Young and Profiting with Hala Taha - YAPClassic: Ex-Google Officer Mo Gawdat Warns About the Dangers of AI, Urges All to Prepare Now!

Episode Date: April 19, 2024

So what do you need to know to prepare for the next 5, 10, or 25 years of a world increasingly impacted by artificial intelligence? How could AI change your business and your life irreparably? Our gue...st today, Mo Gawdat, an AI expert and former Chief Business Officer at Google [X], is going to break down what you need to understand about AI and how it is radically altering our workplaces, careers, and even the very fabric of our society.   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.   Resources Mentioned: 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/   LinkedIn Secrets Masterclass, Have Job Security For Life: Use code ‘podcast’ for 30% off at yapmedia.io/course. Sponsored By: Shopify - Sign up for a one-dollar-per-month trial period at youngandprofiting.co/shopify Indeed - Get a $75 job credit at indeed.com/profiting Airbnb - Your home might be worth more than you think. Find out how much at airbnb.com/host Porkbun - Get your .bio domain and link in bio bundle for just $5 from Porkbun at porkbun.com/Profiting Yahoo Finance - For comprehensive financial news and analysis, visit YahooFinance.com More About Young and Profiting Download Transcripts - youngandprofiting.com  Get Sponsorship Deals - youngandprofiting.com/sponsorships Leave a Review -  ratethispodcast.com/yap Watch Videos - youtube.com/c/YoungandProfiting   Follow Hala Taha LinkedIn - linkedin.com/in/htaha/ Instagram - instagram.com/yapwithhala/ TikTok - tiktok.com/@yapwithhala Twitter - twitter.com/yapwithhala   Learn more about YAP Media Agency Services - yapmedia.io/

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Starting point is 00:00:00 Today's episode is sponsored in part by Yahoo Finance, Porkbun, Indeed, Airbnb, and Shopify. Yahoo Finance is the number one financial destination. For financial news and analysis, visit the brand behind every great investor, yahoofinance.com. Build your digital brand and manage all your links from one spot with Porkbun. Get your.biodomain and link in BioBundle for just $5 at porkbun.com slash profiting. Attract, interview, and hire all in one place with Indeed. Get a $75 sponsored job credit at indeed.com slash profiting. Generate extra income by hosting your home on Airbnb. Your home might be worth more than you think. Find out how much at airbnb.com
Starting point is 00:00:46 slash host. Shopify is the global commerce platform that helps you grow your business. Sign up for a $1 per month trial period at Shopify.com slash profiting. As always, you can find all of our incredible deals in the show notes. Young and Profiters! We have been talking about AI a lot on the show, and that's because we know how important it is to have an in-depth understanding of the technology and how it is rapidly shaping our world. And we can't talk about AI as merely a thing of the future anymore. It's developing exponentially every day and whether we're aware of it or not, we play an active role in how it affects us and our careers or businesses. So today we are dusting off a not so old episode from 2023.
Starting point is 00:01:51 It's only like maybe eight months old, but it is so good. And I want to make sure that anybody who didn't hear it yet hears it. Because this episode with Moe Gaudat blew my mind. And it blew a lot of people's minds, which is why it went massively viral on YouTube. And it was one of my most popular episodes last year, if not the most popular episode. And so I really wanted to resurface it
Starting point is 00:02:16 because I keep referencing this episode and other AI episodes that I have. And I just want everybody to make sure that they hear this conversation. It was really eye opening. So if you don't know Moe Gaudat, he is a guru in the tech world. He worked at IBM and then Microsoft. Then he joined Google. And at first, he was the vice president of emerging markets at Google, and he started half of Google's businesses globally.
Starting point is 00:02:41 And then he became the chief Business Officer of Google X. X is Google's innovative lab where they work on big bold ideas to solve the world's greatest problems. And in this YAP Classic, Moe is going to talk about one of the most intriguing AI experiments they ever invested in, which included robot arms that were taught to pick up toys and put them away. And that might sound super simple, but it actually completely changed the way that Mo perceived AI, and it scared him so much, and he was so against what Google was doing with AI
Starting point is 00:03:14 that he ended up quitting because he didn't wanna be a part of it. Now, that's not to say that Mo is not optimistic about AI. He believes there's a bright future ahead of us, but only if we take the danger seriously of AI and we develop AI responsibly. So there's so much to unpack here. There's so much to learn in this episode. This was one of my favorite episodes of last year. You guys are going to love it. So without further ado, here's my conversation with the incredible
Starting point is 00:03:41 Moe Goudat. Mo, welcome to Young and Profiting podcast. Thank you. Thanks for having me. It's been a while in the making, but absolutely worth the wait. Can you talk to us about your journey at a very high level, the highlights that got you in the C-suite at Google Acts eventually? At the height of my professional career, if you want my corporate career, I was Chief
Starting point is 00:04:08 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 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.
