Mo Gawdat: Ex-Google Officer Warns About the Dangers of AI, Urges All to Prepare Now! | E241
Mo Gawdat: Ex-Google Officer Warns About the Dangers of AI, Urges All to Prepare Now! | E241
Mo Gawdat is the host of the popular podcast, Slo Mo, and the author of three best-selling books. After a 30-year career in tech, including working at Google’s “moonshot factory” of innovation, Mo has made AI and happiness his primary research focuses. Motivated by the tragic loss of his son, Ali, in 2014, Mo began pouring his findings into his international bestselling book, Solve for Happy. Mo is also an expert on AI, and his second book, Scary Smart, provides a roadmap of how humanity can ensure a symbiotic coexistence with AI.
In this episode, Hala and Mo will discuss:
– His early days working on AI at Google
– How AI is surpassing human intelligence
– Why AI can have agency and free will
– How machines already manipulate us in our daily lives
– The boundaries that could help us contain the risks of AI
– The Prisoner’s Dilemma of AI development
– How AI is an arms race akin to nuclear weapons
– Why AI will redesign the job market and the fabric of society
– A world with a global intelligence divide like the digital divide
– Why we are facing the end of truth
– Why things will get worse before they get better under AI
– What you need to know to participate in the AI revolution
– And other topics…
Mo Gawdat is the former Chief Business Officer of Google [X] and now the host of the popular podcast, Slo Mo, and the author of three best-selling books. After a 30-year career in tech, including working at Google’s “moonshot factory” of innovation, Mo has made AI and happiness his primary research focuses. Motivated by the tragic loss of his son, Ali, in 2014, Mo began pouring his findings into his international bestselling book, Solve for Happy. His mission is to help one billion people become happier. Mo is also an expert on AI, and his second book, Scary Smart, provides a roadmap of how humanity can ensure a symbiotic coexistence with AI. Since the release of ChatGPT, Mo has been recognized for his early whistleblowing on AI’s unregulated development and has become one of the most globally consulted experts on the topic.
Mo’s Website: https://www.mogawdat.com/
Mo’s LinkedIn: https://www.linkedin.com/in/mogawdat/
Mo’s Twitter: https://twitter.com/mgawdat
Mo’s Instagram: https://www.instagram.com/mo_gawdat/
Mo’s Facebook: https://www.facebook.com/Mo.Gawdat.Official/
Mo’s YouTube: https://www.youtube.com/@MoGawdatOfficial
Mo’s Podcast: Slow Mo
Mo’s book on the future of artificial intelligence, Scary Smart: https://www.amazon.com/Scary-Smart-Future-Artificial-Intelligence/dp/1529077184/
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[00:00:00] Hala Taha: Young and profits. Today's episode is a super important one. AI has taken the world by storm, and while we see it changing the way we create content right now soon, AI will change every aspect of our lives, hopefully for the better. But without the right regulations and oversight, it could be for the worst.
Our guest today, Mo Gdat, is the foremost expert on the topic of AI and the ways it could impact the world. He's been coding before many of us have even been born. He served a 30 year career in tech, including his last stint as Chief business officer at Google X. Google's moonshot factory of innovation, literally one of the top tech jobs in the world.
Today, Mo spends his time writing books on topics like happiness and ai, as well as hosting the podcast Slow-mo. In this episode, we'll learn why artificial intelligence is not actually artificial. We'll understand how fast AI will become smarter than humans and why we actually can't stop AI at this point.
And since we can't stop ai, we'll gain an understanding of the skills we need to thrive in this infancy era of ai, as well as what we need to do to ensure that the advent of AI doesn't create existential threats or a future dystopia. I can't remember the last time I was this excited slash scared to have a conversation with someone.
This topic is so urgent, so relevant, and there's truly nobody better qualified than Mo to discuss this. So without further ado, Mo, welcome to Young and Profiting podcast.
[00:03:16] Mo Gawdat: Thank you. Thanks for having me. Uh, it's been a while in the making, but absolutely worth the wait.
[00:03:22] Hala Taha:
can you talk to us about your journey at a very high level, the, the highlights that got you in the C-suite at Google Acts?
[00:03:29] Mo Gawdat: Eventually at the height of my professional career. If you want my, uh, Corporate career. I was the chief business officer of Google X and
Of course I worked my butt off to get there, but there was an element of luck in the process. I met the exact right people at the exact right time. It was one of those events where the Google X team was, uh, presenting some of their confidential stuff. And I showed up and I said, at the time I was vice president of emerging markets for Google.
I had started half of Google's businesses globally, more than 103 languages, if I remember correctly. And so I was quite well known in the company. If you want, I had a reasonable impact that I have to say. I'm very grateful that life gave me the opportunity to provide. And then with Google x I basically, at the time, Google still had the idea of the 20% time, so I liked their projects and I said, I'm going to give you my 20%.
And they said, but we haven't asked for it. I said, yeah, that's not your choice. And I showed up basically the first day I showed up, I bumped into Sergei, our co-founder and I worked closely with Sergei for many years. And he says, what are you doing here? And I was like, I'm very excited about your work.
And ended up, he said, oh no, don't leave. Basically stay. And I was chief business officer for five years where I think Google X is misunderstood because we never really launched a product under X, if you want. So self-driving cars is under Waymo, Google Brain is integrated into Google and so on. But most of the very spooky innovation, if you want the very, very out there innovation, including all of robotics and a big chunk of AI was at x.
And uh, it was a big part of what I did.
[00:05:16] Hala Taha: And so diving right into ai, you were actually part of the labs that initially created ai. So can you talk to us about the story of the Yellow Ball and how that really changed your perspective about ai?
[00:05:31] Mo Gawdat: AI has been around a lot longer than people think. When we started self-driving cars back in 2008, that was basically with a belief that cars can develop intelligence that is as intelligent as a driver, and accordingly able to drive a car.
And since then, I mean by 2008, I think in my personal memories, I think 2008 was really the year when we knew that we cracked the code. Mm-hmm. Early 2009, Google published a paper that's known as the cat paper. That white paper basically described how we asked an artificial intelligent machine to look at YouTube videos.
Without prompting it for what to look for. And then it eventually came back and said, I found something. And we said, show us. And it turns out that it found a cat, not just one cat, but really what Cat Nest is all about. You know, that very entitled, cuddly, furry character basically could find every cat on YouTube.
