How Artificial Intelligence is Making Humans Dumber & How to Robot-Proof Your Brain - With Dr. Vivienne Ming

31:12I call them cyborgs, not solely because I'm an unrepentant sci-fi nerd, but that's become the term of art sort of in the field. These people that just, you can't even tell who's making the decision. Like they produce something and it's a truly collective, but we call it hybrid intelligence. It's not artificial. It's not natural. It's hybrid. And it's unique and it's superhuman and it's super AI. And it's so exciting in our experiments, but it's still so few people really are engaging that way.

31:47Shawn Stevenson:So - What's happening to the people who aren't engaging like that? What's happening to their brains? So the people who aren't engaging, as I mentioned earlier, their cognition drops, the gamma activity is down. When they submit an answer, say, have them write an argument, like a debate, and write your side of the argument. People find their arguments not especially compelling, but they don't even remember what they argued. The funny thing is when you give them the AI, they feel like this is part of their knowledge, part of their capacity. Could you do this again next week without GPT helping you?

32:25Yeah, of course I could. But you could give them literally the exact same question. They can't remember what they said. They can't remember what they... So none of it's truly getting processed. There's an interesting parallel in just classic education. Like the boring way to put it is active versus passive learning. But the passive is classic lecture hall. I get up and they pull the string on my back and I go for like two hours. And I really like doing that. As it turns out, who would have guessed? Someone with zero social skills enjoys telling stories on a stage. But I talk at them and they learn something, maybe.

33:11Inactive, I get up in front and I'm Socrates. I start asking questions. I get people to, you know, stand and deliver. Like, they have to be present and engaged. So we already know this. students hate active learning. Hate it. It's hard. It's effortful. To be honest, the teachers don't like it. It's also hard. Instead of a one class of 100 students, you're teaching 100 classes of one student kind of experience. But actually, that's not the reason why students hate it so much. They hate it because even though the research shows unambiguously, you learned vastly more in an active learning context.

33:51They feel like they've learned less because they've had their misconcepts exposed. And most of us spend a huge amount of subconscious effort hiding our misconcepts from ourselves. We give what we know is the right answer rather than exploring a better answer because we might be wrong when we start exploring. Boy, if you can't get beyond, And if you can't even celebrate being productively wrong, you can't get anywhere. What we see in these cyborgs is Gemini. You are my worst enemy, my lifelong nemesis. Here's the chapter I just wrote of my new book. Tell me in excruciating detail why I'm wrong and what I can do about it.

34:43Now, in a natural social context, most people would never willingly do something like that. But that's part of the great thing about this. I mean, a genuine positive. You're not talking to a person. I hate to break it to you. It doesn't care. So you don't have to make it your nemesis, but you could say, hey, you are my friendly, but bruntly honest best friend editor. Tell me what's wrong with this chapter and what I can do to fix it. Frame it however you want to, but whatever you do, don't ask it to tell you why you're right. Don't ask it to just write the chapter for you. Challenge yourself. How can I make this better?

35:28Your job, interestingly enough, is to be you. Your job is to say what no one else in the entire world will say. Because the thing everyone else would say is now free in your pocket. What you would uniquely say, especially with the help of an AI to get the facts right and the details, is magic. And if you're not doing that, you're not getting the most out of these sorts of systems that you could. But if you're not doing that, you're also just in the long scope of your life. You are not engaging your dorsolateral prefrontal cortex that's supporting all of your working memory. You are not developing the resilience you need.

36:18Resilience in psychological context is how likely you to find success after experiencing failure. I hate to break it to you. The only way to get more resilient is to experience failure. um so all of these things that predict amazing life outcomes working memory perspective taking oh such a powerful one um resilience a sense of purpose in life you'll notice i'm not saying that you went to stanford i'm not saying that you know how to do python on your resume these things that sound very squishy but i'm telling you they are the hardest of hard skills um these are things that both predict long-term positive life outcomes, including all-cause mortality, Alzheimer's risk, ischemic heart disease risk, insulin sensitivity.

