that I’ve been thinking about a lot lately. Like, how do we build smaller communities within sign ups so that you aren’t just overwhelmed with four thousand strangers when you show up? And you don’t know, you know, where to look for the people who you might learn something from.
Because, you know, for us, we’ve been going for twenty years. We sort of understand how everything works and where people might be, but it’s almost impossible to figure that out if you’re coming from the outside. So that’s something that we’re we’re building in a lot of different ways, a lot of examples, but the whole goal is to say, like, SIOP is also a small community where you can find your people in addition to being that big overall umbrella organization.
Charles: Yeah. No doubt. I mean, I know there’s communities of practice that are, you know, popping up where you have kind of the, like I said, micro things. I also think the app, the Wova app that’s used is a good way. I couldn’t believe all the cross communication, you know, about goofy stuff and about stuff that people share in common.
It’s really entertaining even to just to take a look at that. That’s kind of a new a new thing. Well, that’s great. I look forward to it this year. This episode may actually air after the conference, but they have it every year, and it just keeps getting better and better.
And thank you for, you know, your leadership and your effort to contributing. It’s fantastic. So I
really wanna talk about your research and your practice stuff too. Some of the stuff I’m familiar with and I thought was really fantastic. It’s you one of the main reasons that I wanted to make sure you could be a guest on the show, but tell us a little bit just personal what’s on your nightstand?
Like, what are you reading? What do you like to stream? What things interest you outside of this world?
Tara: Sure. Well, I’m a big science fiction fan. And so I try to keep up with whatever’s new in that world. I mean, the options are are very numerous, and so I don’t pretend to hit all those boxes. But the other thing I’ve been reading a lot lately is biography.
So I started working my way through the Pulitzer prize winning biography category, like, going back in time.
Charles: Oh, wow.
Tara: And it’s such a fun way of looking at history in a in a different way. Right? Like, you you look at history through a particular person’s experience, and it gives it such a richness, and it it really, I think, puts it in a different perspective that I really enjoyed a lot. And so sometimes I’m reading biographies of people I admire. Other times as people I’m not as familiar with or people I’m actually not so crazy about, but it’s still is always very entertaining and and surprising to hear about folks’ lives.
So Those are the main things I’m reading lately. I’m also a big fan of the Forbes Civilizations podcast. It’s pretty brilliant. It sort of chooses one civilization from ancient history and describes Oh, it fell apart. And it’s really well produced, but also sort of grim as you start noticing all the commonalities and you think, like, oh, gosh.
Charles: That very cool. I’ll have to check that one out. I always love when I get new suggestions. I’ve started to become overwhelmed with podcast. I honestly my dirty little secret, I didn’t really listen to a lot of podcasts even though I’ve had one for a while. The game changer for me, I just got these metal, ray ban, smart glasses. And so you can listen like hands free. You can take pictures, live stream. It’s got a basically, a chatGTP, large language model generative AI built into it. You can look at stuff and it’ll tell you what it is. It’s nuts. But I walk up two dogs. I walk my dogs. Usually my hands are full and I’m fumbling around, but now I can listen when I’m walking and it’s awesome. So I’ve started to listen to a lot more check that one out.
But there’s just not enough time to listen to all of them.
Tara: Yeah. Yeah. Well, the reason I like the the audiobook format is because you can do it while you’re doing something So, you know, in a mock dog in the morning or traveling. I spent a lot of time in airports. And it’s really I can’t do meaningful work in those environments, but I can definitely listen to some sort of medium quality podcasts and and feel like I’m learning something.
Charles: Absolutely. Yeah. I can’t do meaningful work in those kind of transitions either. But working on the plane, that’s the worst. My arms don’t.
Fit. It’s horrible. I’ve had to do it for deadlines before. So tell us a little bit about so you’re
Michigan State now, by the way, both my parents went to Michigan State, my dad graduated from the clinical psych program in, like, nineteen sixty.
Tara: No way.
Charles: My cousins go there. Yeah. My mom from Detroit. So I I definitely have a love for Michigan State, although I’ve never been to East Lansing before, believe it or not. And what a storage site department there in I O and in clinical as well.
So that’s that is awesome. So tell us a little bit about I mean, there you’ve you’re doing research there. I know you’re kind of freshly there compared to the rest of your career. But we’ll talk about that a little, but You have done a lot of research and and it’s all really good stuff. Is there one thing that you have really learned from all that work or one one profound revelation that you might have had or maybe it’s the collective of it all that’s had an influence on you. It really sticks out. You know?
