S1E6: Navigating the Future of Technology as the Future of IOP ft. Hendrik Bronkhorst

Navigating the Future of Technology as the Future of IOP | The IOP Lens

In this episode of The IOP Lens, host Dexter Nyamutumbu is joined by Hendrik Bronkhorst for a forward-thinking conversation on the intersection of technology and Industrial and Organisational Psychology.

Framed as Navigating the Future of Technology, the discussion explores how digital transformation, data, and emerging technologies are reshaping the role of IOP practitioners. Hendrik shares insights on staying relevant in a tech-driven landscape, embracing innovation, and positioning IOP at the forefront of organisational change.

This episode challenges practitioners to lean into technology as a key enabler of impact and future-ready practice.

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Transcript

SPEAKER_00 0:21

Welcome to the IOP Lens Podcast, where we speak to real people about real journeys. This podcast is about the stories that shape us and who we become as professionals. And today's episode is a very special episode because we are speaking to a very hot topic, which has been in the industry for quite a number of years. It's about AI, you know, the fourth industrial revolution and how technology is impacting us within our professional spaces. And today I'm joined by a very special guest, one of the big guns in industry, Hendrik himself. Um he's going to be speaking to us and sharing some tips, some resources about navigating technology and AI within the profession. Welcome, Hendrik. How are you doing today?

SPEAKER_01 1:03

Finding you, Dexter. Thank you very much.

SPEAKER_00 1:06

It's a pleasure to have you here. So before we get into the topic and actually discuss AI, we want to understand what is your story within industrial psychology because this is a podcast for industrial psychologists. So we want to understand who you are and what's been your journey within industrial psychology.

SPEAKER_01 1:22

Dexter, you're taking me back many years now. I actually started off not studying industrial psychology, a broader BCOM degree, and in my third year realized that there was a bug that bit me.

SPEAKER_00 1:35

Okay.

SPEAKER_01 1:36

And um from there transitioned into IO psychology, honors, masters, internship at one of the big banks, and that was very fortunate. Then started with Eveleks and um almost grew up with a business and played various roles within it, from um helping develop, helping grow product development, IT research, and today I'm very fortunate to get up a group of very talented individuals that's that try and make a difference.

SPEAKER_00 2:08

So important luck you guys are doing. So what's kept you in this industry? Because, like you're saying, a but a bug bit you, but what bug was that and how have you stayed in the industry?

SPEAKER_01 2:19

I think the behavioral sciences is what bit me and uh observing people. What's kept me in the industry is the breadth of it and the roles you can play within IO psychology. But I think most importantly is we we're very fortunate as iopsychologists to play a part at an individual level and make a difference for individuals and their lives and their families. We play a part at an organizational level, which um helps organizations become more effective, add more value. And then lastly, we also play a part at a societal level. Uh all these things have a ripple effect, and and the advice we give and the situations we get into and the lives we change, they ripple outwards positively, and that intersection between those three person, the organization, and society, um, that's exciting.

SPEAKER_00 3:17

So and what part of the journey has been the most memorable for you? Because, like you're saying, there's many aspects and many lives that we touch, but for you as Hendrik, what's been the most memorable part of your journey so far?

SPEAKER_01 3:29

It it maybe ties back to us as a business. The memorable parts are the transition points of technology. Originally, our business is uh strongly focused on assessment, so moving from paper and pencil-based assessments to a system, and then Y2K in the 2000s, some of us weren't even born yet. And there was um a big transition point there. And then around the the two 2010s, there was a movement, and especially in the world of simulations, toward online simulations, and now we've got the transition into AI, and each one brings nuances, and to a large degree they're very similar, to a large degree they're very different. And so those are the exciting ones.

SPEAKER_00 4:16

And also is that navigating that change, you know, navigating what the future is actually going to look like and trying to prepare for that. All right, so on that, let's speak to the day-to-day then. What does the day-to-day um look like when we have incorporated AI, data, and technology within our spaces as IOPs? I think it's shifting.