37:07They also predict, intriguing enough, how likely people are to engage as cyborgs with the AI that they're using and ask it to challenge them. Curiosity, an obvious one, but did you know you can develop curiosity? It isn't just in your genes, right? It isn't just something you got by the roll of the dice in character creation. This is something you can actively foster. Easier to foster in your kids if you're a parent, so go all in on it. But you can do it in yourself as well. Wow.

37:41Shawn Stevenson:Thanks for sharing that because, you know, curiosity, I think, is just we think is an inherent. What level of curiosity do you have that you can develop that? Wow. Um, you know, this is what I'm really hearing as well as like, we cannot actually be fully ourselves if we're outsourcing our thinking, you know, and there's just so much human capacity and character, even the development of curiosity that we can unknowingly be outsourcing and not, you know, I, I'm also thinking about the argument of some people just like, well, it's not going to matter anyways, because my thinking is all, and my interaction is going to be in this virtual world.

38:20Shawn Stevenson:And there is a place for that, but I don't really see most humans wanting that to be their life. And for those of us who are interested in really being human and enjoying life and maybe looking at AI as an opportunity to, again, kind of supplement, support, foster more of these capacities, have a better relationship with it, I want to ask you about some of these tenets. You mentioned individuals who are thriving, looking at this more as a cyborg interaction versus think for me. The truth is when something is thinking for you, use it or lose it, really, to put it bluntly. But also that could free up space for your brain to think and to do other things.

39:11Shawn Stevenson:But most of us are not. We're just going to end up being more complacent. You know, there's this idea of a universal basic income. Hey, if robots just take all of the jobs, Jeff Bezos will pay you to do nothing. Well, I don't know. Amazon tried to hire me to be their chief scientist once. It was, in fact, one of the best job pitches I've ever gotten because it's one of the few that actually got me. This will date it a little bit when you hear the statistics. Dr. Ming, in seven years, we will be a one million person company. I think they're like one, eight, two now. Your job will be to make their life better.

39:53So I've gotten the pitches of we've got nasty data problems. Who's alive at the end of that? Why do I care? You know, I love a good movie, but solving nasty data problems for Netflix just didn't to excite me. We're all going to get rich. A lot of companies have pitched me on that. Boy, do you not understand me. I give away all of my money every year. If I wanted to be rich, I'd probably start by keeping it. But my family has an amazing life. And there are kids that are dying. My kids will have a better life. Because I've already given them what they need. If I make the lives of other people better, especially because of my quirks of my own life really make me understand that.

40:36So none of that matters. To get that pitch from Amazon, which is probably not on everyone's hero list right at the moment, that was something I appreciated. Not that I was mistaken that I'd think I'd take the job, but I went up, met with them. I actually offered you the job for free. I will only do the things I believe in because the simple truth is I think their philosophy, I don't believe I'm mischaracterizing it to say they're not a believer that people can change. For the most part, you are what you are. We want to buy that from you for a few years, and then have you happily go away. And if that's your view of the world, maybe humans are sort of superfluous, right?

41:21If we're just your minions to carry out your orders, why not just build robots? And then let the rest of us do it for free. Except I am here to tell you, not in a million years would Jeff Bezos pay you money to go sit on your ass and drink Mai Tais, nor would Elon Musk or any of them. So things like a universal basic income is a solution to some kind of problems. How do you pay your rent? How do you pay for food? Not a great solution, but it is a solution to that. But what it's not is a solution to how do I make meaning in my life? um you know they say we'll pay you and then you can go create and be free it's the same kind of pitch you get with ai it will do all the boring work so you can do the fun creative work i don't know about you but the boring work is part of the creative work if i don't i mean i have a quirky idea of what fun is if i don't understand the data if i haven't gotten dirty with the data I don't understand it.