Tara: Yeah. I’ll say two things. One about the research process and then two about the findings. So as far as the research process goes, something I’ve learned over time is that doing a few projects that you’re really excited about that you think will make a difference in people’s lives is way more valuable than doing a bunch of papers or projects that you don’t care about. And it just leads to better work and leads to more work in the end sort of paradox Right? If you’re focusing on doing good work that matters, you end up with a body of work that is maybe bigger than it would be otherwise. But but I I tried only to use projects that I’m really excited about and that I think really will be useful to somebody. And that will lead us to learn something that is that is true about the world. So my favorite research projects are always where they’re two possible explanations for something, and then the project is a way of figuring out, like, which explanation is better or under what circumstances is this explanation more true. So that’s something that, you know, has emerged over time, and it’s something that I really try to keep as a value.
As far as things I’ve learned from the research, two things. One is that we talk about technology a lot. I think we talk about the effect of technology on whatever, everything. But Ultimately, it’s the people that matter and that theme shows up in my research over and over again that technology doesn’t have these sort of uniform effects rather we have to think about the psychology of the implementation, how the technology is being used, and what context is it being used, if we wanna understand anything about it. We had to think about the particular features. Like you talked about your meta glasses. Can we say anything about those glasses that applies to other kinds of augmented reality interventions or applications, like, maybe not. Right? But we really have to use, like, the logical ones to understand when it might be true or not true. And so that that theme has showed up so many times.
And I sometimes, I feel like I’m falling down into a cliche, repeating myself so much about that, but it really is, like, the people first and the technology second is how we generate insights about technology.
Charles: Yeah, one hundred percent, you know, there’s oh my gosh. Well, it shows up in a lot of things, you know, in in every time we start talking about AI, it’s like, it’s not just working on its own. It’s, you know, it’s it’s the people that are behind it, the people that are working with it. Hopefully, it stays that way. It doesn’t get and I don’t wanna get too dystopian.
I don’t I don’t like to fall into that trap unless I’m really making hyperbole, you know, to try and try and make a point. But but what you just talked about really came out a lot, like, when you said that, the I saw you present at a conference, we both presented that. I think it was iPad, but the the work on surveillance. Right? That I feel like the takeaway from that really was that kind of individual differences and individual circumstances really made a profound difference in how people solve things psychologically.
Right? And we are people. So psychology applies to all of us And when you’re in the workplace, you have a lot of interesting dynamics and you throw technology in there, and it can get really cookie. And I felt like that was really fascinating research as we look at psychological safety and and as devices. Right?
Like medical glasses or I think I don’t know if you’ve ever read the book the Future of Work. I’m trying to remember the author. It’s actually not a super recent book, but what they did is they had people wearing little tracker things all day in the in the office environment and just kinda watched what they did and tried to draw some conclusions from that data and you know, I think one of the conclusions is people don’t really like that very much. But tell us a little bit about the, you know, the surveillance research that you’ve done, kind of what those studies were, and what did you find there that people would be interested in? Because this is something that’s happening. Unfortunately, a lot of times when we don’t even know it, hopefully not that often, but, you know, it’s it’s kind of shady these days sometimes. So
Tara: Yeah. Well, I try to avoid making claims like you should or should not do x, whatever x might be, and rather focus on one of the behavioral effects when you do x. Right? What are the consequences? And can you live with those consequences?
And if and if not, don’t do that thing.
Charles: Right.
Tara: So in the context of tracking, monitoring. Sometimes the purpose is lifesaving technology. Right? Like, sometimes you’re monitoring whether someone’s been exposed to too much radiation and that’s really really important and you should definitely keep doing that or you’re monitoring your eyes for signs of fatigue and you’re telling a truck driver to pull over, which is, again, a lifesaving technology. So I’m never going to say, don’t track people at work. That’s not a useful statement.
Charles: Sure.
Tara: But what I will say is don’t use the information that you collect from tracking to generate performance goals. Don’t use it to define what performance really means because it is not a rich measure of all a person’s contributions to the organization. And also, when you do that, when you put these metrics in place, you end up creating perverse incentives and negative consequences. Like, The best example is that delivery driver services. I think it’s really tempting to use the information from tracking to set new tools about how long your route should take, and how long every stop should be, and you might say, like, look, the data say you can do every stop in thirty seven seconds, so do that.
But then what people do is they drive unsafely. Right? They don’t stop stop signs. Charles: Yeah. Yeah.
Tara: They don’t even sometimes, they don’t even bother stopping at the house, right, because it’s faster to just stick a sticker on the note. This says, sorry, we miss you. And you don’t want any of those consequences. Right? So if you take this data that could be used descriptively and you use it prescriptively, you cause problems.
If you take data that were meant to be safety measures and now people are suspicious, then they find ways around the safety measures, and then now they’re not accomplishing their safety purpose anymore. So if you were to track for example, where people are throughout the day, from nurses. This is a really valuable thing to be able to deploy who’s the closest nurse to an emergency. Right.