SPEAKER_01 4:36

Um, well, it's always been shifting, but I I don't think it's shifting in the sense that we're moving away from not really how we do things is different, um, but the way in which we add value is slightly different. And if we maybe take some areas of IO psychology and use some form of a taxonomy, um, let's take the world of organizational development and maybe things like climate and culture and engagement. There's a shift there from traditional survey-based types of information gathering to micro-behavioral information gathering, where you can see how people interact in meetings, in their emails, in their discussions, what they do in their LinkedIn profiles. And so the ability to gather sentiment and engagement is moving away from just a survey. And then, of course, there's the analysis of them. Then you take areas such as um work design, where you need to look at all organizational design and job specifications and grading. And there we have AI that helps us with the content in development and learning. Um, there are so many apps and solutions now that help us identify skills and competencies and map them and suggest learning interventions, and there are coaching apps and there are diagnostic types of AI that help us. And then I'm sure we're going to speak a little bit about recruitment and selection later on. Then you get um areas such as research, where research is fundamentally changed by the way in which we um how AI changes us, and uh there's a there's a fascinating um um uh platform, Edison is its name. And I played around it with the other day, and it's a platform that's really built for research in the bio and medical field, um, but we played around with it to see what it can do with iopsychology. And I mean, literature reviews traditionally took you a very long time, just finding sources. And most of us as iopsychologists needed to do a literature review at some stage, it takes weeks. And here, within a couple of minutes, literature is synthesized, brought together, hypothesis formed, answers um put in place. But I think the a fundamental place where where AI is really helping us as I psychologists is just content development. Whether you're a young IOP who wants to start their own practice and needs to put together a brochure, brochure, a um uh proposal for a client, whether it is you need to develop competence definitions, whether you need to um analyze a set of data, it just speeds up and augments what we normally do immensely.

SPEAKER_00 7:20

That's true. And speaking, you mentioned something that I also encountered recently. So I was doing a sort HR data analytics course, and I didn't know there's so many touch points of data within the organization. Like you mentioned, the email. I never thought we could get information from emails about engagement, about people's sentiments about the company, because traditionally we think servers are the way to go, servers, interviews, focus groups, but now looking at things like emails, things like what's happening in the coffee room, you know, that things of that nature are proven of so much value, and often in the past that went unnoticed. So now I'm just thinking now, and this is my next question to you is for you within the various spaces that we address as IOPs, and like you mentioned already, there's grim selection, there's development, there's org design. To you, which aspect has adopted AI the most, or have we as Iops adopted AI the best? Um, and to what extent are we making use of it? That's a difficult question.

SPEAKER_01 8:23

Each of those fields where we'd looked at so the organizational development, organizational divine, they've all got their elements. I think the places where it's probably played the most part is synthesizing of a lot of data. Um analyzing that data. You spoke about sentiment. I mean the sentiment analysis is now an easy thing to do. Uh so I think it plays, I don't I wouldn't say there's a place where it plays the larger or bigger part. I think it's playing a part everywhere.

SPEAKER_00 8:56

Oh, interesting. And I I've seen that play out in so many spaces because I think that's why we're seeing so many consulting firms. You you see in the past a consulting firm startup and then focus on something like recruitment and selection, and that'd be their niche for the longest time. But now they're able to expand because they realize that there's actually so many sorts of data, even within that recruitment and selection, that feed into other processes as well. Um, but on the topic of recruitment and selection, so we are seeing AI being incorporated big time within that space because, especially in a in a country like South Africa, where you're getting thousands of applications from people, you need something that's going to help you filter out and sift out the best candidates quickly. So, what does that currently look like in terms of what does AI look like in the recruitment and selection process?

