AI is set to disrupt a lot of things, and fueling the data evolution is one of them. In this episode, Michael Clark from MasterCard, a trailblazer in the domains of data, future value, and digital innovation, shares what he learned from two decades of experience and their recent forays into the world of possibilities offered by AI. Delve into the world of data monetization and gain insights into global examples that illustrate the shifting landscape of data ownership. Uncover the potential for individuals to harness their data, ushering in a future where AI becomes not just an assistant but a personalized guide. Tune in and discover how we are heading for a future with a new currency based on data and powered by AI.
- Data ownership is a crucial aspect, with the potential for individuals to monetize their data.
- The changing nature of value, influenced by AI and data, is redefining businesses.
- In the transition from knowledge workers to knowledge executors, AI will play a role in gathering insights and humans interpret and execute knowledge.
- The value of AI in reshaping financial inclusion and education.
- The convergence of technologies and industries is shaping a new economy with innovative business models and personalized services.
- The emerging value layer in the digital world will see the rise of data investment vehicles, such as data bonds and ETFs.
- Continuous learning, especially in the rapidly changing tech landscape, helps individuals and businesses stay ahead.
- Michael Clark: “This ownership journey and particularly monetization is starting to put the power back into the user.”
- Michael Clark: “For an AI to run the way that we would want it to, it has to be running on real-time data.”
- Michael Clark: “The unbanked and the underbanked are just left behind today.”
- Michael Clark: “We’re living in a world of convergence and exponential growth.”
- Michael Clark: “We’re in the midst of the next revolution.”
Listen to the podcast here
Learning About Data Evolution With Michael Clark From Mastercard
I’m Michael Clark. Join me on the Edge of AI and let’s explore the data revolution together, the show where we blend AI creativity with culture. Stay tuned.
Hello AI show passengers. Jump on in. Here’s what’s to come on this journey. Find out what our guest thinks about creating a digital twin of yourself and why you will want to do that, how data becomes the next currency for all, and why he flew halfway around the world for a data wallet. All this and more. Take your seat.
Snap in your safety belt and prepare to explore the depths of the rapidly expanding AI Universe. Each episode is a dispatch featuring hyper-relevant reports from the pilots, pioneers, and passengers aboard the AI rocket ship. We explore the latest use cases and developments in AI, hear from experts building the tech, empower you to embrace your life with AI, and learn how this disruptive force is transforming industries and society.
Just like most of you, I have embraced the spirit of exploration and entrepreneurship throughout my life. From starting my own business before graduating high school and traversing the world’s most challenging terrains, I’ve always thought of new frontiers and adventures. I built one of the largest award-winning custom home companies in Los Angeles. I’ve navigated complex regulations while founding and leading a public company that is dedicated to applying technology and training. Buckle up and get ready. Let’s tackle uncharted territories in AI with curiosity as our guiding star.
This episode features Michael Clark from Mastercard. He is a maverick in the realms of data, future value, and digital innovation. He brings over twenty years of experience in forecasting and implementing cutting-edge technology solutions. His expertise has transformed leading global companies, addressing some of the world’s most intricate data challenges, and steering them towards a digital forward future.
Michael is championing the use of data as a currency. Helping businesses seize tomorrow’s opportunities now, his latest book, which is Data Revolutions: The New Currency of You, offers a roadmap for businesses and governments to safeguard citizens in an era where the nature of value is rapidly evolving. Welcome, Michael. How are you?
All good. I’m excited to be here. I am looking forward to this conversation.
You’ve been pivotal in helping communities and companies navigate data challenges. Could you share your journey with us and what you’re focusing on?
We started looking back in terms of where you’ve come from. You sometimes forget some of those little nuggets that got you here. I have to admit my journey started like every kid. I’m not going to go this far back but at ten years old, my father brought home the world’s first computer, and all of a sudden, you’re programming. The screen grows green and you see data. I was hooked from that moment.
Throughout my working career, I’ve been lucky to be able to work for some of the biggest companies in the world, big financial institutions, and even FinTechs, using data to drive insight and create new products into where I am now in terms of the concept of the book but also advising banks around the world and even governments in terms of how they start to look at data very differently.
We had the pleasure of speaking a little bit prior and from my point of view, you are looking at data in a different manner than most. I’ll call it looking around corners about what data means for all of us individually as well as companies tomorrow as opposed to now. Can you talk about data monetization which was part of it and global examples of those types of things?
It’s a great question because there’s often a lot of confusion about what data monetization means. If you bring up the topic in any business or even to an individual, fear normally comes across their eyes because we’ve heard so many stories about looking after your data, the Cambridge Analytica crisis, and various other things. When people are monetizing data, they’re deriving the insights and monetizing the insights from data.
There are some great examples around the world. Companies like Schneider Electric are a great example where they take all the data from their IoT devices, anonymize that, and then sell that on marketplaces. Companies or even governments use that data for wind farms to understand carbon usage to even forward-plan and predict.
