Transforming Education with AI and Virtual Reality with Labster’s Bjørn Toft Madsen

Hi everyone, it's Alan Shimmel here for Tech Drunk tv. My next guest is Bjorn Toft. Matson Bjorn is Chief Product and Technology Officer at Lobster.

It's okay if you don't know about Lobster, 'cause you will after this. Let me bring Bjorn on and we'll get right to it. Bjorn, welcome to Tech Drunk tv.

It's great to have you on. Thank you for having me, Alan. I'm really excited to be here.

I'm excited to have you on. Um, Biard we're gonna talk about Napster, but before we do, I mentioned you were basically your C-P-O-C-T-O. That's a, that's a pattern I see a lot lately.

Yeah, lately, earlier in my career, not so much. Right. The Chief CTOs were very different than CPOs.

Right. Was more likely that my CT o was a VP of engineering, maybe, or heading development, not, that's not product. But give us a little bit of your background and how you came up to have these dual roles.

Yeah, certainly. Yeah. So my, my background is in games.

I started in, in low level engineering, uh, you know, doing memory managers and graphics code, et cetera. Worked my way up, uh, through, um, a, a bunch of roles at Xbox. Um, ended up doing a bunch of cross Xbox projects, shipped the avatar system, uh, and did a bunch of stuff to align data, uh, systems across Xbox.

Uh, then I went on to join, uh, uh, activism Blizzard King and shipped a bunch of mobile games there. And about 70 years ago, I made the jump onto, uh, EdTech. Uh, I joined a, a business called Education first and last year I joined Laber as the CPTO.

And you're right that the, the title is, is more common these days. But, um, you know, my journey has really been leading engineering teams and I find on the product side, um, and the engineering side, you end up at, at, at, at a sufficient, at a high enough level, you end up sort of doing the same thing anyway. So engineering teams, large leadership, that's about the, the architecture.

And from the product side, that's about mapping that architecture to, to a business problem. And so I, I've sort of ping ponged between engineering roles and, and product ish roles. And, um, seven years ago when I took the jump into EdTech, that's when I did the actual jump into officially being in product.

And then I rejoined engineering, so to speak, with Lobster here, uh, a year ago. So became Chief Product and Technology Officer. I love it.

I love it. Good stuff. Um, I was just reading a lot going on with that, the Xbox team at Microsoft.

They had some layoffs, some may have some more, but yeah, we could talk about that off camera. Sure. Let's talk lobster.

Bjorn. Let's talk lobster. I don't know if our, a lot of people in our audience are familiar.

What, what's lobster about? Yeah, lobster's a really interesting company, which, which is also why I joined it. We, we launched in 2012, so that, that's really when, when Lobster two was formed.

And, um, really with a mission to try and digitize lab access and kind of, um, create immersive laboratory experiences on screen. And, um, that sort of had, you know, a steady growth path, um, uh, pre COVID. And then of course during COVID, like many other ed tech companies, Laber, um, had a, a huge influx of, of customers.

And, and in that process also acquired a, a different company called uim, which kind of does the same but in pre-licensure nursing. So that was more of a VR based experience, but also really about immersive education. So today we have these two products, uh, lab are virtual labs, which really is aiming at getting students into doing, uh, lab experiences on a, a screen-based environment, still in 3D.

And we run, uh, ubm, uh, which kind of does the same, but it's all about, um, learning to treat and, uh, and engage with a patient for nurses that are in training and, and not pre-licensed, uh, yet. So that is VR based. And, and lab is, um, uh, is screen-based, but both of them 3D.

Excellent. So let me just make sure I got this right. These are sort of, I dunno, is VR still a term or is it ar Yeah, yeah, Yeah.

Okay. Yeah. So, So these are, Go ahead.

VR is, uh, uh, juicy is VR entirely. So, so it's very much virtual reality. So you put headsets on you, um, uh, you step into a, a, a completely digital environment.

It's not mixed with, um, uh, with the reality that, uh, that, that you are also in. Uh, yeah, exactly. And, um, uh, on the labs side, it's entirely, um, virtual as well, but it's, it's screen-based.