SPEAKER_01 9:43

So at the moment, there's a strong focus on the early recruitment stage, especially in the high volume. Um, as you'd mentioned rightly, that is where you have your your many applications for one person. So you're seeking some consistency. So that's where it's starting. I think it will spill over later into the value chain and more into to maybe more senior types of hires in recruitment as well. It also brings with it its own oversight challenges. Um so why why would we use it? Why would we use AI in in recruitment generally? And I think there's a there's a speed element to it. Um a lot of our clients these days speak about time to insight. How quickly can you get data from an assessment into I've got an answer? And then you've got then you've got um cost is being reduced significantly, especially human capital cost. Think about if you need to do a thousand interviews. How are you gonna manage that with line managers and HR people? And you've got consistency gains sitting there as well. So AI is really helping us revolutionize that space in dealing with volume quickly, effectively, and efficiently.

SPEAKER_00 11:03

And I think it's so easy to fall into that trap that AI is really good, it's this good, you know, revolution, like we're speaking to. There are so many benefits to AI helping us speed up processes, make decisions, make better decisions, and make them quicker as well. But what about AI should we be cautious of, especially as industrial psychologists?

SPEAKER_01 11:22

Yeah, it's uh it's almost like a child playing with a new toy, and you don't really know, you don't really know what you're playing with, is it? Um, I think a couple of things, because to a large degree, we as I psychologists must suggest and look for and decide on applications and technology that might work, and people are going to lean on us to offer those opinions. Uh one or two things that one we need to look at is is what is the training data that the AI is trained on. So that old saying of rubbish in, rubbish out. And um, we're all familiar with uh the Google CV screening mechanism that that failed. There was they introduced bias. So that's something we need to consider. We need to consider the black box and the explainability of the AI. That's very important. You need to be able to say, from the point that I enter data at this point to something comes out at the other end. Can I explain that process? Now that's difficult, it's proving more and more difficult because the developers of AI methodologies that's their IP, that's their livelihood, that's what they're selling. So they're not very open to revealing that. Um, but one needs to look up for at least some sense of link between the input and the output. What worries me, especially for younger psychologists, is over-automation of decision making. We often, and let's call it algorithm algorithmic decision making. Now, don't get me wrong, algorithmic decision making is good. Um, it reduces bias, it increases efficiency, it increases reliability to a large degree can increase validity as well. But if the young psychologist or the line manager doesn't know what the number or the score at the end is made up of, they can't explain it. And there's two pieces to that. If you don't know what's in it, you don't know what's not in it, you don't know really what it's about. And then secondly, as young psychologists, one needs to fundamentally understand the that which you are dealing with. And if we start putting algorithmic decision making in, we forget what that that secret source is. And then lastly, maybe uh maybe two last things on this point is um know what the AI is actually doing because they're all designed to do solve different problems, and some of them are designed just to automate a process, some of them are designed to gather data, some need to sort, classify, match, some need to diagnose, some need to analyze, and then some need to predict and know what it is doing because on there's a that on that continuum, there's a degree of AI-ness, if I can call it that, that we need to understand. And then the last thing is this introduces a fundamental rethink of what we view as ethical and what we view as legal, and what we view as good and wholesome. And we need to keep an eye on that on that.

SPEAKER_00 14:26

And I think you touched on so many important points because um currently I was watching the news recently, there's this whole conversation about around how do we make legislation that speaks to AI? Because the conversation is currently there is no legislature or um laws around AI, and to what extent can AI be incorporated? What are the limitations for AI? And this is a global conversation that is happening, and how much more so within our space, as oftentimes as industrial ecologists, we are the ethical spokesperson. We're thinking of ethics, like you said, processes to ensure do I understand this process from start to finish? Am I able to defend in a country like South Africa, where we're highly legislative, there's so much constitution that we have to be cognizant of. If a candidate from uh the recruitment process comes in and says, I feel that your process was unfair, and I, as industrial colleges, I incorporate AI, I'm able to defend my process, even though I don't know what was happening in that space. So it's it's very important for us to be mindful of that. And this might be a difficult question for you to answer, but how do we navigate that? Understanding that it's not as legislated, the AI space is not as legislated as you know your selection processes. There's no BCEA version for AI. So, how do we navigate that to ensure that we are still ethical in our processes and still making the best use of AI?