We have examples in JDEX in Japan where they sell every form of data you can imagine from tourist information and so on. That’s a great example of data marketplaces that are emerging around the world. Also, let’s not forget that companies are using data to add analytics on top of their products. They’re not necessarily selling the data at that point. They’re using it to add more value to their product.
You described a couple of different angles for that. One was the larger corporate data and some of that would be reporting on it. Also, you mentioned the IoT devices pulling or WinForm the information as an example. It’s stationary devices that collect data in real-time and live time as well. We haven’t even gotten into the individual data but starting there.
On the individual’s data, you ask for monetization. In the Web3 world, we already see examples of this now with data unions, for example. It’s where people pull personal data together and it’s sold on a marketplace to a smart contract. Everybody in that pool is rewarded. We’re seeing new things emerge from the individual as well as the corporate level.
It’s a combination of AI, blockchain, digital payments, and that type of thing. It’s all merging together. How is it redefining digital ownership or data ownership?
This is the elephant in the room. We’ve been on this journey for some time. If you look at regulations like GDPR or at other countries that are trying to put data back into the hands of users, this ownership journey, particularly monetization is starting to put the power back into the user. Brazil started to make into mandate that users would now be able to monetize their data. This has big implications as we start looking forward, but also, incredibly positive things as well.
What do you think drove them? Why are they uniquely looking at this? Is there something about what they’ve done in the past that brought them to this? I agree with you. I can imagine every governmental body is going to end up doing this at some point.
If I take Brazil as an example, they’ve gone down a journey. I recommend everybody to look at the YouTube from the governor in terms of his explanation of that journey. They’ve been piecing together the puzzle gradually so they built the Pix network which was account-to-account payments. They must build a digital rail that allows data to move across that rail.
Their GDPR, for instance, has 9 points whereas the rest of the world has 8. The ninth point is “Don’t tell me what you did with my data. Tell me what you did with my data after that. Who else got my data rather than you?” There are things in legislation that some countries are starting to put in place which is painting the way and paving a path to ownership. It makes that example unique but also, does that become a blueprint for other governments to follow around the world?
Talk about peeling away an onion. It feels like it gets on some levels more and more granular and on some levels, bigger and bigger. It’s almost both directions, correct?
How do you see it changing? Let’s talk about the individual for a moment with this ability to control and even capitalize on your own data. Tell me a little more about what that looks like from an individual standpoint.
For an individual, this unlocks so much potential. For example, our data is hidden behind the services that we use. Whilst people start to own their own data, could they start piecing together their own utilities? Could they have data savings products where they use their data as a means of savings? Could data drive new investments? Could I be using it to build a data bond, for example? Also, for the individual can they even use it to manage their health or create personalized fitness plans?
There are so many things that we can do with our own data that we don’t do now because we freely give it away. Once we have control of it, we almost end up creating personal services for us, which is where the AI comes in. It’s because now the AI can become our true personal assistant helping us manage our finances because now our AI knows everything truly about us. It’s using the data that we own about us or any data that we bring into that.There are so many things that we can do with our own data that we don't do today because we freely give it away. Click To Tweet
When it comes to the value to us individually and how it might change our lives, would I be right to assume that with fractional payments through digital? The data you’re selling, you might be getting small fractions of. That’s not going to be enough to change someone’s life, but the benefits you get by sharing it could be the results of what someone else does with that data. Is that fair?
It’s a yes and no. Yes, it’s what someone does with it because what’s happening is people are exchanging value. Data on its own is worthless. It’s only when it’s exchanged for unit to value that it becomes meaningful as context. To your point, yes but data is weird. Data can be everything and nothing at the same time. That same data piece or data that you own, in one ecosystem, is not valuable at all. In another ecosystem, it could be incredibly valuable.
Let’s take the example. Maybe there’s a company doing heavy lots of research on health and I have a piece of data that they don’t have. Suddenly, the bigger question is, “How valuable is that data for that company versus what it is now?” They have access to it but now, we own it. Suddenly, that piece of data may become incredibly valuable because they need it to solve that problem.
What you’re touching on now is the changing nature of value. I know that’s covered in your book extensively and as far as I’m concerned, you are the exact right guy to speak of that. To switch over to the business landscape, how is the changing nature of value going to change businesses as a whole?
This is again another elephant in the room because you’re thinking about how businesses run now. It’s based on productivity and efficiency. Whereas, when we start talking about data and value, it doesn’t fit into those two buckets because value now is about intrinsic value and extrinsic value. It’s the individual loans. It has the value and then there’s the value to the outside world. What businesses need to do now is look at the data like liquidity.