Charles: Right.
Tara: And that’s really useful. But if you start punishing the nurses for, you know, you were in this room too long, they’ll just take those badges off and throw them in a different room and ignore them. And now they’re not serving any purpose any at all and potentially distracting people from things that are more important. Right? Because they’re focusing on whatever is being act.
So a lot of people feel like if they’re remote workers, then their managers don’t know how to manage them. And so they rely on this kind tracking, and they’ll say, like, well, I see that your computer was idle for an hour in the middle of the day. What were you doing? Well, maybe I was thinking. Right?
Maybe I was thinking, you know, for the company, or maybe I was having a phone call, or maybe I stepped away, you know, to deal with a personal matter, but it doesn’t matter because what matters is what I’m contributing to the organization. Not how many minutes I was in my seat. And that’s the danger of these technologies is that people use them as a shortcut for lazy management, and that’s never okay.
Charles: Yeah. Well, from a psychological standpoint too, though, just how people’s attitudes or reactions are. Right? I remember getting that research there was definitely something about just how the company positioned the reason for the surveillance made a really big difference. Right?
So I think it’s and it goes down to the basic things that people want. Right? Communication, rationale, like so maybe talk about that a little bit, what are the individual circumstances where surveillance does go on that where it can even if it might seem creepy if it’s positioned properly? Maybe people understand and buy into it more?
Tara: Maybe. So we did look in the paper that you’re referencing, we did look to see whether the stated purpose had a difference. And and actually, it doesn’t have the kind of difference that you might expect mostly because people have to believe you when you say it has a purpose, and they’re gonna use their eyes first. And so if you say this is just your own benefit, but then you see people getting fired all around you. Like, that’s not a believable message.
So what people say and what they do, right, are different. We can say though that if people are in, like, a fear mindset, then they’re not gonna perform at the same level. They’re not gonna learn anything new. They’re gonna be afraid to take risks and taking risks is how you learn new things. So they’re not learning anything new.
So all of these things we take we can say, for sure, happen as soon as people perceive that the purpose of the tool is to punish them. And that perception can come from what they see around
them, not what the manager says they’re doing. Right? So the manager can say, oh, this, we’re just easiness for workforce planning. We won’t use it for individual consequences, but you’re gonna look around and see what happens.
Right? So The part of the reason this is an issue for me too is that all of these cool, like, AI tutors and real time feedback systems, they all rely on monitoring for the information that they used to do the feedback. Right? So if that’s gone because people are afraid to make mistakes in front of the tool, then the opportunity for them to learn is gone too.
Charles: Yeah. Yeah. For sure. I mean, it is very delicate. Is there a use case that you’ve seen that’s really, like, the most universally, like, You just should not be doing this at almost. It feels to anybody who looks at it. Like, that’s so wrong. I can’t believe they’re doing that.
Tara: Yeah. Yeah. I think anything that could be called micro managing, right, is never gonna be beneficial. And it’s especially bad if the micro managing target is something that is personal. So if you are sort of crossing those boundaries of people’s personal information, like their emails, or who they talk to all day.
Right. And there’s no clear work purpose. That’s Mhmm. Number useful.
Charles: Yeah. And that happens. You’re saying that happens.
Tara: All time.
Charles: Yeah.
Tara: Yeah. All time. People think that, you know, this is an unfortunate consequence of the big data revolution you people are so eager for sources of new data for for generating insights. Right? Like, how do we train all these cool AI models that we wanna implement? Well, we need data And so they’re just grabbing any source of data they can think of to train new models. And the problem is that there are people involved who don’t necessarily appreciate having their data taken away from them.
Charles: Yeah. It’s like somewhat of a dismal empiricism, right, where you’re just like getting a bunch of data, globin it together and seeing what what does that show? And that’s never that’s never really good. We gotta have some some rationality in there. What about and, again, I haven’t worked internally very much at the company.
But my own most of my career. But, you know, there’s things that I’ll any company email that’s a property of the company, basically. Right? So they can scan it and review it. Have you have you had any experience with just professional email surveillance, we’ll call it? And how that goes?
Tara: Well right. Like, my computer has a big sticker on it. It says property of Michigan State University, for example. Right? So they’re fully within the rates to look at what I’m doing, what I’m sending from my company accounts, what files I have stored.
That’s that’s part of my agreement with my employer. And most people have an agreement with their employer that looks something like that whether they know it or not.
Charles: Right.