SPEAKER_01 15:52

Look, luckily in our fields, we've got decades, and some might argue even close to a century of what good looks like. We know what it is, the principles are still there. I mean, we've got so many professional bodies, whether Bouakbi uh SAOPSA here in South Africa, SAOP in the in the US, whether it's the Association of Test Publishers, whether it is um uh uh uh the International Test Commission. All these bodies are very active in defining we know what good looks like. Now it's defining what good looks like in the new AI world. We have luckily some legal frameworks on their way. I mean, the EU Act is is busy being implemented at the moment in the EU, and that guides our principles. And then and then you've got certification bodies that can give a stamp of approval as to whether the AI we use and the way that we do it is done at a particular standard with a level of effectiveness and efficiency and what it promises to do in a good way. So they are. We have them, they're slow to catch up, but they're there.

SPEAKER_00 17:04

It speaks to a conversation I remember having with a previous president of Saiyobs a couple years ago, because as a young emerging psychologist, I was of the perception that within our space we're always reactive, we're always reacting to what is happening in industry. And my challenge to the then president was how do we become proactive? We're not waiting for legislation to catch up. How do we now influence and impact those spaces before they influence us instead? Um, so I think it's a conversation that's still ongoing, like you said. Is that happening in the EU, the societies we're in, the bodies that we're in? So I think it's an ongoing conversation we're having. Um, I want to uh speak to now the young emerging psychologist, going back to the young emerging psychologist, how can they make the best use of AI? Um, especially as they're still navigating these early careers, they're still navigating, figuring themselves out what this process looks like, what this journey looks like. How do I, as an emerging psychologist, make the best use of AI currently?

SPEAKER_01 18:06

I think it starts almost before we get to AI. There's there's a set of skill sets that young psychologists should espouse to to build. Um data literacy is is absolutely critical. You need to know how data works and how to work with it. You need to understand some level of statistical research type of knowledge. Um we need to understand ethical judgment, we still need to understand how we collaborate with other people outside of our fraternity. We still need to be able to communicate and influence. So those are the core capabilities that we've always needed that won't get enhanced now. But if I consider what I would suggest for a young psychologist is uh maybe two or three things. And the first one is comfort with technology. Um I observe often in my house, my family, in our business, when something goes wrong with a computer, the hands go up and what did the computer do? It's broken, it doesn't work. Nine out of ten times it's the user of the computer that did something. Consider for a second if something goes wrong with your technology, are you calling tech support? Can you figure it out yourself? Consider for a second have you taken an Excel spreadsheet and used it beyond just basic formulas and looking at data? Ask yourself, um, do I use chat or any one of the platforms for like Google? And if you fall into that category, then you need to say, well, that's the start. You need some level of comfort with technology. Then as a next phase, I'd probably really be curious. Now, when we look at curiosity, often we think about curiosity about I need to gather the information, I need to go and find it, I need to listen, I need to learn. And so if somebody says, Well, you need to do something with the gentic AI, we'll say, Well, let me go and watch a YouTube video. Maybe I can go into a course. Now that's the sourcing side of curiosity, but I want to challenge us as young IOPs, you need to move into the next phase of curiosity, which is the creative side of curiosity. Okay. Which is rather than saying, What does a Gentec AI do? say to yourself, let me try and build an Agentic app. Let me play around with it, let me see what it does, let me fail. So that's the second thing, curiosity. And then thirdly, is in the realm of collaboration, we we tend to stick to our type. So we're behavioral scientists, so we stick to the people types of people, we stick to the creative types of people. And I think we need to be brave enough to move into the realm of the not so similar to me, the highly analytical thinker, the black and white thinker, the really logical person, the person that's testing your assumptions, the product developer, the business analyst, the business owner. You need to live in their world before they allow you to give advice on their world. And so those are the three I'd probably highlight as Mark.