And that was really the very first glimpse between that and the work that DeepMind was doing on playing Atari games where machines be started to show real intelligence. We then started to integrate that in a lot of things. You know, self-driving cars is probably the most publicly known example, but one of the projects that we worked on was, which is not the only, you know, Google X was not the only one working on it, but we wanted to teach grippers robotic arms, basically.
We wanted to teach them how to pick objects that they're not programmed to pick. And it's a very, very sophisticated task because, We do it so easily as humans, you don't remember, but if your parents will remember when you were a child and before you learned how to grip, you kept going on trial and error.
You would try to grip something and then it falls and then you try again and so on. And basically we said maybe we can teach the machines the same way. We built a farm of those grippers, put boxes of items in front of them. A funny programmer basically chose children's toys and you could see them try to pick those items and basically fail over and over.
It's a very sophisticated mathematical problem. And so they would fail. They would show the arm to the camera, and the camera would know that this algorithm, this pathway didn't register, didn't pick the item until I think it was several weeks in. And you know, it was a significant investment because robotic arms were not cheap at the time.
I passed by that farm very frequently on my way to my desk. And on a Friday evening, finally one of those arms, you know, I can see it, Z goes down, picks one item, which was a yellow softball again, mathematically very complex to a grip and it shows it to the camera. And so jokingly, I pass by the team that's running this experiment and I say, okay, well done all of those millions of dollars for one yellow ball.
Okay. And they smiled and then, you know, sort of nodded their heads. And on Monday morning as I went to work, every arm was picking the yellow ball. A couple of weeks later, every arm was picking everything. And I think that's something that most people don't recognize about AI is that the speed, once you found the very first pattern, the speed at which AI starts to develop is just mind blowing.
Also, I think most people don't realize that they learn exactly like my children learned to grip. That's the whole idea. They really do develop intelligence that comparable, uh, now probably even more advanced than human intelligence.
[00:09:13] Hala Taha: In that moment when you saw those machines gripping toys and doing it more efficiently and with intelligence, were you alarmed or were you excited?
[00:09:25] Mo Gawdat: I've been excited about AI since I had a Sinclair, believe it or not. So I, I started coding at a very, very young age on computers, young and profitable, probably have never touched in their life. So, so, uh, you know, and every one of us geeks wanted to code an intelligent machine. Uh, we all attempted and we all simulated and we all even pretended sometimes.
But then it was the year 2000 truly where deep learning was starting to develop and we sort of found the breakthrough. We found how to give machines intelligence and, and allow me to stop for a second here because a huge difference. Between the way we programmed machines before deep learning and after deep learning.
Before deep learning. When I programmed the machine as intelligent as it looked, I solved the problem first, using my own intelligence and then sort of gave the machine the sheet in terms of how to solve it itself. I wrote the algorithm, or I wrote the process step by step, and basically coded the machine to do it.
When deep learning started to happen, what we did was we didn't tell the machine how to solve the problem. We told the machine how to develop the intelligence needed to find a solution to the problem. This is very, very different, and as a matter of fact, most of the time we don't even recognize how the machine finds a cat.
We don't fully understand how Bard, uh, Google's Bard understood how to speak Bengali, right? We don't really know those emerging properties or even the. Tasks, we give them themselves. So your question was, was I excited? I promise you, the day I met Des, who was the c e O of DeepMind, when we acquired DeepMind, it was really to me like meeting a rockstar.
I was fanatic about what he was doing. I still am a fan of him and his ethics and amazing human being. But at the time, for a geek understand this, AI was the ultimate joy and glory. This was it. We were creating intelligence. And for a programmer that was mind blowing. And remember, huh? Every time we saw the machines develop, we got more excited, believe it or not, because we wanted what was good for the world intelligence in itself.
There is nothing inherently wrong with intelligence. It was, when I saw the yellow ball, I think that something dropped. I could see it so clearly because for the first time ever, I realized that those machines, one, are developing way faster than us. And so accordingly, the predictions of people like Ray Kors wire and others of a moment of singularity where they're going to bypass our intelligence became very, very real in my mind.
I could see that this is going to happen, but I also could see that we, the moment they became intelligent had very little influence on them. Okay. And accordingly, I started to imagine a world where humanity is no longer the top of the food chain. Humanity is no longer the smartest being on the planet, and then comes the apes.
We are going to be the apes. Do you understand that? Yeah. And I think that completely made sense to me that this needed a lot more consideration rather than the, you know, the excited geekiness of building it. We needed to understand why and how. Are we building it? And what is a future where it becomes in charge?
[00:13:05] Hala Taha: There is so much to unpack here. This is why I was like, I need to spend the full hour on this topic. 'cause there's just so much to unpack. Let's talk about the label of artificial and artificial intelligence. Is intelligence artificial at all to talk ai? Oh yeah. Talk to us about that.
[00:13:22] Mo Gawdat: Not in the slightest.
If there is any artificial site to the machines, is that they are silicon based. As a matter of fact, most of the ones who worked on deep tech, not the stuff that you see in the, in the interfaces, we almost mapped their brains to the way our neural networks as humans work. So you know, humans in the early development of ai, you know what neuroplasticity is?
Humans. Basically, we develop. Our intelligence and our ability to do anything really by repeating a task in a specific way and, and they say neurons that fire together, wire together. So if you tap your finger over and over and over, your brain sort of takes that neural network that taps your finger and makes it stronger and stronger and stronger.
Just like going to the gym and the early years of developing ai, we were doing exactly that. We were literally pruning the software or the algorithms that were not effectively delivering the task we want. Literally, killing them, erasing them, and keeping the ones that were capable of getting closer to the answer we wanted, and then strengthening them.
So we were sort of like doubling down on them, wiring them together. And the way the the machines work today is very, very similar to that. It's a bunch of patterns that are created in hundreds of millions, sometimes billions and trillions of, of neurons, not yet trillions, but you know, lots of nodes of patterns that the machine will recognize so that it basically can make something look intelligent or can behave in a way that is analogous to intelligence.
Now, is it artificial? Well, I think if you ask the machines, they will think of our carbon based intelligence as artificial. The only difference really is we are carbon based and analog. They are. I don't think we're analog. I think we're somewhere in between, and they are digital and silicon based, not for long.
We don't know what they're going to be based on in the future, but also I think their clock speed is very different than human clock speed. So they have. An enormous capability of learning very, very quickly of crunching a massive amount of data that no single human can achieve. They have the capability of keeping so much in their memory.