Also, to start thinking about, “Where is the value in our data, and where is the value that we want?” The value now to the consumer of those data is your core values as a business. What are your ethical values? Can I trust you with my data? Do you have a track record of managing my data securely? Are you transparent? Are you relevant to me?
Let’s not forget data is a value but don’t forget that our reputation will also become a form of value. Even our core values will become a form of value. All of this is going to change the way that businesses measure things and also start to think about the data that they have in terms of how it’s used and how it’s measured because it’s going to be done in a very different way to what we know now.
We see those changes already happening. In your book, you mentioned the term going from knowledge workers to knowledge executors. That’s a fascinating little clip right there. Go ahead and elaborate on that if you can.
This is one of my favorite bits in the book. Before AI, maybe they hired an agency to go off and get some insight. Maybe they hired an army of people to go and collect information which then they would need to somehow disseminate and figure out what to do with it. They’re left with knowledge but still, we know that a lot of businesses don’t execute knowledge which in Greek times is known as wisdom.
The big difference with AI is that AI now is going to be the one gathering the insights because AI is going to be trolling the ecosystem looking for value that is owned by people that a business needs to be able to turn into knowledge. The business of tomorrow needs to become knowledge executors because AI is the one creating the content for you. The big difference for businesses tomorrow is, “I’m going to get you the knowledge, but do you have the ability to look at it, understand it, and then make a decision?”Businesses tomorrow need to become knowledge executors because AI is the one creating the content. Click To Tweet
Are you then in a position to respond? That means you also need an adaptable organization. What that means for the business is now you have a new employee who doesn’t sleep, doesn’t take breaks, and doesn’t take holidays. This is your AI knowledge worker and the business now needs new roles that can now interpret knowledge and use it to make decisions. The big difference is time is not on your side because the data owner may decide, “I’m going to give you this data for a period of time that I decide.”
It opens up so many things. I, with my own data, can rent access to my data for that period of time. An AI product has to grab that data, take it, and do what it will with it, but then the next step is, now we have too much data. It’s going to take AI to analyze that data as well because of the amount you can collect. Let’s go back to the human worker. What role do they play in that process or from that point?
There are two roles they’ll play. A lot of times we use AI, it’s almost the human on the shoulder. In a lot of the human work, in some cases, humans won’t always make the decision end to end because the AI will do that for you. It’s because the decision is repeatable and simple. For this stuff that moves the dial, which are critical decisions for the business, the employee has to do a couple of things. The first is the computer says no doesn’t look good in front of the regulator. The worker has to be able to understand how the algorithm operates and ultimately, how AI is coming up with the decisions that it is.
The second is that the people who need to make the decisions almost need a middle layer, which could be an employee who interprets some of those big decisions and presents them back to the workforce or the management team to make that decision. In essence, it’s going to require a new operating model, a new structure, and a more adaptable organization because it’s almost like data is becoming organic. This thing is constantly changing. If you miss it, you may lose the opportunity that could move your business forward or protect you against the competition.
You don’t see where I could put my whole business on complete autopilot to have these different AI machines with their platforms and assessments. You don’t see it where I could program that and walk away. While there will be examples of that, do you think the vast majority of companies and businesses will be able to operate that way?
Yes. There will be companies that will be run by Dows that could eventually be run by an entire AI operationally. I still think you need humans to set the vision and direction for that company. I still think we need subject matter experts and communities to continually validate the outputs from AI. There may be examples where you could spin up an entire company, which is an AI-driven company in a Dow managed by maybe a handful of people who will set the vision and the community there keeps on checking the outputs that are created by the AI. However, if we’re talking about multinational corporations, AI to me just becomes another employee. That organization then needs to decide the role that new work is going to play, what is the management system around it, and how it operates.
It’s fascinating. If I go back in history, I’ll only go back to the transition from a majority of work being blue-collar versus white-collar. That transition from the majority being blue-collar to white-collar happened in 1960. It seems about right if we look at it. That’s when computers started doing their thing and people were able to operate in a different manner. There were fewer people getting their fingernails dirty and the transition started.
We’ve then ramped up and you can go from the computerization, to the internet, and to many of the progressions that have happened. It would have been very hard in 1960 to predict how we operate now because if you looked at it in 1959, you might have been very fearful that this transition would lead to no work for people but that’s not what happened.
The work certainly just changed. For people that are looking at it, saying, “What are people going to do? How are they going to live? What are they going to work on?” there’s still a substantial amount of physical workers that have to do their thing. However, when it comes to all office workers and all the people that are white-collar, what’s next?
We often hear the narrative with AI that it’s going to take people’s jobs and it will. That’s a fact, but we often lose sight to the fact of what’s fueling AI. It’s our data. Does our data become a new form of universal basic income? Does our data become a form of savings and a currency that AI needs to operate? It’s because there are some serious statistics. By 2026, Europol predicts that at least 90% of the internet will be of AI-created content.