Tara: The problem is that there’s your real contract, your sort of legal contract, And then there’s your psychological contract, your beliefs, about whether you can trust your employer. And that’s the thing that’s more fragile. So yes, Michigan State has the legal right to go read my emails. But
if I found out that they were doing that for no reason and that they were sort of making judgments about media sign emails, I would feel that my personal boundaries have been violated regardless of whether that’s in my actual contract Right? That is a that is a psychological perception about whether I can trust my employer.
And that’s gonna change my behavior because then now I don’t maybe I don’t do as much sort of organizational citizenship behavior. Right? Maybe I don’t contribute extra ideas. Maybe I don’t go beyond what the stricter requirements of my job are, and you see that kinda contracting. Like, alright.
You have violated your part of the deal, so now I am just going to strictly to the letter of the law of what I have to do and nothing more because that’s the net that’s now the nature of our relationship. So that’s what you tend to see when people feel that that line has been crossed. Now the question of, like, why don’t you cross the line? Is it individual line? So some people don’t care and some people care a lot.
I looked at, you know, potential personality predictors of of who might care. There’s recent and during age effects about who cares more or less. But ultimately, it’s going to depend on their own past experiences, their own understanding of their job and their role, how much autonomy do they expect in this job, And those are just those are gonna be collections of of past experiences and perceptions.
Charles: Yeah. I mean, it a lot of times, this may be a way oversimplification. But, you know, it boils down to the golden rule, you know, treat other people like you would wanna be treated. That’s pretty important. And you hear about things in the workplace where people aren’t treated like people or like others would and it’s always kind of scary.
What do you think in this regard with surveillance, I mean, I feel like it’s only gonna get crazier and crazier. What do you see in the future around this area? And, like, maybe what research would you want to do next in this area? What fascinates you about the future of this?
Tara: Yeah. So in the in the months and years following the onset of pandemic, I think we saw this unbelievable increased explosion in the the market for these technologies. The, you know, the but we’re also seeing a market in technologies that are meant to sort of counteract the surveillance tool. It’s like the best example is a mouse jiggler. Right?
It’s like a thing that will keep your mouse moving to make it look like your computer’s active. You can get ten bucks on Amazon or, you know, you can make it yourself. And so there’s a constant sort of give and take of employers attempting to measure performance of a set of metrics, and then people are reacting to those metrics and and finding ways to exist within them. So I think that that interplay is important to remember. What I would hope is that eventually employers cut on to the fact that the way around it is, like, the way to resolve this is to just measure performance in a way that’s meaningful from the start instead of using these shortcut measures that are easy to check.
That’s takes more effort, though, I understand that. The other thing I would say is that, you know, people, my age, tend to have very different relationships with their employers in that we are more likely to see them as as like an entity that is, you know, I I might trust them. I might trust my manager. I’m sort of it’s almost like a an interpersonal relationship. And what I’m seeing with
younger people is that they’re much more skeptical.
About their employers from the beginning. They’re not willing to just say, like, you have my loyalty until you break it, but rather they’re starting from a sense of, like, you need to earn my loyalty, which is probably the better perspective, frankly.
Charles: Yeah.
Tara: And so they’re they’re much less likely to take the kind of you know, bad treatment that that maybe people my age would have accepted twenty years ago. They are much more likely to see innovations of their privacy, but also this sort of attack on their dignity because that’s really what it is. Right? When you track people this way, you’re you’re taking away their humanity and their dignity, and you’re reducing them to this set of metrics that is just very inhumane. So people nobody likes that.
Right? People are differentially willing to put up with it, but nobody enjoys it. And and what I’m seeing is really inspiring from younger people who are willing to just say, like, No. Thank you. To that kind of treatment.
Charles: Yeah. Things are, I think, in the workplace in general. I mean, if you think about, and I certainly wasn’t around in the fifties or what, It’s always been very hierarchical and very much like you really just respect whatever the company wants to do. You stay in the company a really long time. I feel like you know, we’re getting more individual rights and more degrees of freedom or whatever than than we’ve had.
And then technology is definitely supporting that. And yeah, I haven’t had as much exposure. Right? But what you’re saying is consistent with kind of the things I read as far as, you know, younger generations and what they expect in the workplace. And, you know, that they’re coming in.
That’s gonna be the work. You know, it’s a constant change, a conveyor belt of of new kind of generations coming in to the workforce. Super super interesting. I don’t know. It just comes back to really respecting people and giving them a meaningful opportunity to exchange their effort for, you know, the purpose of the organization and vice versa.
That that’s to me what the psychological contract is. And I feel like if you’re studying work, that’s such a core principle that it’s it’s just really important to, like, build your foundation on understanding how that works and and why it’s a, you know, it’s a true thing. And with the AI stuff, you know, my my experience has been a little bit more. The the surveillance has been on proctoring. Right?