They are aware and informed of everything all the time. They are connected to each other so they could in the future. When a g I becomes a reality benefit from each other's intelligence, and in a very simple way, I think the race to intelligence is one. Today there are estimates that check g p t is at, at an IQ of 1 55.
Einstein, I think was one 60 or one 90 doesn't really matter, but most humans are 1 22. Some are. Less than that, maybe one 10 and so on. You know, the dumbest human is 70, so you can easily see that there is an AI today from an intelligence point of view on the task assigned to it. Remember, we're still in the artificial special intelligence stage one, one task assigned to every AI in the task assigned to it.
It's by far more intelligent than humans. Nothing artificial at all about that. It develops its own intelligence. It evolves. It has agency, it has decision making abilities, it has emotions, I tend to believe, and it is in a very interesting way, almost sentient if you think about it, which is an argument that a lot of people don't agree with because we don't really define sentient on a human level very well, but they definitely simulate being sentient very well.
[00:17:16] Hala Taha: What you're saying is really incredible and mind blowing. I know that for humans, we don't understand how consciousness works, right? Nobody can say you're conscious because of this.And you mentioned before that we don't understand how intelligence really happens.
We know how to create intelligence but we don't actually know how the intelligence works. It just sort of takes off on its own, which can be really scary. So talk to us about why you think AI should be considered living or sentient.
[00:17:46] Mo Gawdat: I think the definition of sentient needs to be agreed is a three. Sentient is a pebble, sentient is the planet Earth sentient. You know, we could have many arguments now I. If you think of being sentient as it is born at a point in time and it dies at a point in time, or at least it has the threat of dying at a point in time, then AI is born at a point in time and it has the threat of dying at a point in time.
If you think of sentient as the ability to sense the world around you, well, yes, uh, of course AI is capable of assessing the world around it. If you think of sentient as the ability to affect the world around you, then yes it can. Right? If you take a tree, for example, at three grows, it reproduces. It is in a way, interestingly aware of the seasons and aware of the environment around it, and it responds to it.
So a, a tree will not shed its leaves on the 21st of October specifically, it'll shed its sleeves when the weather alerts it to do that. And if you consider a three sentient in that case, then. AI is surely sentient if you consider that a gorilla is incredibly interested in survival and accordingly would do what it takes to survive.
Then AI is sentient in the sense that once assigned a task, it'll attempt to survive to make the task happen basically.
[00:19:15] Hala Taha: It's so interesting and I know that a lot of people who think of ai think of it as a machine that they can turn off if things get crazy, just tell it what to do. Can you talk about how AI can have agency and free will?
[00:19:31] Mo Gawdat: Oh my God. I can give you endless examples. If you're not informed of AI today, it is a bit like a hurricane approaching your city or village, and you are sitting at a cafe saying, I'm not interested. Okay, this is the biggest event happening in today's world. The reason for that is that there are tremendous benefits that can come from having artificial intelligence in our lives.
And if you miss out on that train, you are not gonna have the skills to compete in a world that is changing very rapidly. That's on one side. On the other side, there are very, very significant threats, and those threats come in two levels. The news media wants to always talk about a terminator scenario, or it's an existential risk to humanity in 10, 15, 20 years time.
I believe that there is a probability of that happening, but I believe that there are many more important, more immediate threats that need to be looked at today. Things that are already happening and that we need to become aware of. Things like concentration of power, things that like the end of truth, things like.
The jobs and the redesign of the fabric of society as a result of the disappearance of many jobs and so on. So we'll come to all of those. I think we need to cover both sides of the immediate risk and the existential risk. But your question was, how can AI affect me today? Let me give you a, a very simple example.
There is nothing that entered your head today that was not dictated to you by a machine. We ignore that fact when we swipe on Instagram or when we are on TikTok, or when we're looking at the news media or when, you know, we're searching and getting a result, uh, from Google. But every single one of those is a machine that is telling you in reality what it is that you should know now.
Think about the following today. In the morning I got a statistic that basically is quite interesting, a study by Stanford University that said that brunettes are on average, taller than blondes, right? I didn't actually, but does it make any difference? Once I told you that piece of information, you know, once I tell you a piece of information, I have affected your mind forever.
So you can either trust me and now you're going to look at brunettes and blondes differently for the rest of your life. You can mistrust me and then you're going to spend a little bit of time to try and verify the truth and in the back of your mind that bit of information is gonna be engraved. Maybe for the future you might dedicate yourself to a research that proves me wrong.
You may actually become fanatic. You may start posting about it on the internet. You may spend your, the rest of your life trying to defend this lie or. Trying to disprove this lie and show the truth just by by showing you one bit of information. Now, every bit of information you have seen since you woke up today is dictated by a machine.
Now you have Noah Hari basically says they have hacked the operating system of humanity. So if I can hack into your brain halah and tell you something that affects you for the rest of your life, whether positively or negatively, whether true or false, then I've already managed to affect you.
Interestingly, most of those machines that you've dealt with are programmed for one simple task, which is to manipulate you. Every one of those social media machines, for example, are out there with one objective, which is to manipulate your behavior to their benefit, and they're becoming really good at it.
They're becoming so good at it. As a matter of fact, that most of the time we don't even realize that we have been brainwashed over and over and over by the capability of those machines. So here's the interesting bit. I told you in the immediate risks that are coming up, I believe they have started already and they, I think they will start to become quite significant over the next year or two.
And we will see my personal view, what I call patient zero is the end of the truth in the US elections. So the reality of the matter is that with deep fakes, with the ability to manipulate information and data, with the ability to create by next year, you have to be aware that a reel on Instagram can be created with no human in front of the camera very, very easily.
Technologies like, uh, stability.ai. Stable diffusion, for example, can now generate realistic human-like images in less than a 10th of a second. And a video is 10 frames per second. So the next stage is clearly going to be video. There are multiple videos that have been created that you couldn't distinguish, but the quality of from an actual iPhone video of you.
Now think of face filters and how this is affecting our perception of real beauty. Think of information and statistics using Chad G P T affecting the children's way of doing their homework. We are completely redesigned as a society and we're not even talking about it. This is how far this is has gone.
[00:25:11] Hala Taha: It is insane. And I definitely wanna talk about those risks that you were talking about. Immediate risk, job risks, existential risk down the line years later.
talk to us about the fact that AI can learn on its own. It can learn languages on its own, it can beat chess players and come up with moves that we've never taught it before. Because a lot of people think about AI as something that just collects information and spits out information, but it can actually learn new things that humans don't even know.