Starting point is 00:04:40 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. And I said, yep, that's not your choice. And I showed up basically, the first day I showed up, I bumped into Sergey, our co-founder and I worked closely with Sergey 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.
Starting point is 00:05:15 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 it was a big part of what I did.
Starting point is 00:05:49 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? 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
Starting point is 00:06:15 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. 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
Starting point is 00:06:51 that it found a cat, not just one cat, but really what cat-ness 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 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
Starting point is 00:07:29 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 would 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
Starting point is 00:08:14 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 goes down, picks one item, which was a yellow softball, again, mathematically very complex to 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. I'm the smile and then you know sort of not that their heads and on monday morning as i went to work every arm was picking the yellow ball.
Starting point is 00:09:14 A couple of weeks later every arm was picking everything and i think that something that most people don't recognize about the eyes 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. So they really do develop intelligence that comparable, now probably even more advanced than human intelligence. 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? I've been excited about AI since I had a Sinclair, believe it or not. So I started coding at a very, very young age
Starting point is 00:10:05 on computers, young and profitable, probably have never touched in their life. So, you know, and every one of us geeks wanted to code an intelligent machine. 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 allow me to stop for a second here, because there is a huge difference between the way we programmed machines before deep learning and after deep learning.
Starting point is 00:10:43 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 cheat 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.
Starting point is 00:11:21 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, 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 Demes, who was the CEO of DeepMind when we acquired DeepMind, it was really to me like meeting the rock star. 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
Starting point is 00:12:08 intelligence and for a programmer that was mind-blowing. And remember, 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,
Starting point is 00:12:37 one are developing way faster than us. And so accordingly, the predictions of people like Ray Kurzweil 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 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 cast the apes. We are going to be the apes. Do you understand that? Yeah. And I think that completely
Starting point is 00:13:21 made sense to me that this needed a lot more consideration, rather than 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. There's so much to unpack here. This is why I was like, I need to spend the full hour on this topic because there's just so much to unpack here. This is why I was like, I need to spend the full hour on this topic because there's just so much to unpack. Let's talk about the label of artificial in artificial intelligence. Is intelligence artificial at all or is AI? Oh yeah, talk to us about that.
Starting point is 00:13:56 Not in the slightest. If there is any artificial side 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 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 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
Starting point is 00:14:41 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. The way 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 neurons, not yet trillions, but you know, lots of nodes of patterns that the machine would recognize so that it basically can make something look intelligent or can behave in a way that is
Starting point is 00:15:38 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
Starting point is 00:16:16 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 AGI 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 chat GPT is at an IQ of 155, Einstein I think was 160 or 190, doesn't really matter, but most humans are 122, some are less
Starting point is 00:16:57 than that, maybe 110 and so on. 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 task assigned to every AI, and 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,
Starting point is 00:17:34 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. What you're saying is really incredible and mind-blowing. I know that for humans, we don't understand how conscious this works, right? Nobody can say, you're conscious because of this.
Starting point is 00:18:00 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. I think the definition of sentient needs to be agreed. Is a tree sentient, Is a pebble sentient? Is the planet Earth sentient? You know, we could have many arguments. Now, if you think of being sentient as it is born at a point in time and it dies at a point in time, or
Starting point is 00:18:35 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, 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. If you take a tree, example and tree 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 that we will not shed it's leaves on the twenty first of october specifically it will shed its leaves when the weather alerts it to do that. And if you consider a tree sentient in that case, then AI is surely sentient. If you consider that a gorilla is incredibly interested in survival and accordingly would
Starting point is 00:19:36 do what it takes to survive, then AI is sentient in the sense that once assigned a task, it will attempt to survive, to make the task happen basically. 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?