SPEAKER_00 21:41

So what I'm hearing is first, you need to start with from within. So me as the emerging psychologist, I need to look at myself saying what skills am I lacking? What within my space do I need to grow in and make an effort towards that? With the example you gave, I could relate to it so much because I've been in spaces where I think. What I was doing was so I did CAD, so CAD is computer application technology, like in high school, and then I did some IT course also during my varsity day. So what I thought was basic technology understanding and know-how, once I was in certain spaces, I would do something to me that was so simple, but then everyone else was like, wow, how did you do that? And that's simply because, like you're saying, it's those other courses and how I've gained knowledge elsewhere and not stuck strictly to the behavioral sciences space and gone elsewhere. And I think the other part I'm hearing is networking, um, but also internal within your company because the main stakeholders, if you are employed, are those people that you engage with on a day-to-day. Um, I was engaging with a friend just the other day and we're speaking of how within her space, she is basically the people partner for different departments, so for your finance, your legal team, within the big corporate space. And you can't speak their language if you're not in their space. So, in as much as you are the behavioral scientist, they trust your opinion regarding psychology. But once you're stepping into that space, you need to understand what's happening there and for you to actually be able to make an impact. Um, so yeah, I'm I'm I'm in full agreement with what you're saying, and I've seen it play out as well within the various spaces. So, in terms of that networking, I'm gonna plug Sayopsa just a bit. So, in terms of networking, what opportunities would you advise young emerging psychologists to take advantage of so that they grow their networks and they're able to speak different languages to different stakeholders?

SPEAKER_01 23:32

Well, I mean, at a practical level, I mean CEOPSA gives a platform for young psychologists to meet each other, and the conferences are a good place and any other uh events that we have, but there are other there are other bodies that bring people together that are like-minded in their nature. Um maybe it's less about the activity of going to build the network, and to me it's more about leaning into the value that you can add to the network side rather than asking the question, what can the network give to user? And if we look at networking maybe in your broader business and not necessarily just in IO psychologists, often we think about a network as what can I gain from the network? That's usually a starting point. The question should rather be, what value can I add to the network? I think you make that shift, you start adding value. If you get adding value, you're gaining trust. If you're gaining trust, you can make a difference.

SPEAKER_00 24:39

And that's what we are about as a psychologist, we want to make a difference. Like you said, starting from the onset, we speak to many three aspects of life within the organization and also society at large. So we speak to the individual, we speak to the group of the team, speak to the organization, but as a broader responsibility, we also speak to the general society. And exactly like what you're saying, that's the best way we can make an impact even within those spaces. So we've spoken to the emerging psychologists. Now I wanted to shift slightly to now the more established industry psychologists. Um, speaking to how can they make an impact and be influential across their company, for example, within different departments at a more strategic level. So not just looking at the various spaces that they're in. For example, if I'm stationed in recruitment and selection, it's easy for me to just simply focus on that recruitment and selection and just be getting people into the company. But now, how do I, as an industricologist, regardless of what space I'm in, get a seat at the strategic table, especially with regards to AI and technology and to actually have a voice, not just a seat, but also have a voice and make an impact, like you said, within that space?

SPEAKER_01 25:47

I don't think it's fundamentally different from the other things that we've mentioned. But I if I were to if we were to say, How do I get a seat at the table? Well, you earn the seat at the table. And how do you earn the seat at the table is you uh add value. And how do you add value? Well, you make a positive impact on people's lives. You maybe uh give them something they didn't know or need. Um but in organizations it's about information. I the big part of us as Iopsychologists is advisory in nature. We advise and give opinion towards a particular problem. Now, traditionally, that advice has been more on the theoretical, humanistic side of the world. More and more, their advice is the interpretation of data. So moving towards that data world is, I think, well, critically important to be invited to the table. Otherwise, you're gonna have a seat, but they don't really want to listen to you.

