Introduction

So who has used Suno before? Yeah, a few of you.

So this took me 30 seconds to create. And I think it's a fantastic candidate for the next Eurovision.

Can you hear me? Yeah.

Yeah, wouldn't you think so? I think it might be better than possibly like half of the Eurovision contestants. Much more sort of, much more in the wind on the topic.

So I wanted to just kick you off with that as we're talking about skills. So future skills and scenarios.

Speaker's Background

So I've had a past in learning at Google, and I've worked with startups and scale-ups in the EdTech space for the last couple of years. So I wanted to take you on a more somewhat theoretical journey of what the future with AI can look like, but from a learning and skills perspective for organizations mostly.

So just to start off with, like my story and why I think this is interesting. So I've always been a thinker and somewhat of a geek, so playing with computers when I was younger.

And I clearly remember when I was in high school, sort of 14, 15 years, I went into the classroom and I wrote on the blackboard my email address. I was like, I was so proud I got this email address.

And then nobody, like nobody understood what I was talking about. So this was like before internet was popularized. Nobody else could talk to me on email. But yeah, my inner Neo from Matrix was really, really happy.

Early Technology Adoption

So if we bring the parallel to today, I feel a bit the same today. With you, we're a bit of the early adopters, right?

There's a few that are really experimenting and testing and creating things, ideating, and doing all kinds of crazy things with AI. generative AI in particular, but there is a need to really understand, to build these skills, to really be able to use the technology.

And that's what I want to talk to you about today.

AI skills are the new bag. Yeah. Yeah. It's so cool.

The Skills Gap

So the problem is that there is a huge gap. There's a huge skills gap today.

So on one side, leaders are saying that, OK, generative AI is going to change roles and skills. People are using AI in the workplace, but they're afraid. They're worried about what's going to happen when they get exposed if they're not using it according to policies and all the internal barriers.

And then actually companies, they are only a few providing training and helping people develop these skills. So there is a huge gap. And that's, I guess, partly what MindStone is trying to bridge as well, and others in this room.

But there is already a divide, and it's really, really important to bridge this divide now and to start with the basics. We're not talking about the technical skills here to develop AI applications. We're talking about AI literacy for everyone.

Upskilling vs. Reskilling

And when we're talking about learning and upskilling in organizations or outside in society, there's two sides to this coin. On one side, there's upskilling, and the other side, reskilling.

So upskilling is, OK, you have a role in sales, marketing, you're a marketing manager, so you will need to learn some new tricks. But your role is not going to fundamentally change. Well, some might say yes. But you need to learn some new tools. Your process will still stay the same, but you will do things a bit differently.

However, in some roles, and I think a great example here is IKEA, who deployed an AI chatbot and saw that 47% of their customer inquiries were answered and dealt with by the chatbot. And then you would say, OK, let's fire 47% of our customer support people. They didn't do that. They offered reskilling to these 8,500 employees so they could become interior decorator specialists. So to support all those customers who wanted to go further in their inquiry, because they're asking about some kind of furniture at IKEA. But actually, that was an area in huge demand.

So I think that's where you see differences for some roles and then some companies. might do the sort of firing thing. But actually, isn't there a better way when you've actually spent so much time and resources to onboard employees and bring them in the company? There's probably a better way.

Future Organizational Roles

So I'm going to take a huge step now before we dive into the future scenarios. Say, OK, in these new organizations, these new roles, these new skills, what should we do differently?

Investors, researchers have said, okay, we need something new for new organizations in this new world of transformation. We need a chief skills officer, or you can call it the transformation officer maybe a few years back.

But to me on the sort of learning transformation side now, what's the data that has some value? It is the skills. Like the organizations need to understand what the skills are of their employees. And they need to understand them fast and put them into system over the whole life cycle of an employee.

So it doesn't help to just sort of say, okay, yeah, we're going to do this learning program. Like, okay, you have like a marketing skill. We're going to make you like a great marketer, like even better, advanced. No, no, no.

You need to start at the beginning. So think about the people, HR function. So you recruit someone, like talent and recruitment. And then you onboard them. And then you give them some continuous training program. And then you have performance, management, and offboarding at some point.

What if you had systems that you can actually use to understand and track and help the employees all along that journey? And by the way, these systems exist today. So there's a whole thing to do across all these functions, HR, learning, and development, and beyond, to help people.

So almost not talking about AI, but preparing the organizations for this new transformation.

And you can see a few things here. What are the KPIs you would look at? And is looked at, but across different functions today in silos that needs to be broken down.

Future Scenarios

With that, we'll move over to the future. So this is sort of today.

How many of you have heard about Ethan Mollick? Yes, a couple.

So he's my greatest inspiration around AI, like practical AI, period. So he's a professor at Wharton in management in the US. He has a newsletter, and he has published a book called Co-Intelligence.