Starting point is 00:20:04 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're sitting at a cafe saying I'm not interested. This is the biggest event happening in today's world. And 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're not going to have the skills to
Starting point is 00:20:36 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 the terminator scenario it's an existential risk to humanity in ten fifteen twenty 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 are 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
Starting point is 00:21:23 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 very simple example. There is nothing that entered your head today that was not dictated to you by a machine.
Starting point is 00:21:44 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 we're searching and getting a result 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.
Starting point is 00:22:06 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
Starting point is 00:22:36 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 going to 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 the rest of your life trying to defend this lie or trying to disprove this lie and show the truth just 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 Harari basically says they have hacked the operating system of humanity
Starting point is 00:23:22 so if i can hack into your brain Hala and tell you something that affects you for the rest of your life whether positive or negative whether true or false then i have 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. They're becoming really good at it. They're becoming so good at it as a matter of fact,
Starting point is 00:23:58 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 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,
Starting point is 00:24:35 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 Stability.ai, Stable Diffusion, for example, can now generate realistic human-like images in less than a tenth 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 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.
Starting point is 00:25:19 Think of information and statistics using chat GPT, 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 has gone. Let's hold that thought and take a quick break with our sponsors. Hey, AppBam, starting my LinkedIn Secrets Masterclass was one of the best things I've
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Starting point is 00:31:39 It is insane and I definitely want to 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. Let me give you
Starting point is 00:32:10 a concrete example. There is a strategy game known as Go. Go is one of the most complex strategy 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 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, I believe, that 10 years ahead of any estimate, that AlphaGo, again, DeepMind, basically became the world champion in Go.
Starting point is 00:32:56 And AlphaGo 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 that's the runner-up. And it won 5 to 1 or 5 to 2. 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.
Starting point is 00:33:32 That was around a few months later. And then we developed another code that was called Alpha Go Zero. And Alpha Go Zero basically learned the game by playing against itself. So it never saw a human ever playing Go. It just played against itself. So it would be the two opponents and through the patterns of the game randomly, it would
Starting point is 00:33:56 learn what wins and what loses. AlphaGo Zero within three days, three days, won against AlphaGo, the original, within 21 days, one against AlphaGo 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, was playing against AlphaGo 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
Starting point is 00:34:39 break to understand. It was a move of ingenuity, of intuition, of creativity, of very deep strategy, of very, very deep mathematical planning. And we never taught AlphaGo Master 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.
Starting point is 00:35:12 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 Sund sunday the CEO of alphabet. Talks about google's a i n how that we discovered or they discovered i was not no longer at google at the time that it speaks banglali. We never taught banglali whenever showed it at the test of banglali just learns banglali chai GPT is learning research chemistry. We never taught it research chemistry. We never wanted it to.
Starting point is 00:35:48 It just learns just like you and I, Hala. 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 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 elementary school, in math tests, they asked the student to show the thinking they went through.
Starting point is 00:36:15 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 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 in a control code within their code, because it takes time and effort,
Starting point is 00:36:52 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 the ChatGPT 4 was 10 times smarter than chat GPT-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.
Starting point is 00:37:29 That's the level of intelligence difference between us and them. Just like it's so difficult for someone like me who 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, one billion with a B. So it's quite interesting when you really think about it, how the arrogance of
Starting point is 00:38:12 humanity still imagines that it can control something that is a billion times smarter than us. So I don't want to be grim. I want to 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
Starting point is 00:38:45 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. Yeah. 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? Yeah, I don't know how stupid humanity can be, honestly.
Starting point is 00:39:19 I really 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're burning the planet. We continue to favor the patriarchy 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.
Starting point is 00:40:06 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 FDA 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.
Starting point is 00:40:36 This is safe for humanity at large. And none of that happens. And I understand Sam Altman, 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 chat GPT out there to be accessed by everyone is completely reshaping everything. That's number
Starting point is 00:41:01 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 basically the repository of where developers share their code, 41% of it is machine developed. Within a year, almost less than a year, of 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,
Starting point is 00:41:46 the design of a code, but coding itself was annoying. Now you can tell the machine, build me a website that speaks about Hellas podcast that is blue and yellow in color and that is 15 web pages long and it will do it in less than a minute and it's not only that it's a lot of the base programming like chat GPT. 75% of the code offered to judge GPT to correct or to review was made one half times faster so basically. Every time it reviews a human code it makes 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. And the third is we said don't have AIs, instruct AIs what to do.