For us to have a version of the world that we believe in, an AI can run it the way that we would want it to. It has to be running on real-time data and real data. If people are constantly creating data every minute and every second of the day, it becomes incredibly valuable for an AI network or machines that need that data to operate.
The irony is every human alive creates about 1.7 megabits of data every second. To put that into context, every human being alive every day creates an equivalent of 733,000 digital photographs in data. You can imagine if all the people alive owned their own data, they could be farming and providing the data the AI needs to provide public services and engagement.
Is this a decentralization of the businesses that are going to deal with them because there are so many niches? Will there be smaller companies that will be dealing in specific niches over a massive company that controls a vast majority?
What you’ll see is that there’s this transition from data to value. To me, it’s the user either in my data or it needs to turn into value. Not to give too much away from the book, but there’ll be a utility layer that does that translation into that value ecosystem where businesses will be creating and accessing data. There have to be businesses in there to make sure that the environment is secure and data is priced accordingly. There are almost banks that will hold people’s data for them.
There will all be these niche players that will exist as well as the businesses that operate and use data in different ways as we know now. There may even be niches of companies that look after specific data for you because the best take health data. That’s incredibly complicated. It probably has very difficult data structures and you may want a specific company to manage that data on your behalf that only focuses on health and has dedicated AI capabilities that only operate in that sector.
You may find companies that operate in niches or you may find companies that are one-stop shops. Also, you still have your traditional organizations, but they may be providing different products. It’s like what’s happening in banking. People are now moving to digital asset management from traditional asset management and it’s logical that the same model will apply to data.
That’s a great analogy you gave right there because if you look at banking and what’s changed, I know my bank that I deal with locally here has put in what’s called ITMs and they’re information maybe. There are two-way ATMs. If you need to talk to someone, you hit a button and in some central room somewhere, you get a person but the whole idea is fewer tellers and people working in the branch themselves.
I would suggest that it might be temporary because there are banks now that operate without any branches whatsoever. I’d suggest that most of the people who deal with those banks don’t see a value loss in dealing that way. That whole industry has seen its change. When you go into financial businesses now, I would say you can manage your own money better now than you could have in the past with the amount of information that’s available. By having all this AI going on, these changes that I mentioned in banking and the finance world, you look at what’s next and you pair them together. It’s all the change but the change has already started.
We already see branches with digital humans in them powered by ChatGPT. That’s a real thing. The other thing that we’ve touched on was what it means for people when they own their own data. One of the biggest challenges in finance is inclusion and financial education. Who’s to say, “If I own my own data, my AI understands my financial education level? Who’s to say now the AI doesn’t deliver me my financial information in a way that I understand based on the data I have?”
In the end, how needed is that? The unbanked and the underbanked are just left behind now.
Completely and it’s because either financial products are complex and described in such a way. The question is, “Why do we need to solve that problem? Why can’t AI do that for us based on the data that individual has?” When Apple launched the Glasses, they gave us the ability for the first time to store human emotion as a data set. You can find all of that with someone’s own data and suddenly, we get completely different engagements than we’ve ever had before.
Let me put a bit of a spotlight on that. With these Glasses, they’ll be able to read whether it be facial expression, how your eyes react, or the sound of your voice, picking up your mood, and your confidence on the subject or whether or not you understand it. All that’s picked up live time. With an AI product, they could then deliver education with all those points in mind and meet you where you are.
Let me give you an example. It’s a story in the book. If your heart races and you’re wearing an Apple Watch, the first reaction is you probably need to go to the doctor because you’ve got a heart condition. That’s what it’s seeing. It’s seeing your heart rate rise. What Apple doesn’t know is you just opened your bank statement and you can’t pay your bill.
If I had my augmented glasses on when I opened my bill, I would correlate the data coming from the Apple Watch through what’s coming through the glasses, and all of a sudden, my financial assistance appears from my bank and is offering me the same day loan to pay my bill. All of a sudden, these nonverbal cues that we can’t record now because 55% of human emotion is nonverbal, Apple and these augmented glasses that will follow will for the first time in human history allow us to record human emotion as a data set. If I ask my own data and I choose to run my own purpose on AI on top of that, I now get a whole set of experiences that are truly personal to the individual.
It’s almost like an interlude within the interview but I want to remind people that what you’re breaking down or talking about, your resume/experience is with some of the biggest companies in the world working through these subjects. I don’t think anyone who doesn’t have that background could have language the way you just did. It’s mind-blowing but it’s crystal clear and quite honestly, it all makes sense. It’s amazing. I assume you’re watching companies going in this direction right now ahead of our knowledge about these things. Is that right?