Because I I do a lot in selection. And you know, I just I just looked up because I was doing a presentation on cheating using chatGTP for job applicants, which is a whole another thing. You look at some of the ways people are like, you can have AI proctoring. There’s so many ways to fool it. You can you can put fake browsers up there.
You can there’s all kinds of apps and things that you can do to wear and typically, the cheaters or the people gaming it are usually ahead of the of the people who are trying to mitigate. So it just becomes an arms race that you can’t really win, you know. And in in some situations like proctoring an assessment. I don’t know what other things there are. You can bring somebody in person, you know, or maybe I don’t even know.
But and and chat GDP is really, really kind of raising the the bar for that cat and mouse kind of thing, you know. It’s it’s pretty interesting.
Tara: Yeah. Well, I mean, the same idea about meaningful assessment. Like, the way that we measure people’s skills and knowledge has to change to be more meaningful because an un factored test might not be a meaningful measure of what they know or can do in the same way. So maybe skills assessments are more are more common and the kinds of multiple choice exams that we’re used to seeing go down.
Charles: They will.
Tara: Right? Instead of signs, we see samples of behavior. And it’s not a scalable right now, but maybe your collective creativity, you know, we figure out a way to scale it more. All these AI tools are not just making assessment more challenging. They’re also opening up opportunities for things we haven’t considered before, like, in scoring assessments.
So when I look in the horizon of iosecology, I see the way that we think about assessment just totally differently. And this emphasis on, like, simple measures of constructs that we no matter might not actually work the same way. For example, maybe we come up with problems where if you can solve them using any means at all, including AI, we’re happy. Right? Yeah. You solve the problem. Right? So all we need to actually verify is your identity. That is, I think, more exciting than endlessly trying to figure out ways to make people not cheat on an assessment that’s not that great in the first place.
Charles: Yeah. A million percent. So in that kind of The thing I came away from that presentation that I put together, I came up with this term called AI enabled work ethic. So it’s basically saying, because because job applicants and early career folks, they expect to be able to use generative AI on the job for the most part So if you’re saying don’t use it in the application process, you’re using it kind of for for the same purposes and you’re gonna use it on the job. So Maybe you should be really good at it.
Maybe you should know how to use it to, like, achieve things. Right? And and at the same time, you’re right. I believe the modalities of assessments, like multiple choice, questions, accurate scales, slowly slowly going by the wayside for task based experiential things. Like, I’m a huge believer in simulations.
I’m working on my own work right now. I’m using large language models to role play as simulation people, like, that’s my passion. I don’t see it any other way, honestly. You know, in the future. That that was like my first I remember I showed up at grad school. I don’t know. You may have experienced the same thing. You got like a like a flat that you put a case of beverages in. Right? And it was piled like that high with Zerox’s journal articles, you know, and you had to read a lot of those journal articles.
And my very first class, my first year was selection, and I had one IO class. I I really felt a little lost. I don’t know if other people can can kinda empathize with that or not, but I was like, holy shit. What am I doing? Because we had second, third, and fourth of your people in there. So I was talking to a much higher level than I was used to. And I got used to it, of course. But my paper I had to do was on work samples. And I remember I read this paper, Ashard Skier, you know, nineteen, seventy four, one of the only sites I can actually remember from grad school. But it was about point to point correspondence between the predictor.
Right? The signal and the outcome. So, you know, you give somebody’s got to assemble things in a factory. You give them some bolts and some screws and you tie them and you look at their dexterity, and that’s basically what you’re using on the job. And it made so much sense to me that
through my whole career, I’ve just been waiting until simulations that are customized and stuff can be more accessible because of the technology.
So we’re living a very exciting time from that, and those are much harder to cheat on. Right? I would think, anyway, I mean, I don’t I don’t see how. It’s not the same as being able to look stuff up. So
Tara: Well, I mean, again, I’d say that part of what you’re measuring is Hivo’s ability to use all available resources to solve the problem. And so in the work environment, if you’re the kind of person who can marshal a bunch of external people to give you advice to solve a really difficult
interpersonal problem, like, great. Do that. That’s that kind of resourcefulness and creativity is job relevant information. Right?
We wanna know what that is. And sort of tying people’s hands and say, well, for the purposes of assessment, you can’t use all these things that you would definitely use later. I don’t I think that logic is starting to break down a little bit.
Charles: Yeah. I totally agree. We’re, you know, we’re entering into exciting and crazy new times. I keep saying that, but that’s the life I’m living in all the time is just, wow, this is blowing my mind. So very cool.
So what about a wave lab? I’ve I’ve seen some stuff and some of the I think surveillance stuff was done there. And I think Richard is Richard Landers involved in that with you as well?