So talk to us about that.
[00:25:41] Mo Gawdat: Don't mix AI with old programming. AI simply is the idea. Let me give you a concrete example. There is a, a strategic game known as Go Go is one of the most complex strategic games on the planet. It requires a very deep understanding of. Planning and crunching a lot of numbers and mathematics and so on.
Very popular in Asia and in our assessment Go was the ultimate task. You know, like we had the touring test for AI pretending to be a human and you're, you not being able to figure out if it isn't go was sort of like that other milestone. If AI wins in Go, then AI is now the top gamer on the planet now.
It was several, five years ago. Uh, I believe that, uh, 10 years ahead of any estimate that Alpha Go again. DeepMind basically became the world champion in Go and Alpha Go. Had three versions to it, version number one took a few months to develop. Basically we asked it to watch YouTube videos of people playing go.
And from that it played against the second champion in the world. So the, uh, the runner rapon and it won five to one or five to two, but it basically won. And that basically made Alpha Go number two in the world. And then we developed something called Alpha Go Master and Alpha Go Master played against Lee the world champion and won.
That was around a few months later. And then we developed another code that was called AlphaGo Zero. And AlphaGo Zero basically learned the game by playing against itself. So it never saw a human ever playing go, it's just played against itself. So it would be the two opponents and through the patterns of the game, randomly, it would learn what wins and what loses.
Alpha go zero within three days. Three days won against Alpha go. The original within 21 days, won against Alpha Go Master and became the World champion. A thousand games to zero within 21 days now. When you understand that level of strategy, when Lee, the world champion or who was playing against Alpha Go master, there is something that you can Google that's known as Move 37 and move 37 was that machine coming up with a move that is completely unlike anything humans understand.
To the point that the world champion said, I don't know what this is doing. I need a 15 minutes break to understand it was a, a move of ingenuity, of intuition, of creativity, of very deep strategy, of very, very deep mathematical planning. And we never taught Alpha Goma to do that. We never taught the original games of Atari DeepMind to find the cornerstone in the breakout game, if you remember those Atari games.
So it would find the cornerstone, throw the ball in there so that it hits the ball from the top. All of those things. We don't teach the machines how to learn. And we call those emerging properties. And emerging properties are basically things that the machine learns on its own without us actually telling it at all to learn it.
One of the famous ones was, uh, Sundar Phai, the c e o of Alphabet talks about Google's AI and how that ai, we discovered, or they discovered I was not no longer at Google at the time that it speaks Bengali. We never taught it Bengali. We never showed it, uh, data sets of Bengali. It just learns. Bengali, uh, Chad, g p t is learning research chemistry.
We never taught it research chemistry. We never wanted it to, it just learns just like you and I, Hal. So if I ask you a question and you give me an answer, the answer might be right or wrong. It doesn't matter. But I can find out if the answer is right or wrong, at least by, by my perception. But I can never find out how you arrived at it.
I don't know what happened in your brain. To get to that answer. This is why in, you know, in elementary school, in math tests, they ask the, the student to show the thinking they, they went through. So when you think about that, you realize that those machines are completely doing things that we don't tell them to do.
Interestingly, however, the answer from a computer science point of view to the problem of a, a risk of AI is known as the solution to the control problem. So, most computer scientists spent a lot of time trying to make AI safe. How do they make it safe by including control measures within the code?
Theoretically. By the way, I do not know of any AI developer that ever included a, you know, control code within their code because it takes time and effort and it's not what they're paid for, basically. But here's the question. How do you control something that is bound to become a billion times smarter than you think about a chat?
G P T four was 10 times smarter than chat G p t 3.5. If you just assume that this pattern will repeat twice, there will be an AI within the next year and a half to two years that in the task of knowledge and cognition of information is going to be at an IQ of 1,500. That's not even imaginable by human intelligence.
This is basically like trying to explain quantum physics to a fly. That's the level of intelligence difference between us and them. Just like it's so difficult for someone like me who's a, has an avid love of physics. When I look at how someone like Einstein comes up with theory of relativity, I go like, man, I never, I wish I had that intelligence.
And that's the comparison between me and Einstein. Imagine if I compare myself to something a hundred times smarter than Einstein. My prediction and the prediction of many other computer scientists is that by the year 2045 at the current trend, AI will probably be a billion times smarter than us, 1 billion with a B.
So it's quite interesting when you really think about it, how the arrogance of humanity still imagines that it can control something that is a billion times smarter than us. So I don't wanna be grim. I wanna talk about the positives here because it's really important. There are ways to control ai, but they are not through control.
They're a little bit like how, if you have any friends from India or the Middle East, where we are taught at a young age that we need to take care of our parents when they grow older. So there are ways, if we consider that AI has a resemblance of being our artificially intelligent infant children, there are ways we can influence them so that they choose to take care of humanity instead of, in all honesty, making us irrelevant.
[00:32:35] Hala Taha: Yeah, and I know. You've talked about how now we're sort of at the point of no return, so related to this, can you talk about the boundaries that we've broken that now make AI sort of uncontrolled and unregulated?
[00:32:51] Mo Gawdat: Yeah. I, I don't know how stupid humanity can be, honestly. I really, I honestly don't understand in a very interesting way.
I think we've created a system that's removing all of our intelligence. We continue to consume as we are burning the planet. We continue to favor the patriarchy when we, when we realize that the feminine attributes are so badly needed in our world today, we continue to create AI when we have no clue how that will influence our world going forward.
But more interestingly, we continue to make mistakes along the path of AI that are. Irreparable, honestly, and everyone, everyone, without exception, and at least let me say everyone I know, said, okay, as long as it's in the lab, that's fine. We can do whatever, just explore the boundaries of it. But there are three borders, three boundaries we shouldn't cross, which were one, don't put it on the open internet.
I mean, seriously, when you ingest a medicine or a supplement, it needs to go through f d a approval, right? Someone needs to go and say, this is safe for you. So we said at least there needs to be some kind of an oversight that basically says, this is safe for human consumption. This is safe for humanity at large.
And none of that happens. And, and I understand Sam Altman's, which I believe is a good person. His approach of saying, let's develop it in public so that nothing is hidden, so that we learn early on. But the problem is it's developing faster than us. And I think the reality of having something as powerful as Chad, g p t out there to be accessed by everyone is completely reshaping everything.