So we really found to, um, to really hit as many students as as possible for, for lab environments. Getting onto the screen was, uh, was key for us. So while we have had VR experiences in Laber before, we're now focused on the, on the screen entirely for, for laber for nursing.

Of course, a lot of that is kind of kinesthetics and body memories of really learning how to put hands on patients. And so we, um, virtual reality makes a lot more sense there. Wow.

Really cutting edge stuff. Now. I'm sure AI is having a, an impact.

What actually, before we jump into it, for people who just wanted to peel off and, and check lab out, what's the website? com. Uh, and that will also, uh, provide a, a link off to, uh, uh, to UB sim, which we, uh, run as a, as a product with its own, own domain as well.

com, you'll find all about our business and both UBM and Lab. Excellent. Alright.

Back to ai. Yeah. Can't, you can't walk, you know, three steps without tripping over it today, right?

Indeed. Yeah. Talk to us about the impact that AI is, is, uh, having here on the, on the, on the lab and, and education world that lapsed their place in Yeah, yeah.

Yeah. So ai, like everywhere else, as you say, AI is having an enormous impact on, on education as well. That is true for education in general.

It's certainly true for, for EdTech tools and, um, and digital tools like, like ours too. Um, obviously in education especially, there's a lot of concerns around, um, large language models and generative AI and, and how it impacts education. And, um, and that of course leads to a weird sort of love-hate relationship with AI and education where everyone can see the opportunities.

Everyone can understand that to reflect together with a large language model can be really powerful. And, and in some respects it can feel like an expert at everything, but it's also in a, in a sort of formal education environment, um, it can be felt like a, like a threat or something that really upsets, um, the, the normal loop of education, um, that students attend when they go to higher education, for example. So, um, we've obviously, um, feel that impact in lab as well.

So we, um, we have to take account of how our customers are seeing ai, and also we have to jump on the opportunities that AI provide. And they are, uh, plenty, which of course, um, tons of detail to, to dive in there. But, but certainly we are also trying to take a, a, a cautious approach to AI where we try and make the best use of the benefits that we can while avoiding some of the, the risks and the pitfalls that are really education are really feeling from, from generative AI today.

I love it. I love it. Now, you know, in my, looking through my notes here, we, there was this phrase, building AI that works for educators, not just for algorithms.

Yeah. I hope we're not just building stuff for algorithms these days, but something tells me we are right. A lot of times we, we just do things because it seems to fulfill a particular formula.

Yeah, that's right. Yeah. And you see, um, I think there's a lot of places in, in education, both more on the informal sort of business to consumer side where people self-select to do something to, to make them better.

Um, but also in the, in the formal side, you know, we, we see a lot of use of education that, that really, um, I would say is, is about almost circumventing what education is, is trying to do. Um, so if you, and, and to have that debate, I think in, in the right way, you really gotta start having a debate on what does it actually mean to learn? And it's something I I thought a lot about in the last seven or eight years, right?

To for, because learning, we tend to think of, if you, if you wanna learn something, you gotta do it a lot. And, and that's of course true, but, um, but what we forget in that, uh, way of describing learning is that, uh, you've gotta do something for a long time, and then you've gotta have the time to reflect on, on what it is you've, you've done. And without that reflection, you very rarely have, um, actual learning occurring.

So you might be trying to ride a bike, ride a bike, ride a bike all day long, and then you take a break and, and you can't really explain what's happening inside of your brain. But the next time you try riding a bike, you've, you managed to aggregate and associate some of the experiences you've had, and now you are better at riding that bike and, and suddenly, of course, it will click in a bike, in a bike case. But, but for other things, you've really gotta go back and reiterate that, do something, do something, do something, and then reflect, reflect, reflect.

And what we see in education today is that a lot of the, the reflection are happening by way of, um, essays. And so we see, uh, teachers passing information onto students, asking them to reflect on something in an essay or in front of a classroom or online is in, is increasingly happening. And then what happens there is that that reflection suddenly now can be taken over by a generative ai.