42:28And therefore, I don't know the models that fit. I don't know what's going on in those human stories that I'm touching. I won't get it right. In that case, I should just let the machine do all of the work. If I'm trying to write a screenplay, paint a picture, analyze a spreadsheet, generate marketing copy, and I'm outsourcing the boring stuff, I hate to break it to you. There's no creative stuff left for you to do. In fact, kind of nerdy, but we built an economic model, did some simulations. If you only outsource the boring stuff, guess what? You just get more boring stuff. You get more, not less.

43:10So you really want to support creativity. AI should directly support creativity. And the easiest and best way for it to do it is to challenge you for it to act as an external working memory so you can expand what you are keeping in mind it sounds silly to say this but the best totally totally fictional but still the best sort of you know i wish this was my day-to-day but i actually have to write code but the best example of working with ai is in adventures end game when tony stark is figuring out time travel and he's just sort of talking to his ai jarvis i think it is and he's like well try this what what if we put the whole structure on a helix and then we we change these parameters and it goes and runs the simulation boop figures out time travel like that's not entirely unlike what i'm seeing those cyborgs do in my experiment the thing that almost no one else is doing how you know we we ask them to make predictions about the future that way we know the ai can't just have memorized the answers what will the price of well we all are thinking about the price of oil right at this literal moment in time but six months ago what will the price of oil be in six months turns out you grab the random people off the street they have no they don't even know what the price of oil is right now so we're terrible at this we ask them to make 10 predictions in an hour, UC Berkeley students, sort of man, women on the street, it's above chance, but they don't do great.

44:51We have AI do these predictions, it's way better. So again, why are we here? What's the point of us? Then we do the hybrid intelligence. We give a little team of humans an AI, even just a cheap, free, open source, small model. And we have them do the same predictions. And if they have high measures of fluid intelligence, curiosity, perspective taking, your ability to understand what's going on inside someone else's head, and intellectual humility. Don't tell me what I want to hear, AI. Tell me what I need to hear. When they have these qualities, then they shift into the cyborg mode and the humans explore and the ai pulls you back towards the data then the humans explore then the ai pulls you back and three or four rounds of that and they came up with predictions that weren't just better than the ais by themselves easily better than the humans by themselves we pulled our predictions off of this site called polymarket which is in the news nowadays it's a prediction market people literally bet on the future it does better than polymarket where professional predictors have real money in the game.

46:05Random people on the street who don't know anything. The smartest thing on the planet today is not the bleeding edge of Google or open AI. It is not Terence Tao, the mathematician.

46:19It's random people with these deeply human qualities paired up even with a modest AI. It so excites me, but the crucial ingredient is they are thinking for themselves, for the good of us and them, but also, again, to bring it back to the theme, I guarantee you they're going to have better long-term health outcomes, long-term happiness, friendship networks, even income, not just because they're smart, but that rich sort of human quality.

46:54Shawn Stevenson:today highly refined sugar is infused into so many of the things that are on our grocery store shelves and we've got to make a change we've got to make an alteration right now to take back control of our palate and to reduce the consumption of that ultra process version of sweetness so how do we do that where can we get that sweet sensation that we're looking for without all of these metabolic problems well a recent study that was published in the peer-reviewed journal nutrients detailed how honey, raw honey specifically, can actually improve our fasting blood sugar levels, improve fat metabolism, and reduce the risk of heart disease.

47:38Shawn Stevenson:Additionally, the scientists noted the vast antioxidant and anti-inflammatory properties that honey has. To call honey a mere sweetener is an absolute atrocity. It's an understatement to call it merely a sweetener. It has remarkable benefits that are simply seen in not many other foods. For example, a study cited in the journal Evidence-Based Complementary and Alternative Medicine determined that honey's antioxidants have nootropic effects such as memory enhancement. Plus, a randomized, double-blind, placebo-controlled study cited in the journal Pediatrics revealed that honey was able to outperform a placebo and significantly reduce cough frequency and severity at night and improve sleep quality.