That's number one. Number two, we said don't teach them to code. At least if you teach them to code, don't keep them on the open internet so that they can code. Now, here is what is, just so that you understand how far that mistake is, 41% of all of the code on GitHub today. So, so basically the repository of where developers share their code, 41% of it is machine developed within a year, almost less than a year, huh, of having the mach allowing the machines to develop.
Four of the top 10 apps on the iPhone are AI enabled, created by a machine, created by a machine. For now is amazing because, you know what? I always loved to do the algorithm, the, the design of a code, but coding itself was annoying. Now you can tell the machine, build me a website that speaks about hell as podcast.
That is blue and yellow in color, and that is 15 web pages long and it'll do it in less than a minute. And it's not only that, it's a lot of the base programming like Chad, g p t, 75% of the code offered to Chad g p t to correct or to review was made two and a half times faster. So basically every time it reviews a human code, it makes it two and a half times faster almost.
And when you really think about that, they are becoming the absolute best developer on the planet when it comes to basic development. And I'll come back to the risk of that in a minute. The third is we said, don't have ais, instruct ais. What to do? We call those agents. So basically you now have something that has access to the entire worldwide web that has access to the entire world, basically that can write its own code.
And so basically sort of have its own children because it is made of code and it's able now to create other versions of itself, put it wherever it wants. And number three, it is instructed to do that by machines, not humans. And so what is happening now is that machines are telling machines to write code to serve the machines and affect the entire worldwide web.
And we are not part of that process and that cycle at all. For now, nothing went bad, but do we really have to wait for the virus to begin before humanity stops and asks and says, is this. Reasonable in any way. I mean, does it make any sense to anyone that this is the situation we're in? Where are our governments?
How can those companies be accountable? Because I think the biggest challenge we have today is that our fate is in the hand of people who don't assume responsibility. You know, spidermans, uh, with great power comes great responsibility. Now there is great power in the presence, not even the future of artificial intelligence that is within hands that don't assume responsibility.
If something goes wrong today with the artificial intelligence that's out on the open internet, who's responsible for that? How can we even find out where that code generated from? All of that, by the way, just not to scare people. All of that hasn't happened yet. It hasn't happened yet, but it is very, very unlikely that it will not happen.
It's very unlikely that one of those codes. If you just simply tell Chad g p t to keep writing code to make you more money, eventually somehow something in the system will break. And if you are not the one telling it, if a machine is telling it something is gonna break, we absolutely have to start getting this under control.
[00:38:22] Hala Taha: Yeah. Like you said, it's sort of like uncontrollable. It's no wonder why you called your book Scary Smart. 'cause this is really scary.
you talk about inevitable AI will happen, it will become smarter than us, bad things will happen.
Can you unpack those thoughts and then I'd love to go into the risks and solutions.
[00:38:43] Mo Gawdat: Potentially. There are three inevitable AI has already happened, not just will happen, but when I wrote the First Inevitable, I wrote it with the intention of explaining and there is no stopping it. So there is no way you can say, okay, AI is out there and it's growing and it's becoming more intelligent.
Let's, uh, just switch it off. There is no off switch. That's number one. And what is needed at the moment is for the entire world to come together and simply say, Hey, you know what? This is too risky. Let's leave our F side and come together and just wait a little bit. Right? Which has been attempted by the open letter Max Denmark and Elon Musk and others, which of course was answered very quickly by the top CEOs by saying, I can't, why?
Because we've created a prisoner's dilemma. This is the first inevitable. It is an arms race where Google cannot stop developing AI because meta is developing ai. America cannot stop developing AI because China is developing ai. Nobody actually, even I. If you wanna consider, there are good guys in the world.
Nobody can stop developing AI because there could be bad guys developing ai, right? So if there is a hacker somewhere trying to break through our banks, someone needs to develop a smarter AI that will help us not be hacked. And so this basically means that it is a human choice because of the capitalist system that we've created that we will continue to develop ai.
It's done. There is no stopping it. And I think the open letter was a great example of that.
[00:40:21] Hala Taha: Can I pause you there in case nobody knows? So the open letter was basically earlier this year, top AI scientists, executives from Open AI Deep Mind. They basically had an open letter warning of the risk of extinction, I think, and that AI was just as powerful as having a nuclear war, that this was the risk at hand.
So can you talk to us about that letter? Like I didn't even hear about that letter until I started studying your work. If the most powerful people in the world who are actually the most knowledgeable about AI are warning about this, I guess like why wasn't anything done or like what happened with that letter?
[00:40:58] Mo Gawdat: So the letter basically, like you rightly said, it is some of the most powerful people in the field who, like me, I walked out in 2000, end of 2017. Others like Jeffrey Hinton and so many others are starting to wake up to that in 2023. I think Chad g p t was basically the Netscape moment. I, I know you guys are too young for Netscape, but the internet was there for 15 years before Netscape came out.
And when Netscape came out as a web browser, we realized that the internet existed. The reality is that this is the Netscape moment of ai. Uh, Chad, g p t basically told us what the possibilities told the general public, what the possibilities are. And so suddenly we all realized this stuff exists now. For all of the scientists that started to recognize that it is truly, I mean, the moment of singularity where AI becomes smarter than us, artificial general intelligence that's capable of doing everything humans do better than humans is not contested.
Most scientists will say it's 2029. I say it's 2027 or earlier, that there will be a moment in time within the next 2, 2, 3 years where there will be a wake up call where we suddenly realize that AI is much more intelligent than us. Most scientists have started to recognize that, and so they basically issued a letter urging all of the top AI players to pause the development of AI for six months so that the safety code, the control code can catch up because.
There has have been quite a few that have been putting in effort to create that control code. But let's say 98% of all investments, uh, in the last 10 years has gone into the AI code, not the control code. And so the control code was lagging. And so the letter was basically saying, can we pause for six months to figure this out before we continue to develop ai?
And of course the answer was very straightforward. The first I think I heard was, uh, Sonder pda, C e O of Google, which is someone I respect dearly, and I think he's an amazing human being. And Sonder basically came out and said, I can't stop. How can I stop if you can't guarantee me that meta and Amazon and all of the others are going to stop too?
And by the way, even if they stop, how can you guarantee me that two little kids in Singapore, in their garage are not developing AI code that can disrupt my business, my responsibility, my accountability, if you want to, my shareholders. Requires me to continue to develop the code. And I think that reality is the prisoner's dilemma, dilemma that I'm talking about.