And then obviously teachers, uh, see that as a, as a risk students, um, very easily can get tempted by it. We've all been young before and sometimes we, we haven't quite prepped, and it's a normal thing to, to jump onto that. So that learning and reflection loop really gets upset by, by generative AI forces us to rethink what, what is learning and how do we pass information on, and how do we get students to reflect?

So we've taken a slightly, uh, different approach to it at, at lab for us. Um, we are really seeing AI as both as an opportunity to create experiences for students to, to have, um, thereby prompting them to do that kind of painful, um, remodeling that happens in the neurons in, in the brain of, of, you know, you're pushing hard, you're pushing hard against something. So provide a lot of experiences.

How do we support that with ai? And then helping students and teachers reflect on those experiences and how do we support that with ai? And if you suddenly see education's that loop about undergoing some experiences and then reflecting on it, then you can get outta that loop of being given information and having to do essays.

And that, that is the loop that is threatened by generative ai. But that doesn't mean AI can't play a huge and beneficial role in that loop. And that's kind of how we're trying to apply it.

How do we make more experiences and how do we make students and teachers reflect on those experiences? And in those cases, when you cast it like that, AI can be a, a huge, um, uh, yeah, huge power play for everyone. I, I agree with you.

You know, right before I got on to record this interview with you, I was over on our other set in the studio here mm-hmm. For our tech strong gang show. And we were talking about a recent, uh, report from Microsoft.

Yep. About, you know, over not being able to turn the off button on a lot of digital workers, especially, especially those of us working from home and so forth. You know, it, it's re it's reaching crisis proportions where we're just, we're always on, and there is no time to reflect and there is no time to learn or at least contemplate.

Right. You're working on a problem and it's sort of information overload, right? We're being constantly bombarded with information interruptions and, and so forth.

And how do we, how do you, how does one learn, how does one make rational decisions without the time to reflect and, and kind of, you know, compute if you will, what, what's the right thing to do? Or are we heading to a world where humans don't do that? Our AI will do the reflection for us somehow, and just tell us what the answer is.

I hope I'm not alive for that part, but I don't want to live in that world either. Alan and I, um, I've got four kids that I'm trying to raise from my wife, and we see the interruptions, uh, the challenges that you're describing. We see them firsthand, we see it in their friends, we see it in our own children.

And that constant battle of how do you get a moment where your children or other children can reflect on, on the experiences that we've had where they're not constantly interrupted. So we don't see, um, and, and this is, this is sort of a, a little bit about latch as well. 'cause we don't really see our role as being about constantly being in, in, in the face of a student or constantly demanding a student's attention.

We see it as a natural part of a qualified teacher's loop to say, how do I now create some experiences for my students? How do I assign those experiences? How do the students do those experiences?

And how do we reflect on them, um, together so we are not driving for microtransactions and, and, and pushing hard to, uh, compete for, for attention at lab. So for us, it's really about go into an environment, have that experience, and then once you've had that experience, we're gonna help you reflect on that experience with some, some feedback. And then we will help the teachers say, how do I reflect on this collective set of experiences that our students have had?

So that is also what we are, um, uh, pushing for. And, and it, I have a personal stake in this. As I say, it's, uh, that, that is the environment that I think students learn best in as well.

The chance to really go deep on something where you're not distracted, and then the chance to really re reflect on that. Agreed. Agreed.

But you, I, I think it's important and, and you hit it. That's how people learn. And if, and if we're in the educator business mm-hmm.

Right? Where lobster clearly is, we, we, you know, that's the gate, that's the goal here, to teach, to educate. Yes.

That's fine. And that's part of that education thing. And, and you know, though the world is changing and like the sand is shifting beneath our feet, I think we need to remember those, those things.

Yeah. Um, I wanna turn a little bit to ar, or not ar, excuse me, vr. Yeah.

Obviously AI is again, having huge impacts there, right? In terms of creating, well, your, your background was in the gaming world originally. That's fine.

Yeah. So you, you know, from this, right? But creating our environments, creating, you know, these VR labs that you guys are doing.

Yeah. Yeah. I gotta imagine making that a little easier.