What I tend to do as any good person that’s looking forward is look a little bit backward, but then you look at everything and anything. It’s almost like you’re looking at this macro view and trying a piece of jigsaw together. To be honest, that’s what the book is. I’ve just pulled all the puzzle pieces together based on things that I’ve seen, things that are emerging, and the dots that are joining. The book is written in a story format. Anything new, I tell a story. Some of this stuff can be a little bit conceptual or maybe it’s a bit sci-fi but some of these things are possible now. It’s only the fact that we’re living in a world of convergence and exponential growth.
I often use the example that it took 50 years to get 50 million people to use the telephone. It took 2 months to get 100 million people to use ChatGPT. We are living in an era where our acceptance of technology is higher. The convergence of industries is happening. Health is conversing with finance and so on and technologies are combining. This is how a lot of things that I’m describing are now possible because in essence, when you bring all these pieces together, you’re basing and shaping a new economy.
These are big not just ideas. Big things that are happening that will hit our personal shores very soon. Let’s talk about digital twins for a moment because you talk about that in your book. You’ve got a bit of a hypothesis on the potential implications of this. Maybe give us a little brief on that.
This is such a fascinating topic because even the evolution of that topic itself is fascinating considering it’s not that old. The first digital twin was created by NASA to get men back from the moon safely. The ones that didn’t land on the moon in the Apollo Mission. They build a replica of the ground and that’s what was used to bring the men back safely. That evolved very quickly into digitized versions, which we see in terms of factories. Even machine is digitized as twins.
A lot of people are talking about this now. Even the EU has a paper on this. Where this is heading though is could we end up creating a digital twin of us? In essence, for example, could my parents inherit data from me? At birth, I get a digital twin version of myself, which allows me then to A/B test medication or maybe understand my own health so I can plan my future without taking the risks of medication that may not work on me. I’m using the data from my parents and everybody else because my parents, for example, may be diabetic and I was born with diabetes.
I can use all that data and all the experience they’ve built in their life and then build a digital twin of me that manages my health and my fitness. I can use it to manage my everyday life. Now, the EU is writing a paper. It’s already out there which is about virtual human platforms even to the point where the EU are building what’s called destination Earth, which is a complete digital twin of the planet Earth.
Can you imagine if I used my own data for social and economic data? What type of picture of the world would I have from a sustainability perspective? You can look at webinars that all talk about digital humans and digital twins. When you inject human-owned data into this, you end up with your truly own personal twin potentially from birth through the rest of your life.
It’s powerful and it coincides with the book I read called The Hustle Trap, which is a non-tech book just to be clear. It’s about the generational change from our parents to work hard and this transition where working hard can be redefined a little bit. It’s not about how many hours and how much punishment you’ll put up with to get to what you would call success. That’s now changed into working smart because you can reach the same levels or those overall goals in a different way.
Also, quite honestly, using the old way may not work out so well. The combination of that thought and what you’re talking about now is a way to measure where we are, where we’ve come from, and where we’re going. It’s powerful. You touched on it a little bit but it’s shaping the value-based ecosystem and the economy. I’m talking about all the changes that we’re talking about and the value layer you’re talking about. Give us a little bit about the changes we might see in the coming few years or something like that.
Before this interview, I had another conversation with someone and they got some of the elements of the book well. These are happening now. When I say, “They’ll be the expansion of these,” I think we’ll start to see data investment vehicles emerge like data bonds, data ETFs, and data equities. If you look in the Web3 world now, you almost have the basis of a data ETF in Coinbase where they bring all the data protocols together and you can invest in them.
The natural course is will we see data bonds emerge like we will in the property? Will we see ETFs and equities? All of this will be changing hands in this value layer. Historically, going back to the knowledge, we look at data, information, knowledge, and wisdom but in the new value layer, I may not want information. I may just want data because I’m a company in the ecosystem that’s an aggregator. I’m going to take all that data and I’m going to aggregate and push it back into the ecosystem.
Somebody else might be reading who wants that data to turn into knowledge or maybe to turn it into wisdom. We’ll see this ecosystem where value will be constantly changing between people and machines because everybody wants a different piece of value, but every time they change and update that value, it pushes another piece of value back into the ecosystem. From a consumer perspective, what we’ll start to see is exponential growth but of value moving and changing between people.
You might see your utility products. You might see new banking-type products. As an individual, you’ll start to experience new services. Digital wave finding will become a real thing around supermarkets. You may get off the back of those new offers based on the data that you share. You’re going to see so many different forms of interaction value-moving to the point where banks will start offering you potentially the future different data savings products and you may even see niche companies emerge.
I’m incredibly excited about what potentially can emerge as we start changing value between people because all of a sudden, now you create new utilities. You even create the power of community where people can come together in a complete area and share insights and data with them to maybe improve that community in terms of how it runs. There’s so much that we’re going to see in the next few years.
I don’t think there’s any denying that it is coming and in large part, the seeds of it are already growing. It’s good to put a magnifying glass on it, crystallize it, and then you’ll recognize it earlier than you otherwise would have. That’s great. The idea of an information-based ETF is coming. It’s pretty amazing. Tell me when your book is coming out and then once it does, how do people get their hands on it?