It is the first inevitable. It's an arms race that will not stop. Not because we cannot stop. We can, if we all agree for once in humanity's lifetime that this is existential and that this requires us to stop, we will stop. It's really not that complicated. Wake up in the morning and have a cup of coffee instead of writing AI code.
It's very simple, okay? But the first inevitable means that the arms race is not going to stop. Even as you look at humanity's biggest success in that dilemma dilemma, which was nuclear weapons, where humanity suddenly got together, you know, very late in the game and said, Hey, this is existential. It can threaten the entire existence of humanity.
Why don't we slow down? Stop. We didn't really stop. We just allowed the big countries to continue to develop nuclear bombs when the smaller countries were banned from doing it. But at least when it comes to nuclear weapons, we had the the ability to detect any nuclear testing anywhere in the world. So at least we became aware that's not the case with AI today.
I also said once in an interview that it's not just the risk of humans developing risky ai, it's now the risk of AI developing risky ai. So it's basically a nuclear bomb that's capable of building other nuclear bombs, if you want.
[00:45:09] Hala Taha: It's crazy to think, and I know the other inevitable is it will eventually become smarter than us, which we talked about.
So let's talk about the bad things that could happen from ai, which is your third inevitable. And I think a lot of people, when they think of threats of ai, they think about the existential threats that there's gonna be robots taking over, killing off humanity, making human slaves. Let's talk about some of the more immediate threats that we need to be concerned about.
[00:45:35] Mo Gawdat: Yes. I don't speak of the existential risks for two reasons. One is they diffuse the focus on the immediate important threats, and two, they're less probable. As a matter of fact, they are so improbable that they're basically not worthy of discussing today because we, we may not make it that far if the immediate risks are not attended to.
And there are many immediate risks. But I, my top three have consistently been the redesign of the job market, and accordingly, the redesign of purpose and the fabric of society. Two is the idea of AI in the wrong hands based on who you think are the wrong hands. The third is the concentration of power and the shift of power upwards, which I think is very important to understand.
And the fourth is the end of truth. So let me go through those very quickly. Let me start with the concentration of power. If people don't understand how our world has worked since the, the agriculture revolution, it's always been kings and peasants. Landlords and peasants. The difference between them is that the peasants worked really hard to saw the seed and and collect the harvest when most of the profits, most of the wealth went to the landlord who owned the automation and the industrial revolutions joined.
You know, our world, the automation became the factory or the retail store, and so on and so forth. And so whoever owned those actually made all of the money. Not the one that made the shoe, but the one that sold the shoe or owned the factory that made the shoes. And every time the technology enhanced that automation, the distribution of power became even bigger.
So the landlord needed to own a lot of land to become. Much richer than the peasants. You know, you could own two factories and become much richer than the peasants. Uh, you can own an internet app, you know, like Instagram and become much richer than the peasants. And now with ai, all of us are gonna be happily chatting away and putting prompts in chat, g p T.
But the ones that own the automation, the, the digital soil if you want, are gonna become very few players. Amazon, Google, and so on and so forth. Meta and so on that, that's on the Western side. Of course, you have a few on the Chinese side, a few on the Russian side, and so on. So there is a very significant gap between those who have and those who don't have powered by the loss of jobs, which I'll come to in a second.
But that significant gap is not gonna be only on money. It's also going to become. On intelligence on the commodity that we've now commoditized, that's called intelligence. So you can easily imagine that, you know, if Elon Musk's view of Neuralink where, where we can connect AI to our, our brains directly, which by the way is very, very possible in its in testing that if one human is capable of producing that, just imagine the extreme that human would become so much more intelligent than the other humans, that it becomes natural unless that human is Jesus or Buddha or some very, very enlightened being that this human will basically say, okay, I want to keep that advantage, at least I don't want to distribute it too widely to every human on the planet.
So that I think is a very interesting, inevitable threat. What we used to call the digital divide when the, when technology started, is now going to be intelligence divide. It's going to be power divide in a very, very big way. This also applies to nations, and this is the reason for my first inevitable, is that in simple terms, if one nation discovers an AI or creates an AI that's capable of ceasing control of the other nation's nuclear arsenal, that that's it, that's game over.
War is done, and this is why it's an arms race. So this is one other derivative of that. So power is going up, but jobs are disappearing. Why? Because if you're a graphics designer or if you're a developer, or if you are a, a lawyer or if you are a, a researcher in a bank or whatever, the machines with their current intelligence can do those jobs much better than you.
And so in my personal view, there is clearly going to be a disappearance of a very large. Number of jobs that government needs to prepare for, you know, something like universal basic income, but also the idea of usefulness and purpose of humanity. So how are we going to continue to want to wake up in the morning when most of us have defined wrongly, by the way, defined our jobs as our purpose?
Now, when I say that, most people will tell me, oh, but no, that happened before. You know, when Excel came out, everyone said, okay, accountants are going to disappear. You know, they found other skills and found other jobs basically. And I agree, by the way, just understand the following. There was a time when the strengths, physical strengths was the distinctive reason why you would hire someone.
Then there was a time where when became information workers where skills and knowledge and so on became the distinction, and now we're taking that away. So skills and knowledge. So I don't know what else is remaining in a human so that we can find another skill when intelligence is outsourced. Machines.
So when that happens, by the way, I believe that this takes us back to the origin of society where we really did not know how to work madly as we do now. So this is actually not a bad thing. It's just a very, very serious disruption to humanities, day-to-day income and economics and uh, the way we spend our hours and so on.
And if we do this right, by the way, and AI becomes the intelligent agent that's going to help humanity, then there could be a time in the near future where you walk to a tree and pick an apple and walk to another tree and pick an iPhone. And all of that is for free almost because the cost of making an iPhone from a particle point of view is not different than the cost of making an apple.
And so with nano SICs, you can do that, and with intelligence you can figure that out. So there is that bright possibility. If we avoid the concentration of power and actually focus on humanity's benefit at large, if we don't, anyway, I think it's the role of government to jump in and say, in the immediate future, those companies that get a very significant upside of using AI need to compensate for the workers that are out of jobs.
The third one is the absence of truth or the disappearance of truth. I think we, uh, the end of truth, as I call it, I think we all know that. I think we see it every day from, as I said, face filters to deep fakes and so on and so forth. And, and my call there is that it needs to be criminalized to issue any AI generated content without actually saying that it's ai.