Tara: No. So the Wave Lab is my group of graduate students and undergraduates. And occasionally postdocs or visiting researchers. And we’re spread across four different universities right now, but the common thread that they have is that they are people who’s research, I’m advising in some way or another. So the kinds of things we work on tend to evolve based on the interest of the group.
And what I like to do is have a few projects that are going on in a given time that are sort of bigger that everyone’s contributing their ideas to. And then people have smaller projects that they might be leading and sort of developing their skills in different ways. And it’s a place to just how fun conversations about all these exciting changes that we’re talking about. Right? It’s a place to say, like, did you read this article?
And can you believe? And, like, what are the potential research implications here? So it’s a very important, let’s say, central part of what makes my job fun, and it’s it’s something that I would not be as excited about my job if I didn’t have the voice lab. The folks I know who mostly do research on their own, I think don’t get the kind of enjoyment. Out of it than I do. So that said though, I have outside of collaborations also with lots of researchers. I mean, you mentioned Richard. You know, I’ve written a bunch of papers together and actually we just finished writing a book together, which is something we’re both really really excited about. It’s not a how to book. It’s more like a why book.
So why do we do research? What are the decisions that we make? And what are the implications of those decisions in terms of how the how the research ends up being useful in the world or or limited? And how can we sort of think through the process of of becoming a researcher a long way. And so the the book is sort of organized.
And first, you think about, like, your identity. Who are you as a researcher? And then how do you choose the research questions that you wanna work on? And then from there, we sort of talk about various specific tactics and approaches and why you might choose one over another. But
we’re really, really excited about that book, and it’s it’s coming out any second now, actually. I think it’s available for preorder as of yesterday. Oh, we’re
Charles: tell us the name and stuff. You gotta promote it. Promote it. Promote it. Please. Because people need to read it.
Tara: So the book is called the research methods our national organizational psychology, science, and practice, which is definitely a mouthful. And I think if you go to my LinkedIn or Richard’s LinkedIn, we have a link for a preorder, but it’s again, it’s it’s something that that I hope people will use in courses or just for their own leisure readings or reflect on these choices, like, why did you choose that research question that you study? Like, what you know, why not some other research question? What are the what are the real implications in terms of ethical consequences for the kinds of situations you might find yourself in? And how do you share the research knowledge that you generate in a in a responsible and ethical way. So it’s those kinds of questions that we tackle, and I I think it’s it’s a lot of fun. I put all my dorkiest stories in there too. So I really look out for this.
Charles: Okay. Well, tell us, give us a preview of one of your dorkiest stories. I gotta hear it.
Tara: And I’m sort of afraid to go away, but I frequently use the cocktail party metaphor to explain how how a person should enter a research field. So maybe you’ve heard this. I did not invent it for sure, but I’ve who perfected it. The idea is that, you know, when you go to cocktail party, let’s imagine that you’re in the car on the way over and you hear really cool NPR story about Bs and you’re like, oh, Bs, that’s so interesting. I can’t wait to get to the party and tell a word about Bs.
And you get there and you get to the party and there are people standing around in groups of three or five and, you know, how people do it parties. You can’t just stay in the middle of the room and start screaming about b’s because that’s you won’t get invited to more parties after that. Right? That’s not right. What you actually do is you approach one of the groups. You listen first. Right? You first listen to what they’re saying. And then maybe they’re talking about climate change and you can contribute something to say, like, well, here’s how bees, you know, relate climate change. Here’s how they’ll be affected by climate change. But you have to first listen to what they’re talking about and make sure that you’re meaningfully adding to the conversation, not just changing the subject to what you wanna talk about. And that’s how research works. Right? When you are writing a research paper, you are entering into a conversation with your peers. And so you first need to let us know what they’re talking about. And then second, figure out how you can meaningfully advance that conversation. And I found that analogy just works incredibly well and people are sort of stuck about, you know, what to write about or who like, how to frame it. When you frame it in terms of this is a conversation, and the scientific field is having lots of conversations at any given moment, and you need to pick one and contribute to it. That sort of changes everything.
Charles: Yeah. And something that you’re passionate about. I feel like that’s also a good a good guide. So at a cocktail party, what cocktail are you ordering?
Tara: It depends on my mood. I I’m actually a pretty big fan of cocktails, and so I I I like to make different classic cocktails depending on the occasion, so I I can never pick a favorite. That’s impossible.
Charles: Gotcha. Okay.
Tara: But I like the classics. Let’s get that.
Charles: Just gotta name one. I got gotta name one. It doesn’t even have to be your favorite. What’s one that you like to make the most? Or free association.
When I said that, did a particular cocktail pop into your mind?
Tara: Like, it’s one would be a Gibson, which is very similar to Martini, but with an onion instead of an olive. And then the other would be sort of any variation on Manhattan. So sort of playing around with ratios and different Amaros. To make them appropriate for the occasion. Those would be my two main boat shoes.