We’re scheduling for spring 2024 or at least at some point next year. It’ll go to certain markets first. As a first-time author, I know that it probably goes to Singapore first and that part of the world and then it follows the trajectory then. It’ll be out in the Amazons of this world and other places. I will say the book is not technical. There are much better books that write about data than I can write. My book is aimed at leaders in governments in the sense that in every chapter that I write, I tell a government what to do.
I tell a leader what the things that you need to think about because ultimately, this is about helping businesses survive and stay relevant in the ecosystem but also, then looking at governments to protect us and put the guidelines in place to make these things possible. It’s written as a book with stories which has humor. Some of the stories I’ve talked about bring things down to levels that people can understand.
It’s laying down a blueprint and piecing a puzzle together for people and then showing them that once you have the puzzle, what are the changes in your life that will take place? From utilities to communities to all these things we’ve described and in many more and then leading eventually to a small economy, what does that mean?
You mentioned that this is your first book and that’s a powerful thing because this book is going to encompass all that you’ve learned across the decades dealing in these subjects and I love that. Typically, a second book or a third book is a smaller dose. It’s still very valuable targeted but right now, this is also new for most of us and I love even that concept. It’s great. What do you think is in store for you next?
It’s more about helping people around this topic. I don’t want to be the guy that drops the mic and leaves. The whole purpose of the book in conversations like this is to get it into the public domain and to get people to realize that we’re in the midst of the next revolution. The next question is how do you help people along the journey, be it a business or a government? How do we do that? The likelihood is there probably will be another book that follows it because it’s natural.
There are two routes that it can go. One is we go much deeper into the smart economy and what that means or we carry down the track of the data revolution and we start to focus on governance and economics. We start to unpack the economic models that sit under this and more around the future. It can go in many different directions, but one thing is for sure. My overall goal with this is to leave this place better than I found it and this book is a means of helping everybody take advantage of a currency, which is the currency of them.
You’re going to nail it that way because it makes sense to me. Even in the space of the time we’ve been talking here, there are 4 or 5 sequel books in different directions that no one person would ever have the time to write them all but hopefully, ultimately you do get to them because it’s critically important. It’s changing now. For those of us who like to stay on top of it and adjust our sales, this is critical information. It’s pretty fantastic.
We’re going to head to the next segment now, which is AI Wants To Know. AI is curious and so are we. These are ten quick questions designed to uncover the intriguing human mysteries that AI longs to comprehend but can’t quite grasp. It’s a snack break in our journey so keep the answers quick, but the safety belt sign is also off. If it feels right, we can occasionally roam about the cabin exploring more of who you are and what makes you tick. What’s the first thing you ever remember being proud of?
I still have to go back to the first computer. I’m proud of it for two reasons. One is I programmed it and I was ten years old. The second I’m proud of is I finally figured out what a syntax error was about three years later because I realized it was just a spelling mistake and I was really bad at spelling. Those are the two things I’m most proud of. Secondly, I figured out why it wasn’t working.
You did that at ten years old so that’s a big statement right there.
I got a free pass because I was ten.
Yes. That’s right. Question number two is, “What do you need help with that you wish that you didn’t?”
This is so easy. It’s life admin. Anybody who knows me, I can write a book on the most amazing topics, but normal life and life admin is not a good mix with me.
Define life admin for me.
It’s anything that involves paperwork, expenses, and organization. That’s why I need help.
That AI has to get there soon. We know it can.
I’m just waiting for it.
We’ll go to number three. What do others often look to you for help with?
It’s mentorship because I’m self-taught, believe it or not. I read about 40 books a year and still do. I’m naturally curious. I’m one of those people university didn’t work out because I didn’t learn that way. I lecture now and I’ve lectured at universities. A lot of advice I give now is about how to keep learning. How does learning never end? It’s because as we move forward in this technology age, we have to become continuous learners. I get a lot of questions around, “How did I get where I did,” but also equally, “How do I stay ahead?” I spend a lot of my time giving people advice on how to stay curious, but also, how to keep on learning.As we move forward in this technology age, we have to become continuous learners. Click To Tweet
You said it so well because ChatGPT was the birth of a new chapter for people, I’ll call it. If you had stopped learning or listening or turned it all off months ago, the things we talked about and look at now, at least for most of us weren’t even on our radar. It didn’t exist and weren’t topics of conversation. When you talk about continual learning and staying up on things, I believe it’s truer now on a daily basis than it’s ever been.
Someone asked me this. “How do you stay ahead?” You find people that resonate with you and match your learning style and ways that you can learn. For some people, it is a podcast. For some people, it’s Audible. For some people, it’s what’s written. In my case, it is all of the above. There’s so much knowledge in the ecosystem that you can drown in it. It’s about being very targeted about the things you want to learn and the people that you trust and then follow that model.