If there's one book you should read around AI, like it's not technical, and the future of AI, read it. And in there, he is talking about future scenarios for AI.

And he has created this bot. So this is a GPT bot that anybody can use. And it will help you construct different scenarios for the future. Very, very interesting.

So, I wanted to show you what that looks like in practice, but with a twist on skills, because I think that's why we're here today, and make it a bit fun or extreme. So, let's see here.

First, a few things to think about when you do this analysis. And I think it's important for you to think about as well.

This is like a typical steep analysis that you would do in a competitive environment, but also helps to analyze the future. So taking out a few things, will society accept widespread AI use? I was talking about people are afraid to show what they do.

Will society accept? that? Will organizations accept this usage?

Also, environmental. They say now that by 2026, generative AI will use the amount of electricity in Belgium. So can we live with that?

And then political, will governments come in and regulate some of that? Or will they maybe mandate some literacy programs? And that's actually happening in California right now with their latest.

It's not the AI Act in Europe, but it's their own version of the AI Act in California. And they are actually mandating AI literacy programs for students.

So a few things to think about as we move along. So shall we play? Let's see what we get.

Transformation and Disruption Scenarios

So we have two scenarios. I'll just call them sort of the transformation scenario and the disruption scenario.

So one here starting with, okay, actually things didn't go so well for AI. Something just stopped the development. So this is possibly the case with, let's say, energy usage.

So governments came in. They regulated and said, hey, you're not going to spend this electricity on data centers. We need some more important things. So the first thing that was cut from data center usage was AI applications, because it takes so much electricity.

So actually, it means that most developments stop. So we focus on sort of human skills in real world instead of these digital skills. Do you think we'll get there?

Next one, so AI everywhere. So this is almost like we're a bit at now. So I make the comparison with like the smartphone.

So we got the smartphone, you know, fantastic, like huge step in terms of how we interacted with internet and had it with us all the time. But then, well, features sort of come and they're sort of incremental now. Like there's no revolution with the smartphone, right?

So maybe we've seen the best of AI so far. Maybe, you know, open AI, like they will limit themselves at JetGPT-4. Oh, maybe that's enough.

So, you know, maybe we'll just, you know, integrate AI routines that we can now with new tools and that's enough. What do you think? Do you pick scenario one?

Who thinks we're going for scenario one? No, no. Two.

Two. Yeah, yeah, a few. OK.

OK. We're taking it slow. We're taking it slow.

Exponential Growth and AGI

So this is just the transformation. Then now, look at some more interesting scenarios. And by the way, like all of this was AI generated in Gamma, the application that Joshua was showing as well.

So here, so third scenario. So things are starting to get, you know, going fast, like really fast. So it's almost like we've seen sort of maybe the first year with open AI and the applications.

And maybe somebody feels it still, that pace is going so fast. We can't keep up. And organizations, they have problems to keep people trained and develop the right skills.

And there's unrest, riots, as people, the 47%, they're all fired directly. And, you know, I think this comes into a bit of the fear, right? Like the fear and the risk and all of that when things move so fast.

It's hard to be ready for that. And the last one, this is AGI, Artificial General Intelligence. So this is when computers, they're more smarter than we are.

So it's almost hard to get there. It's almost hard to imagine. But they practically run organizations.

And they will take over most of what we do. So we're left with... Yeah, what are we left with?

I don't know. If you had to vote, which ones? The number three, so exponential, or AGI?

So first, exponential. AGI. Oh yeah, yeah, yeah, we're getting there.

Okay, I like it. Yeah, yeah, yeah, yeah, okay. So I'll let AI itself do the conclusion of this part.

Reflections on AI and Humanity

So I said this was all AI generated. So let's see here, okay. What does it even mean to be human in a world where, let's face it, the machines might just be better at it than we are?

What do we value? What do we aspire to? Those are some heavy questions.

They are indeed. And the truth is, there are no easy answers. But maybe that's okay.

Okay. How so? Because wrestling with these questions, even if we never find definitive answers, that's part of what makes us human in the first place.

And who knows, maybe the journey is more important than the destination. You know, you're right. We started out talking about these four different scenarios, AI stalling out, AI becoming commonplace, AI advancing at warp speed, and finally this, AGI shaking things up in ways we can barely imagine.

And it strikes me that while each scenario is unique, they all ultimately lead us back to the same fundamental questions about, well, about ourselves. Precisely. It's like AI, no matter how sophisticated it becomes, it's always going to be a reflection of us, of our hopes and our fears, our dreams and our anxieties.

And the choices we make today, they're going to determine what that reflection ultimately looks like. It's a lot to think about. But that, I think, is the point of these deep dives, right?

To explore these big, complex ideas, even if they make our heads spin a little. And who knows? Maybe by having these conversations now, by grappling with these questions early on, we can help shape a future where both humans and AI can thrive.