Charles: Gotcha. So next year, Saip’s in New Orleans, and you can come down here, you can go to Gal to us to get a French seventy five or you could get a SASRAC, two really great
Tara: things. When I’m in New Orleans, my first stop is at cure. Actually, cure is one of the best cocktail bars in the world. So I’ll drink whatever they’re pouring there.
Charles: Yeah. Yeah. Yeah. We know the guy that owns that. Yeah.
He had some other stuff too. Both my in laws are in the beverage, alcoholic beverage. Industry down here. So we get a lot of yeah. A lot of fun with that.
So you’ll be able to do that next year. That’s awesome.
Tara: Cool. Like, come in and runs a lot. So Oh, yeah. Let me call you next time. Awesome. Mhmm.
Charles: Cool. So, NSA, tell us a little bit about that, that National Science Association. What is it? Like, I should know what it stands.
Tara: No. I’m NSF. National Science Foundation.
Charles: NSF. Well, no. I have a typo on my notes. Yeah.
Tara: And this day is a different organization that I even if I did work there, I couldn’t tell you about it.
Charles: But the Yeah. The National Science Foundation. I know what it is. Good. Tell us about it.
What do you do in there? That’s amazing that you had a chance to be part of that.
Tara: Yeah. It was a really terrific learning experience. So I was there for a total of about two and a half years wrapped up last spring. The role I had was program director. So what that means is that I have a program that is sort of mine to oversee.
I received the applications, make funding decisions, and sort of work with researchers to shape their ideas and get them in the best possible shape for funding. So it’s just this totally unique opportunity to get a sense of whole field? Like, what are people’s cutting edge ideas? And not just from psychology either, but from all across the social sciences, to just think about, like, what is the state of of research in organizations? So I learned so much and got to meet so many interesting people.
And then the other thing that I did there in addition to managing my program was participate in a cross agency sort of working group related to the future of work. And so I was able to sort of share that group for a year. And I I see my main contribution there. I was helping people understand the contribution of the social sciences in this conversation. Right, that otherwise might be dominated by AI people and technologists and engineers to say, like, this is what we gain in when we have a really solid understanding of human beings and systems and and how it can just really save a lot of wasted effort for saving the wrong kinds of questions or give a new level of understanding to what we’re seeing.
And and I I would say I was pretty successful, so I was very proud of that in shaping achieving people’s perspectives. Now what came out of that is a an edited bug that should be out in about six months ish. Club the future of human technology partnerships that work. And the point of that book is to make the argument that when we talk about humans and technology working as teams and organizations, really I mean, there’s a lot to say, obviously, but there’s not much to say that applies to every kind of human machine team. Right?
Like, these teams are actually highly contextualized depending on the kind of work. And the kind of work curve. So every part of the book takes, like, a specific deep dive on one kind of work. Nursing, hospitality, oil and gas, construction, lawyers. Right?
Like, what it look what it means to work with technology in each of those contexts is so so different. So the bug is meant to show that.
Charles: What was did you have a particular location or part technology human partnership that you focused on within that book or within that context?
Tara: No. So the book tries to be as broad as possible, and then so each chapter has a different job focus and the authors of the chapters are people who are experts in those domains. So I don’t you know, I’m not an expert in those domains, the people who are contributing the work. And then the other section of the book is sort of integrated themes, things like lifelong learning, which is just showing to be such an important element of every kind of job.
Charles: Yep.
Tara: Or access to work for people with either disabilities or other challenges that make access to work difficult, like, even something like child care availability. Right? So the chapter talks about those kinds of things.
Charles: Cool. So overall, I guess, you know, what came out of that whole experience that you feel like is gonna have the most practical impact on things in our world. You know, I’ve said a lot of smart people studying different things thinking about technology sponsored by, you know, the government. Like, it’s a big deal. So what practical that we might see in the future is a result of, you know, the foundation in general and the, you know, the work that you were part of.
Tara: Yeah. So the thing cool about NSF is that they post all of the funded projects on our website, and you can go see what they are. Because the philosophy is that this is a this is a federal government agency, which means that it’s meant to serve the common good. Right? Like, they’re not keeping things secret here.
So all of the results from NSF funded research are available to the public. I mean, you can you can access them as a as your right as someone who lives in the United States and supports the National Science Foundation with your tax money. Right? So a lot of these projects lead to research insights. Many of them lead to new technologies that are developed that, you know, affect our everyday life.
In the future of work program of the the proposals were mostly about building new technologies to solve work problems. Like, make a robot that picks fruit or clean salmon or whatever. But, like, those products will enter the market eventually because of the innovation that’s happening in these research teams. So so if you’re curious about that, then I think it’s fun to just spend a rainy afternoon reading the NSF website because they do a great job showing about, like, new products, new patents, and things that come out of the money that they spend.