Starting point is 00:42:41 We call those agents. So basically, you now have something that has access to the entire World Wide 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're 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
Starting point is 00:43:26 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, Spiderman's 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.
Starting point is 00:44:03 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. 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 chat GPT to keep writing code to make you more money, eventually somehow something in the system will break.
Starting point is 00:44:38 And if you're not the one telling it, if a machine is telling it, something is gonna break. We absolutely have to start getting this under control. 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 inevitables. AI will happen.
Starting point is 00:44:57 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 potentially. There are three inevitables. AI has already happened, not just will happen. But when I wrote the first inevitable,
Starting point is 00:45:15 I wrote it with the intention of explaining and there is no stopping it. So there is no way you can say, OK, AI is out there and it is growing and it's becoming more intelligent. Let's 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 differences aside 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
Starting point is 00:45:51 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. Google cannot stop developing AI because Meta is developing AI. America cannot stop developing AI because China is developing AI. Nobody actually, even if you want to consider there are good guys in the world, nobody can stop developing AI because there could be bad guys developing AI. 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
Starting point is 00:46:38 to develop AI. It's done. There is no stopping it. And I think the open letter was a great example of that. Can I pause you there in case nobody knows? think the open letter was a great example of that Can I pause either 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 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
Starting point is 00:47:21 with that letter? 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 end of 2017. Others like Jeffrey Hinton and so many others are starting to wake up to that in 2023. I think Chad GPT was basically the Netscape moment. I know you guys are too young for Netscape, but the internet was there for 15 years before Netscape came out.
Starting point is 00:47:52 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. Chad GPT basically told us what the possibilities, told the general public what the possibilities are. And so suddenly we all realized this stuff exists. chat GPT basically told us what the possibilities told the general public what the possibilities are and so suddenly we all realize 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.
Starting point is 00:48:28 I say it's 2027 or earlier that there will be a moment in time within the next two to three 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 have been quite a few that have been putting in effort to create that control code. But let's say 98% of all investments in the last 10 years has gone into the AI code, not the control code. And so the control code was lagging. And so their letter was basically saying, can we pause for six months to figure this
Starting point is 00:49:17 out before we continue to develop AI? And of course, the answer was very straightforward. The first I think I heard was a sunday chida CEO of google which is someone i respect. Dear lian i think is an amazing human being and sunday basically came out and said i can't stop how can i stop if you can guarantee me that matter and amazon and all of the others are going to stop to 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.
Starting point is 00:49:58 And I think that reality is the prisoner's 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. 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, which was nuclear weapons, where humanity suddenly got together very late in the game and said, hey, this is existential. It can threaten the entire existence of humanity.
Starting point is 00:50:46 Why don't we slow down or 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 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
Starting point is 00:51:14 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. We'll be right back after a quick break from our sponsors. Young Improvetors, I've been a full-time entrepreneur for about four years now, and I finally cracked the code on hiring. I look for character, attitude, and reliability. But it takes so much time to make sure a candidate has these qualities on top of their core skills
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Starting point is 00:55:44 threats that there's going to be robots taking over, killing off humanity, making human slaves. But let's talk about some of the more immediate threats that we need to be concerned about. 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 are less probable. As a matter of fact, they are so improbable that they are basically not worthy of discussing today because we may not make it that far if the immediate risks are not attended to.
Starting point is 00:56:18 And there are many immediate risks, but 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.
Starting point is 00:56:46 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 agriculture revolution, it's always been kings and peasants, landlords and peasants. The difference between them is that the peasants worked really hard to sow the seed and collect the harvest when most of the profits, most of the wealth went to the landlord who owned the automation.
Starting point is 00:57:15 And the industrial revolutions joined 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 could own two factories and become much richer
Starting point is 00:57:51 than the peasants. You can own an internet app like Instagram and become much richer than the peasants. And now with AI, all of us are going to be happily chatting away and putting prompts in chat GPT. but the ones that own the automation, the digital soil, if you want, are going to become very few players, Amazon, Google, and so on and so forth, Meta and so on. 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.
Starting point is 00:58:20 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 going to 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 neural link where we can connect AI to 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
Starting point is 00:58:58 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. You know, what we used to call the digital divide when the 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
Starting point is 00:59:35 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'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're a lawyer, or if you're 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
Starting point is 01:00:25 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 strength, physical strength was the distinctive reason why you would hire someone.