No, Well that's exactly it. And, and this is really the first part of where we see AI playing a, a huge role in, in, in learning in general. But certainly for Laber specifically as well, we've obviously, um, you know, to align with the interest of, of our customers, we spend a lot of time working with instructors, working with teachers to really understand the, the challenges they face.

And then we try and we wanna go and build content for that teacher group, which means that we have to have trusted, educated educators on, on our team as well. So we do. So we have the scientific experts, we have people that come from academia, because otherwise we can't really understand the customer we are delivering for.

But what we found, of course, over time is creating these kind of immersive experiences that are really make the student reflect and, and aren't just skin deep, but, but really allow the student to explore an area that is a, that is a resource intensive thing to do. And what we're trying to do is to say, how do we keep the scientific experts, um, at the reins and holding the reins of this process, but support them in some of the, the rote work that's happening and some of the, um, some of the heavy duty creation work that they gotta do. So we're trying to build new pipelines, so that, that's what we're doing right now, is to build new pipelines.

So we really have a couple of break points to say, okay, so we've had some AI support on X, now let's get a human expert involved. It's the human expert that reviews it. It's the human experts that signs it and puts the name on it and says, I believe in this, and this is scientifically accurate, and it's aligned with the curriculum that, that the students are about to go and face.

So for us, the creation of content isn't something we want to hand over to ai, but it is something where we really see AI playing a role as long as we keep humans in charge. And it's a little bit of a reflection element on, on the learning bit, uh, as well, right? Where for, for you to learn, that doesn't mean that AI can't be involved, but you've gotta raise your abstraction level to now think in, in larger bits.

And AI can play a role in amalgamating and synthesizing those larger bits, but you still gotta do the thinking on top. And that's what we're really tasking our academic experts with, is to say, okay, how do you remain in charge of this constant creation? How do we make sure you feel convicted that what we're shipping out is something we're proud to put our name on, but at the same time enable you and empower you with all the tools that's happening?

So yes, both on VR in Yim and in our digital environments in Lab, we see, uh, uh, uh, AI play a role in content generation, but not untrusted, not unguided, just steered and held working for us and working for our human experts. I think you're onto something there, BJO. It's, it's important that we remember this is a tool that's right.

It, we can't, we can't lose our ability to think and reason by, by abdicating that to, to to ai. Right. Otherwise we'll wind up in a world like that Wally Walleye Yeah, that's right.

Kind of movie, right? Where we're all that people walking around on those server chairs playing, you know, our games or what have you. Yeah, Yeah, that's right.

You know, gotta keep people thinking. Yeah. And so you're right.

And so exactly that, and that is true in general as well as in in education, right? And, and we're seeing some of the, you know, there's early research now, it's not quite gone through peer reviews yet. Maybe the studies aren't as big as we would like them to, but there is early research now that indicates some of the critical thinking that we really want to engender in our students.

It does go amiss when you, when you just lean back and let AI take over. And we kind of know this intuitively, but it, it is clear and is it, you know, we can see it in the, in the data as well. And so I I, we all see this at work too.

I, I've seen some amazing output that has been steered and, and by a really smart individual who has used AI like a tool. Um, and I've also seen, um, some absolutely AI slop come out of somebody that's just lent back and said, well, we can let AI do the bit. So I think in both education and in the real world, allowing ourselves to, to not critically think is a huge danger.

And so for us, it's now a matter in education. And outside of how do we raise our abstraction levels above what the AI can do for us, and start thinking about this as larger chunks that still have to be critically analyzed, still have to be critically, you know, questioned, are these the right things, but then can be composed as bigger blocks. And that's kind of how we are thinking about, uh, content generation in, in lab.

We have bigger blocks to play with, but we still gotta leave a human in charge of composing them and validating them and feeling convicted. It's the right thing to do. Agreed.

Hey, we're outta time Bjorn you. I feel like we barely scratched the surface here, but Yeah, that's right. It's okay.

It's 15 minutes. It goes quick, man. There's only so much you can cover, but hey, one more time for people who want to head over to Lobster.

com. Dot com. There you.

That's exactly right. Bjorn tof, KOF Mattis Madson, uh, chief Product Technology Officer at LAP here on Techron tv. We're gonna take a break.

We'll be right back.