Charles: Yeah. And we’re in a crazy, exciting time for innovation and new things. We’re just evolving every field, you know, with with access to technology and not just large language models, such as the technology we all seem to talk about now because it’s sedan, interesting. So cool. Well, let’s wrap it up here.
What is your take? Just think about the workplace ten years from now, twenty, thirty four. What do you think is gonna be like? What are what are maybe some of the differences between what we have now. I don’t know.
Just just free association, like, if you had to picture it or visualize it, what do you think is gonna be going on?
Tara: Yeah. I think right now we have a situation where work is changing really quickly, obviously. And there’s also these huge gaps between there are job seekers who have skills and there are employers who want those exact skills and somehow they can’t find each other. There are there are kinds of jobs that are incredibly difficult to fill where they’re where we’re predicting huge shortages. Right?
Like, aviation Yeah. Plumbing, air traffic control. Right? That we’re not gonna have people to do those jobs, which means that we have to really change the way we think about training and education. To sort of better align with the needs that we have.
So what I see happening is a different kind of emphasis in k twelve and in college about the world that you’re entering and the kinds of skills you might need to enter that world and and more focus on the kinds of things that machines can’t do. Yeah. So I think that’ll be a really exciting time. And there are plenty of things that machines can’t do, by the way, that they probably will never be able to do. So what I see is a sort of re emphasis on on those things and better alignment with the job market that we actually have in front of us.
Charles: Yeah. I I would agree. I don’t think that I don’t think machines are coming for everybody’s jobs. I think, you know, you kinda re purpose, what you’re really good at, even from an individual differences standpoint. Right?
There’s there’s certain things that a machine can take away a layer of stuff that you might not been as have been as good at or it might have been boring work, and then you can partner with
that. Machine to to be better, you know, to be a hole is greater than the sum of its parts. I would I would think. And I don’t know it’s buy into the whole, you know, everybody’s jobs are gonna be gone and what’s gonna happen and then, you know, people will be wandering around like zombies needing to be subsidized by the government because there won’t be any work. I mean, you you know, I’ve read some books that kinda go that go that far right with it, but I don’t really believe that either.
And and people, you know, we need work just like work needs us and I feel like we’re always gonna find our way to to doing something meaningful. Hopefully, if you’re in touch with that as an individual, you know, and and are able to to be cognizant of the fact that that’s that’s what you need to do. Right? I mean, we’ve all had jobs that we don’t like for whatever reasons at some point. But those those serve as sterling examples of why you do.
Do you wanna get something you do like? So I think it’s gonna be an interesting an interesting ride. I think it’ll look more different ten years ahead than it did ten years backward. Right? Which is twenty fourteen.
Yeah. I guess, you know, we were talking that was right when everybody started talking about big data. Remember that Saip in Hawaii, one of my favorite Saip’s because I love Hawaii. You know, that was all big data. I think I was on three different things.
Three different panels about big data, big data, big data. Now all data is big data. Right? I mean, almost. It’s like there’s so much of it.
Tara: Ten years ago, people were also saying that within ten years, seventy percent of jobs we automated, which obviously did not happen, which is why shouldn’t always listen to people who think that they can predict the future. But I believe fundamentally that work is about solving problems. And innovation comes with new problems. There are different problems than we had before. Right?
But we still have problems to solve. We will still, like you said, need to drive meaning from our lives. And maybe that doesn’t look like paid work in the same way. Maybe we don’t have RDR work week because it’s not actually necessary because we can reorganize ourselves in different ways. But the kinds of work that right now go unvalued.
Like, CareWork is a good example of that. Right? Maybe we reorganized around around those kinds of things about contributing to our communities and taking care of each other. So so we will figure it out because we always do. There’s no doubt about that.
But I think ultimately, we do need to be a bit open minded and the idea that you could just sort of expect the world to compensate you because it changed is not reasonable, and it it just never has been reasonable.
Charles: Yeah. Yeah. I completely agree. Well, thank you so much. It’s really, really good conversation.
Got a lot of wisdom and a lot of experience looking at things from a very, I’d say, legitimate, methodological standpoint, if that makes any sense. Right? Like like that structure of research, I think a lot of times we we consume research and it’s not always really that well done. I mean, people throw numbers and studies out there all the time and you you gotta be a little discerning. So it’s great to see quality practical stuff and appreciate so much your time today, and look forward to seeing you at sign up.
Tara: Thanks. This is a really fun conversation. And and, yeah, I’m looking forward to seeing you seen at Syrah.
Charles: Cheers.