Couldn't have said it better myself. So to our listeners out there, keep those brains buzzing, keep asking the tough questions, and stay tuned for more deep dives into the ever-evolving world of AI. Until next time.

OK, thank you, AI. So this was a snippet from Notebook LM. So I fed it the scenarios that was generated by ChatGPT without any other instructions.

And I just generated the podcast, if we can call it that. And this was the end of the podcast. So it's not only

you know, taking what actually the scenario was saying, it is actually sort of building upon it. And this was not like the text in the scenario itself. So I don't know, are we touching on AGI here or?

I think it's, you know, it's, it's worth testing it with anything you have, like any documents, any research, just to get some thought stimulation.

Key Takeaways

So with that, I'll move to the last part, which is just the takeaways. So if you take away something from this session, it's that, well,

You need to be better at learning. Individually, in the organization, become a champion. Become a champion for AI.

If you're already doing something around AI, share it. Spread it. And hire a chief skills officer.

Agility. So I think that's also what we heard from some of these scenarios. You have to remain flexible. You don't know which scenario will hit, but it can go up and down and can have quite big consequences. So you need to stay agile to do that.

And what does that mean? That also means that you need to test and experiment with these technologies all the time.

And lastly, as well, our friendly podcast hosts were telling us, by the way, I run a podcast for two years and I think I'm going to stop now because, you know, it's so much better. And, you know, we need to continue building these human and soft skills. You know, they're going to become even more important with this AI transformation.

And That was it. I'm standing between you and pizza and drinks right now.

Q&A Session

But we can take a few questions if you want to. Thank you. Any questions? Yes. Thank you.

Your last slide says something about building up our own uniquely human skills. What are those?

I actually removed it from my slides. But I'll pull it up. So I think it's interesting to see what are the human skills that will have an impact you know, specifically with AI. And why?

So, you know, I think in the education we've for a long time talked about, you know, the five, four Cs, et cetera, and you see a few of them here. So like the critical thinking, why do you need that with AI? Because you need to understand, like, how the hell does this work? And honestly, Even the people who built these LLMs, they don't fully understand what happens in the middle. But you need to be able to evaluate what comes out of it. And then you see the other ones here as well.

And also, to one of the scenarios, like creativity, it's easy to fall in the trap to just, you know, you take what comes and, you know, that's creativity. But no, it just means that you can be 10 times more creative. Instead of 10 ideas, you have 100.

And yeah, I don't know if that answers your questions. Your question. I got a feeling that AI could actually surpass us in most of those skills as well. soon, like, look at what we saw of AI doing two years ago and what it does now.

Yeah. Like, this slide is probably what AGI would have done to convince us that we're still driving it, but actually it is. Yeah. You know, build it. Build it and tell us what new skills we need. Yeah.

I think that for today, I think this is what we need more of, a lot more of. But for tomorrow, maybe there's other skills. Other questions?

Personal Beliefs and Global Perspectives

What do you believe? Which scenario? Yeah, I think it's sort of in between the transformation and the disruption somewhere. So I'm a bit of a geek, so I really enjoy technology.

So I'm less afraid. I'm less on the dystopian side. So I think this is going to be really great and really will have an impact. But I'm maybe too much of a geek. Yeah.

Around the world, the need for AI, the use of AI may be very, very different. Yes. It's growing with AI, but in fact, the AI you need on the African continent with one billion young people, it's not the same as in Japan. How do you build these differentiated approach strategies and responses?

It's always the same kind of deep mind and notebook, but what do we do? Yeah. Yeah. Yeah.

So how can you ensure that there is equity, equality in the use and availability of these tools? Yeah. . Yeah, so OpenAI, they launched what, this year sometime, like their education, what do you say, department, right? So they are trying to see how they can do good in education, like more in K-12 for students, right? So I think, obviously, they would want to push these things.

But Google, for many years, were working on the African continent to provide connectivity. And that's still a big need in many parts of the world. But for the first time, at least now, you have a tool that's free everywhere, as long as you have internet, that someone anywhere in the world with internet access can build a business in 20 minutes. So maybe it's going further than before.

Last question, yeah. What will happen when states will fail, including France and the United States, will Google take the control? And when I say Google, I mean the Google AI, et cetera. So I don't have the answer to that.

But I think what's interesting is that you already see a divide, right? So Europe has been a bit more restrictive and have this AI act, et cetera, which in some areas is good. But in other areas, we don't have the latest chat GPT functionality because OpenAI is restricting it for Europe. And it's also the case for Apple. They're not going to launch Apple intelligence first on the European continent. So does this really help us?

I don't know. But at least Europe is sort of a bit more careful with these technologies. But yeah, I'll let the room debate that over drinks.

So thank you so much. It's just upstairs.