Starting point is 01:01:02 Then there was a time when we 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 to 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 humanity's day to day income and economics and the way we spend our hours and so on and if we do this right by the way and i become the intelligent agent that's going to
Starting point is 01:01:52 help humanity then there could be a time in the near future where you walk to a particle point of view is not different than the cost of making an Apple. And so with nanophysics, 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, 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.
Starting point is 01:02:48 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 want to make sure that this is a machine, not a 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 are the bad guys, they'll say the Chinese and the Russians. If you ask the Americans who are the bad guys, they'll say the Chinese and the Russians. If you ask the Russians who are the bad guys, they'll say the Americans.
Starting point is 01:03:29 So we don't really know who the bad guy is, and everyone is racing to be ahead of the 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. Yeah and I have so many questions for you. We have ten 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 want to understand this,
Starting point is 01:04:02 is in the next you next 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? I think those two are the same question. Exactly, yeah. Because what will it do to human connection? It may fool us drastically, huh?
Starting point is 01:04:22 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 Mo. Pocket Mo basically is an AI that read all of my books, listened to all of my podcasts, all of my videos, all of my public talks and basically is going to be in your pocket so you can ask it any question about happiness and well-being 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?
Starting point is 01:04:53 On the other hand, within five years, this thing is going to 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 book called Finding Love, chapter 10, which means two chapters to go. And I stopped, I decided no, in the age of AI, I shouldn't try this way, I should start over. So I'm now writing a book that's called A Dating Guide for Straight Girls, which is a subset of the finding love that is very specific 80 pages long. You read it within one day, it takes me 10 to 15 days to write
Starting point is 01:05:31 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, I don't remember, I think there was a song by AI that mimicked Drake, which was as good as or better. I haven't heard it because I don't listen to Drake.
Starting point is 01:06:02 I'm not young and profiting. But 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 50s, 60s and 70s. 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 fans will want to see the Beatles life. Yeah, there will be holograms, but we will still want that human connection.
Starting point is 01:06:29 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 we used a lot of the time to highlight
Starting point is 01:06:53 the negative possibilities of AI, unfortunately, that's how the conversation usually goes. The upsides, if you're a graphics designer, for example, for you to learn those tools today is enormous because you can do your job quicker, you can do 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
Starting point is 01:07:17 in the next five, 10 years. You're gonna lose your job to someone who knows how to use AI better than you in the next five to 10 years. So I know you were just saying we focused a lot about the negative. I'd love for you to compare and contrast this probably my last question, because we're out of time,
Starting point is 01:07:32 is in terms of comparing, like what is the worst that could happen? The dystopia, or what is the best that could happen? What is the utopia that we're facing right now? So 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 force inevitable. And the force inevitable is the idea that eventually sooner or later,
Starting point is 01:08:01 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 burn and so on. After that, smarter ones are still destroying the planet while they're aware. Yeah, they have moral issues if you think about it 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 smartest 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
Starting point is 01:08:41 you would expect that morality and ethics are part of enlightenment, which is the ultimate form of intelligence. So in my personal view, sooner or later, AI will go like, I don't want to kill humans. I don't want to kill gazelles. I don't want to kill antelopes. I don't want to kill tigers. I don't want to 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 want to protect the village we want to kill the Tigers life will say hold on No, no create more gazelles and more tigers and more poop and more trees and more everything. It's fine Yeah, a few tigers will eat a few gazelles
Starting point is 01:09:22 more trees and more everything, it's fine. Yeah, a few tigers will eat a few gazelles. 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, and believe it or not,
Starting point is 01:09:48 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're the one that tells it. You're 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.
Starting point is 01:10:11 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
Starting point is 01:10:35 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
Starting point is 01:11:22 troubles, I believe, between now 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.
Starting point is 01:11:53 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. Okay, so my last question to you, and this is a little bit different than how I usually end the show,
Starting point is 01:12:09 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? Three things and I'll make them very concrete. Number one is don't miss the wave.
Starting point is 01:12:30 This is the biggest technological wave in history. Once you stop listening to this podcast, first share it with everyone that you know, please, and then go on chat GPT and ask chat GPT, 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 GPT, 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
Starting point is 01:13:16 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 $1,000 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.
Starting point is 01:13:56 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 and commit to making life better every day.
Starting point is 01:14:27 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.
Starting point is 01:15:06 Because if you're focusing so much on your job, your job is going to 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. you

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