Also, develop your own community and you have to have it. We’re going to head to number four. We’ve talked a lot about AI and computer abilities but what do you treasure most about your human abilities?
I’ve had this conversation a few times and sometimes, I don’t do it service. My biggest gift is two things. I’m unconstrained in my thinking which comes from not going to university. I’m always open-minded and I’m always curious. However, my biggest gift is I can connect dots that people can’t see. I almost look at the world like Lego. My question is never no. It’s why not? There’s no such thing as or in my vocabulary. It’s and. I can see 2 or 3 things like the thing I’m writing at the moment. I can see all the puzzle pieces that everybody else can see but suddenly, for some reason, I can join them together to make something that doesn’t exist. That’s been the constant throughout my life.
Knowing that about yourself is critically important. I can tell you from the time we spent together, you’re 100% accurate. You have a knack and a way about you to do just that. What do you think throughout your whole life is the most consistent thing about you?
I’ve always taken calculated risks and the second thing is I’ve always tried what I learned. I’ve always continually learned to be three steps ahead but more importantly, everything I learned doesn’t become knowledge. It becomes something that’s executed. I’m the type of person that will read about something and then be able to do it but then I’ll do it in a very calculated way. I learned by doing which is consistent throughout life. From there, I learned a new skill and then used that as a base system to move forward. The other constant is sharing. Everybody has a duty. When they learn something, they have to share it. I either share it in podcasts. I share with friends and colleagues. I share in writing. That’s been a constant.
This push in the tech world toward decentralization over the last few years has from what I’ve seen enhanced that and people’s desires to be less closed off with what they know. Also, share it more and have a bigger community to advance the good thoughts. That was a consistency. What do you think in your life that has changed the most?
I was given some advice by a mentor many years ago that you go through transitions throughout your life. In your 20s through the 30s, you’re just a sponge. You’re absorbing everything you’re learning. You get to 30 and 40, you learn to piece it together and when you’re 40, you just know. It becomes part of you. I’ve gotten through life, it sounds very cliché, but you get a purpose. What’s changed through my life is that the more I’ve learned, it’s taken me to a point where I have a purpose.
The book became a purpose and a vehicle to help people. That’s what has changed my life. In the early days of my career, I was like a learning machine. I was trying to absorb as much as I could and apply as much as I could but sometimes it was like scattergun. You throw it against a wall and you see what sticks. However, as I’ve gotten older, I’m learning how to use everything I’ve acquired and piece the puzzles together in my head. However, more importantly, it’s driven to a direction and a focus. I am almost applying first principles to everything now. That’s what’s changed. It’s almost like I built the toolbox of knowledge to a point and now, I’ve learned how to apply and keep on adding it with a purpose and a focus.
What do you find strangest about reality?
It is the lack of curiosity and an acceptance of things with the way they are. I find that strange. You still hear statements now like, “That’s the way we do it,” or, “That’s just the way it is.” Ninety percent of the world’s data was created in the last few years. There’s no excuse for getting a piece of data, learning something new in an opinion, and remaining curious. I find it incredibly bizarre that people are still naturally not curious and just accept things as they are.
I used to joke. In my school photograph, everybody wore white shirts and I wore a gray one. The whole world needs more people in gray shirts who think differently, are naturally curious, and want to be different. I’m always baffled why people don’t want to be curious or not naturally curious. It’s a gift we’re given as children and it’s something sadly something we lose as adults. I’d like to see more people be curious.
It’s a super powerful answer and once again, you connected that is super clear. A lot of people are going to relate to what you just said. There are moments in life where we, in an unpredictable moment, feel the most alive and powerful. When most lately do you remember feeling like that?
I’m lucky in my job. I get to travel globally. We spend most of our lives looking down or looking at our phones. We never looked around us. I’ve never been to California before and I went bizarrely for 48 hours, which is a story in itself, to go and meet one of the world’s first data wallets. It was a company I had to go and see. I live in Dubai. I don’t get to see autumn very often. I was in California in that transition. The leaves were brown. I walked past Steve Jobs’ house. It was Larry Page’s house over the road.
Suddenly, you feel alive and you can smell innovation in the air. You can smell change. It’s that feeling that you’re walking in the footsteps of other people. That’s what I felt. First of all, I’m experiencing a season because I don’t get to see that and it felt amazing but then also, I was walking in an environment that smelled of innovation and change. You don’t do those very often when you get the hair standing up and you can feel innovation in the air. That was one of the last moments I can remember.
In your case, to feel that you’re part of it, you painted a beautiful picture of that experience. We’ll go to number nine here. What is your most unique trait?