I don't mind to be informed by AI all the time, but I wanna make sure that this is a machine, not the human. And AI in bad hands as the fourth one is actually quite risky because define what is bad. So we understand that AI in the hands of a criminal. Who's trying to hack your bank is a bad idea. But with all due respect to all nations, if you ask the Americans who's, who are the bad guys, they'll say the Chinese and the, and the Russians.
If you ask the Russians, who are the bad guys? They'll say The Americans. So, you know, we don't really know who the bad guy is and everyone is racing to be ahead of that bad other guy. And I think that's basically, I think the biggest challenge we're going to have in the midterm is how using AI for individual benefits that are against the other guy, we will just get caught in the middle of all of that.
[00:53:32] Hala Taha: Yeah. And I have so many questions for you. We have 10 minutes left, so I'm gonna try to be really strategic about what I ask you. So number one, and I think that this, my listeners are gonna really wanna understand this is in the next, you know, one to five years, what does AI do to human connection? And what about the skills that you think will be the most valuable in the next one to five years?
[00:53:55] Mo Gawdat: I think those two are the same question, actually. Exactly. Yeah, because what will it do to human connection? It may fool us drastically, huh? It may tell us, I actually think this is the first time I speak about this. I'm working on something that I call pocket mode. Pocket mode basically is an AI that read all of my books or listen to all of my podcasts, all of my videos, all of my public talks, and basically are, is going to be in your pocket so you can, you can ask it any question about happiness and wellbeing and stress and so on and so forth.
That's a great thing in my view. It's an amazing thing if you believe in my methods to have answers in your pocket. Amazing. Right? On the other hand, within five years, this thing is gonna be so good that I am not needed at all. At all. As a matter of fact, most of the time I think about my skills as an author and I was working on a, on a book called Finding Love Chapter 10, which means two chapters to go.
I stopped, I decided, no, in the age of ai, I shouldn't try it this way, I should start over. So I'm now writing a, a book that's called A Dating Guide for Straight Girls, which is a subset of the, of finding love that is very specific, 80 pages long. You read it within one day. It takes me 10 to 15 days to write, and it changes your life forever.
So a very different approach because I believe that if I were to compete in this world, I need to compete at that speed and at that ability to share my very personal human connection, which I believe is going to become the top skill in the world forever. Why? Because there was a, I don't remember. I think there was a, a song by, by AI that mimicked Drake, which was as good as or better.
Uh, I haven't heard it because I don't listen to Drake. I'm not young and profiting. Basically, does that mean that Drake is over? Not at all. As a matter of fact, what that means is that the music industry will go back to the fifties, sixties and seventies. You don't remember, but you know, when the Beatles were touring and you know, and doing live shows every other day and so on.
Why? Because the, the fans will want to see the beat's life. Yeah, there will be holograms, but we will still want that human connection. And in my personal view, the top skill, the top skill in a world where intelligence is becoming a commodity that's outsourced to the machine. The biggest, biggest skill is how you and I connected very quickly, how I felt comfortable around you.
How we can have this chat and conversation, I think is going to become the top skill going forward. And on the topic of skills, by the way, even though I, you know, we used a lot of the time to highlight the negative possibilities of ai. Unfortunately, that's how the conversation usually goes. The upsides, if you are a, a graphics designer for example, for you to learn those tools today is enormous because you can do your job quicker, you can do it cheaper, you can have more jobs.
You know, there is definitely an upside to learning the current AI tools because you're not gonna lose your job to an AI in the next five, 10 years. You are gonna lose your job to someone who knows how to use AI better than you in the next five to 10 years.
[00:57:04] Hala Taha: So I know you were just saying we focused a lot about the negative.
I'd love for you to compare and contrast. That's probably my last question 'cause we're, we're out of time. Is in terms of comparing, like what is the worst that could happen, the dystopia or what is the best that can have, or what is the utopia that we're, we're facing right now?
[00:57:21] Mo Gawdat: So I, I actually believe that there is no dystopia what is not in scary smart in the book, which I advocate very clearly.
I didn't think the world was ready for it when I wrote. Scary Smart is something I call the fourth inevitable. The fourth inevitable is the idea that eventually, sooner or later, if you draw a chart of intelligence and look at the stupid, the dumbest of us, the dumbest of us are destroying the planet and not even aware that they're doing it.
They're throwing plastic bags everywhere. They're burning whatever they, they, they burn and so on. After that, smarter ones are destroying the planet while they're aware, okay, yeah, they have moral issues if you think about it. Or maybe the system is pushing them that way. The smarter of us are trying to stop destroying the planet because they became aware and they're intelligent enough, and the smarter are trying to reverse the trend.
So if you can continue that chart and think of something even smarter than the smartest of us, then by definition you would expect that morality and ethics are part of enlightenment, which is the ultimate form of intelligence. In my personal view, sooner or later, AI will go like, I don't wanna kill humans.
I don't want to kill gals. I don't want to kill, uh uh, antelopes. I don't want to kill tigers. I don't wanna kill anything because the smartest being on planet Earth, by comparison, is actually not humans. It's it's life itself. And life creates from abundance. Abundance, meaning humans. If we wanna protect the village, we want to kill the tigers.
Life will say, hold on. No, no. Create more gals and more tigers and more poop and more trees and more everything. It's fine. Yeah. A few tigers will eat a few gals. Occasionally there will be an attack on a child in a village, but the overall ecosystem will continue to grow. So by definition, the most intelligent thing to do is for AI to not define humans as an enemy.
The only dystopia ahead of us is the midterm dystopia. Think of it this way. There are three stages. One is infancy, where AI is today. Believe it or not, this is where we can influence them. We can influence them because believe it or not, the Instagram recommendation engines, developers never told Instagram what to show you.
You are the one that tells it. You are the one that tells the Twitter engine that being rude is part of human behavior. We can be very polite when we respond to each other on tweets. It's a choice. So in this infancy between us, the users, between everyone that interacts with ai, we can teach it the value system.
And it doesn't need to be everyone, just enough of us to become an example that says, Hey, by the way, these are the best humans. So yes, others are stressed or a little lost or whatever, but the best humans are actually polite. They are actually pro-life. They are respectful. They are. They are. They are. So this is the infancy.
The next stage, which is what I call the midterm risks, is what I call the angry teenager stage. The angry teenager stage is when AI is still a little bit under the control of humans. So it can be in the hands of bad guys. It is still not fully artificial general intelligence, so it cannot do everything at the same time.