SPEAKER_00 26:54

Like, yeah, because you might be in there, but then I actually having a voice in that space. So making an impact is very important. So we've spoken to what the past looked like briefly in terms of coming from paper and pencil, we've spoken to the different stages and transitions we've seen, um, and we've spoken to where we currently are now and what skills we need to have to be able to make an impact within the current climate. Looking ahead into the future, what do we need to equip ourselves with and how do we prepare ourselves as in just a college generally for the future working world?

SPEAKER_01 27:30

If I can maybe expand there, we've spoken a little bit about some of the capabilities and maybe we'll speak about the roles as well. Equipping yourself in this, can I call it data-rich world means that we're gonna almost need to reskill ourselves in understanding the methods we've always used. So if we think about research and data analytics, there you might say to yourself, okay, well, I know what the reliability is, and I know about validity, and I know about um causality, and I might even know what a regression analysis is. And so it's not good enough anymore. You need to lean into new concepts. I mean what on earth is hugging face and what does it do? And um what is gradient boosting and a rock curve and random forests, F-scores, and accuracy, and so forth. So we need to lean into the world of understanding different concepts and themes. Um then I think we need to shift away from individual level or the focus on individual level decision making, more at a group, organizational, cultural level of insight and understanding. But what is very important is we we sometimes get so stuck on a theory we don't know how to translate that theory into practical action. We know the why, but we don't often think about the what. Business likes the the what answer. And um and then lastly, um AI at its fundamental core is about prediction. Everything that AI does is predicting to a degree of certainty what is gonna happen next. And if we want to predict in the human behavior environment, we need to figure out what we're predicting. And then we need to understand how to measure that. Otherwise, the AI we build is not gonna measure the thing we're trying to measure. So I think the the advice for any IO psychologist is lean into a world that's unfamiliar rather than trying to defend the world that is familiar.

SPEAKER_00 29:56

So that's so important because I've already seen that in various spaces where because you studied something or because you're in an industry, you become so hyper-focused on implementing what you already know instead of looking for new advancements, like you're saying, expanding your knowledge base even on the foundation that you already have instead of just sticking with that foundation. As we wrap up, what is the one thing you would like people to remember from our conversation today?

SPEAKER_01 30:26

Oh, one thing's difficult, Texta. I can give you three, it's way okay. I think we lean in to different fields rather than out. Um data slash technology slash method slash statistics, they all kind of go go together. There's a there's a world that we need to understand in the numbers. And don't forget that. Number three, we are essentially a little bit of the moral compass for moral compass for the organization. We are the ones that need to take accountability for the decisions we make. We are the ones that need to educate business on the decisions they make and the effect that that will be over on the decisions that we'll make later. We are the ones that should when they ask, when they say, can we do this, we need to be the ones that are asking, should we do this. And this is a difficult tension we need to do. On the one hand, we want to lean into the world and enable, and on the other hand, we want to protect and guide. It's almost like being a parent. And there's this tension between those two. And I think we can only do this if we start planting our fields and not our fields, our feet, um in two worlds. Have you ever seen these pictures usually from Europe, people on holiday, and then they've got their one foot in a country and their other foot in a different country. Maybe there's a road or a line or something. And I think our one foot is firmly planted in the humanistic side, and our other foot is just touching on the technology side. And until we probably lean into that and understand that we're probably not gonna make so much of a difference.

SPEAKER_00 32:37

So and the best way to make a difference is to have your feet firmly planted in both worlds. Both worlds. So that's very powerful. Thank you for that. Pleasure. So those are words from the Waz, and that is how we wrap up our episodes regarding navigating the future of technology as the future of IOP. Thank you for joining us for the IOP Lens podcast with my guest, Hendrik Bronkhurst. This has been the conversation around navigating the future of technology as the future of IOP. Feel free to follow us on our social media platforms. The link is in the description below. And until next time, this has been the IUP Lens Podcast.