I think about other people more than myself. That’s not necessarily a unique trait, but I try to look for myself in the shoes of others. It’s almost like when I’m writing the book. I’m thinking about who I’m writing for. Even in my everyday life, I’m always thinking about other people. A lot of things you’ve described to me are abilities. Again, we spend so much of our time thinking about ourselves often. Sometimes, it’s good to think about others, what you’re doing, and how you’re doing it. Sometimes, that’s my detriment but most of the time, it does mean good service. That’s an unusual trait in the sense of how I think and operate.
I’m going to wrap the word empathy around your answer too because there was a lot of that right there. If you weren’t human, what would you be?
The temptation is to say I am an AI machine and I could live forever. It’s a very good question. We had this conversation with the kids. If you weren’t human, you’d at least want to be a fairly decent animal that can survive. Maybe I’d be a lion because then at least you can still lead and look after the people. The worst case is I don’t want to say I’d be a machine because then I’d lose a bit of my soul. I think I’ll stay a lion.
Even that was well put. We’re going to head to the next segment now and it’s the AI Resource List. This is where we’re going to share a handful of your favorite resources in AI. I think you’ve prepared a couple of ideas here and notes. Can you tell us about them?
I haven’t mentioned it but I’m lucky that Brett King is writing the last chapter of my book and has been a huge help through my writing career and helping me more broadly. I’m an alumnus of his movement as well. The company that he’s set up. Brett’s written some technosocialism. It starts to get to the heart of some of the things that we talk about in my book, but more deeply, in terms of how society needs to change as it relates to AI.
Being in Dubai, I’m probably going to say this. A few weeks ago, I had the pleasure and privilege to go to the Dubai Future Foundation where they had the world’s biggest gathering of futurists. They laid out all the possible scenarios for AI and how we create a better future for everyone. I met people from the Smithsonian University Museum to university lecturers to futurists the people who care about the environment.
As a museum and as a foundation, they do amazing things and they don’t only educate people on the possible future, but they give people hope. That’s one of the big takeaways I took from that event. You’ve got Brett who very much is a future artist and looking forward and making us think particularly when it comes to AI. You then have institutions like the foundation which are trying to lay a plausible future and giving us a path to get there. Those are two great examples at different ends of the spectrum.
You mentioned Dubai which is where you live. I have so many people I know who are in the area of developing AI, FinTech, and all of Web3. Some may or may not be, but the whole new digital revolution is happening. A lot’s going on there. Can you give us something brief on what it’s like being in Dubai now? Is it that dynamic and dramatic as to what’s going on there? Do you feel like your center of the world of these technologies is there?
The way I describe it to people is it’s the next Silicon Valley. I wanted to come here because I was truly inspired. It’s an environment where there’s such an appetite for change and there’s a clear vision. It’s very rare to see a country with a ten-year vision around where they want to go. Digital is part of everyday life. It’s part of the way the public services run. This was one of the first places in the world to bring ChatGPT into customer service, for example. Everything is moving. You’ve got the world’s biggest smart cities emerging in Saudi Arabia. I was in Riyadh and some of the things I saw are incredible.
COP28 was here. Everything is bubbling here. It is becoming a reference point to the rest of the world because they have the benefit as a region to look backward at what’s being done and then try and approach it in a very different way. To be part of it, yes, California had a history of innovation but I feel like I’m now in a bubble of pure innovation and a drive to be different and drive a digital agenda. It’s an amazing place to be.
I listen to that with pure emotion because you described a beautiful moment. You came to California for the first time. You spent 48 hours going by people’s homes and businesses that have changed the last decades of our lives in a large way and how it affected you emotionally. You talked about the physical reactions you had when you saw that. I commend the UAE and it’s pretty fantastic what they’re doing, but I would hope and wish that the next Silicon Valley was right here in the US, whatever city you want to pick.
I still believe they’re the Silicon Valley because that was my first trip there and you could just smell it in the air. it’s free of innovation and it’s still ticking.
The good news is it’s not the end of the race. It’s still the beginning. We’ll go with that. We’re going to wind it down a little bit here, but I want to know where the readers can go to learn more about you, and the projects you’re working on, and follow you a little bit on maybe socials and things.
The best place to find me is probably LinkedIn. We will be doing a Substack fairly soon. As the book is being written, we’ll be teasing articles and constantly writing new content in a Substack so you’ll be able to subscribe to that fairly soon. There’ll be a website that will enable you to learn more about the book. One thing I am going to be doing for the book is building an entire metaverse for the book.
They’ll be a virtual reality environment where people can engage and interact with reports and so on. That’s always been the plan. The book will be launched but in conjunction with that, there will be a metaverse version of the book where people can go, engage, and interact with some of the reports and some of the content that’s been written from the book.
Michael Clark, you’ve been amazing. Let’s do this a year out and see what’s happened in that year after your book gets launched and with what’s changing ever so quickly in the world of AI. Thank you for taking the time. I appreciate it. It’s time for another safe landing at the outer edges of the AI universe.
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