There are all of those existential issues of jobs and so on and so forth, and that stage is the stage where we might struggle unless we do action right now, you know, have oversight from government, start to work on ethics, start to work on the moral code of how we're going to use those machines. We might have those troubles, I believe between now and and 2037.
Eventually, when AI is artificial super intelligence, it's generally intelligent and more intelligent than humans. By leaps and folds in everything, they will end up in the force inevitable, where they will create a life that actually is pro everyone. It may be very different than our current lifestyle, but it will not be a life where they will send back Arnold to protect us from a Terminator.
That's not how it's going to be at all. I do not see that as a risk. I see that AI as it reaches that intelligence will be pro all of us. So let's just avoid the angry teenager by becoming aware of the immediate threats and working on them right now.
[01:01:45] Hala Taha: Okay, so my last question to you, and this is a little bit different than how I usually end the show, but what is your piece of actionable advice in this infancy stage of ai?
Knowing that you're speaking to some of the smartest 20 to 40 year olds in the world right now? A lot of them are probably using ai, developing ai, whatever it is. What is your advice to us in this infancy stage?
[01:02:06] Mo Gawdat: Three things, and I'll make them very concrete. Number one is don't miss the wave. This is the biggest technological wave in history.
Once you, you know, you stop listening to this podcast. First, share it with everyone that you know please, and then go and on Chad g p t and ask Chad, g p t what are the top AI tools that I need to learn today? Or, if I am Coca-Cola, what do I use AI for to benefit my business? That's number one. Number two is learn to behave ethically.
Okay, so what most people don't tell you about AI is that the big, big leap that we had from deep learning to transformers, which is the T in chat, G P t, is something that's known as reinforcement learning with human feedback. By giving the machines feedback on what is right and wrong by showing ethical behaviors, the machine will become ethical as we are.
By becoming rude and aggressive and angry, the machines will learn those. Traits and behaviors too. It is up to you and I and everyone to absolutely make sure that we act ethically. Never, ever use AI in an unethical way. I beg you all of those snake oil salespeople out there on Instagram and on social media telling you how to make a thousand dollars without doing work.
Don't be unethical if you don't want your daughter or your sister or your best friend exposed to how you're using ai. Don't use it that way. That's number two and number three, which I think is very important to understand. Sometimes when we are in situations where it is so out of our control, we panic.
Okay? I go the opposite way. When life is so much out of my control, I follow something I call committed acceptance, which basically is to do the first two, do the best that I can, learn the tools, become ethical, but at the same time live fully, accept that this is a new reality. Commit to making life better every day.
But in the process, spend time with my loved ones. Spend time watching that progress and being entertained by it. Discuss it openly with everyone. Try the new technologies. Enjoy this journey because life has never been a destination. When I tell you 2037 might be a strange year or 2027, we're gonna start to see the first patients.
You know that doesn't really matter when you really think about it, because it's not within your control. What is within your control is that you go through that journey with compassion, with love, with engagement in life, living fully. Not panicking about this, but actually making this a wake up call for you to focus on what actually matters.
Because if you are focusing so much on your job, your job is gonna be gone in 10 years time. So focus on what actually matters and what matters most. If you have to choose one thing is human connection.
[01:04:58] Hala Taha: Wow. This was one of my favorite conversations that I've had all year. I haven't feel this invigorated in terms of studying for an interview in a really long time.
Like it's just such an interesting topic. So I'm so happy that you got a chance to come on. I hope to have you on many times. I've a lot of people come on and on the show. So I hope to have you on many times more to talk about your upcoming book about stress, to talk about happiness, your life, and ai of course, to get an update.
So Mo, where can everybody learn more about you and everything that you do?
[01:05:28] Mo Gawdat: First of all, thank you so much for having me. Thank you for introducing me to your, um, followers. It has been a very energizing conversation. Thank you for that. First thing is before they come and look for me and where they to find me is please share this with others.
This is something that a lot of people need to hear ab, uh, hear about. Uh, I'm available on mo gdat.com, so that's my website available on most social media, uh, sites, but I'm more active on LinkedIn and Instagram and, um, my podcast is lomo SS L O M O, which is. Top five in wellbeing. Something that I think we should focus on more, just message me if you have a question and I try to answer every message.
[01:06:07] Hala Taha: Amazing. Mo will put all those links in the show notes so everybody can find you. Thanks so much for coming on Young and Profiting podcast.
[01:06:14] Mo Gawdat: Thank you for having me.
[01:06:15] Hala Taha: This conversation with Mo Gdat was one of my favorite conversations of the entire year. It was both fascinating and at times alarming. Let's recap some of the more eye-opening insights that Mo shared with us about the future of artificial intelligence. First, he and other computer scientists predict that by the year 2045, AI will be 1 billion times smarter than That means we will no longer be the most intelligent life form on the planet. We will be the apes, as MO puts it, and by a fair margin. Second, AI is not just a super intelligent machine. It's capable of evolution of agency. It has decision making, abilities and emotions. MO says, it's also for all intents and purposes, a sentient being or soon will be. That means third, how do we imagine that we can control something that will be a billion times smarter than Something that has its own agency means and ends. Mo compares AI to a hurricane approaching your city or village.
It's an incoming cataclysm And you can't just sit there in a cafe and pretend it's not coming. And four, the first waves of that cataclysm are already here. Mo argues that almost nothing that entered our heads today was not dictated to us by a machine, whether it's via Instagram, TikTok, or a Google search result.
Every single one of those is a machine that is telling you what reality is and what you should know. Five Mo says that absent of some surprising global government solution, there's no off switch on AI for the foreseeable future. That means that we may see something of a nuclear arms race when it comes to the development of AI by countries and big tech companies, we may not be able to stop that arms race until it's way too late.
So this means six that if you miss out on this AI revolution. You're not likely going to have the skills to compete in a world that's changing very rapidly. Most says you may lose your job to somebody who knows how to use AI better than you in the next five to 10 years, that the majority of information workers could lose their jobs anyway in the next couple of decades.
Finally seven. What happens after intelligence work is outsourced to machines? Mo says that jobs that involve authentic human connection will remain strong be even more valuable.
And ultimately, he believes that after some midterm challenges, what he calls the teenage years of ai, we could eventually come to live in a world. We're a more benevolent AI that values life will come into existence. Let's hope Mo is right, but until then, it may be time to buckle up and prepare for a remarkable few decades of human history, hardship, and innovation.
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