48:20Shawn Stevenson:Now, the emphasis here is on raw honey. You want to make sure that it is actually real honey because there are some honey wanksters out there. And if you don't know about the Honeygate scandal, look it up. So you want to get your honey from trusted resources. And my favorite source of honey is from the incredible team at Beekeepers Naturals. Go to beekeepersnaturals.com forward slash model. Right now, you're going to get 20 % off the incredible superfood honey, plus 20 % off store wide. They are adamant about the third-party testing, making sure there are no nefarious things coming along with only the highest quality honey in the world.

49:07Shawn Stevenson:That also has complimentary amounts of bee pollen and propolis as well. It's truly, truly special. Head over there, check them out. It's beekeepersnaturals.com forward slash model. That's B-E-E-K-E-E-P-E-R-S. Naturals, that's N-A-T-U-R-A-L-S.com forward slash model for 20 % off storewide. Head over there, check them out. Get your sweetness from a source that's keeping you metabolically healthy. Again, head over there, check them out. Beekeepersnaturals.com. Now back to the show. So there's already a plethora of studies on the importance of meaning when it comes to not just longevity, but the quality of our lives.

49:49Shawn Stevenson:And it is never it has never been more important. Meaning was kind of baked in in our tribal construct, I think, you know, but now, again, we're all so scattered and isolated. And there's so much to do. There's so much we can do. We can be in all these things. We can get into this conversation of paradox of choice, of course. but I want to talk about some of the character traits for us to really focus on in this emerging age of AI for us to, again, to, to thrive in these conditions rather than what, if, if you're, if people don't get their hands around your work and, you know, the people that you're influencing, there's a high probability of, again, I'm just going to say it, we're going to end up being like dumb and dumber, you know, and not really maximizing our potential, let alone even tapping into it remotely, because we need stress.

50:44Shawn Stevenson:We need to fail for us to get stronger and to get better. We need to figure things out. We need to ask tough questions. And so what are some of these qualities? You mentioned perspective taking. Is there anything else? So long ago, I was the chief scientist of one of the first companies doing AI and hiring, which turns out to be very difficult and biased. I mean, our job was literally our tagline was we take bias out of tech hiring. Boy, was that a harder task than I think any of us at the time appreciated. Who would have thought that a bunch of geniuses in Silicon Valley might get that wrong?

51:27But I'm still immensely proud of what we built. Amongst the things we built was a data set of 122 million working professionals. My job was to figure out how good you were at jobs you've never held. Because our clients were Google and Rolls Royce and Citibank and JP Morgan and Facebook. And they were hungry for amazing people. They knew every student coming out of an elite university. Find me everyone who's as good as them, but doesn't have that pedigree. That was our job. That was our product, if you will. You were our product. And I'm looking, what is it that predicts those people? And it wasn't what you claimed on your resume, the skills you said you know.

52:18It wasn't, once I knew other things about you, the fact that you went to that fancy Eastmancy University didn't, it predicted a little bit, but not much. There wasn't that much it added. So what was left over? Nowadays, we might call them foundation skills. What was left over was measurable. It predicted life outcomes, not just careers, but as we've talked about, long-term health outcomes and more. Probably causally, not just predicting, but really driving it. And for my interest, changeable. The thing I said in taking that job was, I want to find people and employers and tell those employers, here's nine people that are exactly what you're looking for.

53:08And here's a tenth that could be if you were willing to invest in them. And guess what? They're going to come a lot cheaper because no one else is going to look at this person. But if you invest in them, you can make them amazing. So that's what got me really interested in change plus my life story. So in the end, I started calling these qualities meta learning. Because what bound them together is the people that possess them had learned how to learn. It didn't matter that they didn't know how to do a thing because they could go figure it out on their own. So there were cognitive skills, working memory, attention, numeracy, literacy.

53:50A lot of those, as adults, you and I, we're long past doing a lot of development of our cognitive skills. It's a maintenance game, which is just as important. But early in life, up to about age five to eight, are you a parent? All of these are still open. Working memory predicts so much of our life outcomes.

54:13And kids' life experiences early can drive it up and down. Like, own that. Make a difference. social skills, perspective taking, communication, leadership, hugely theory of mind. These I've already mentioned that perspective taking was a big predictor in our study and in other studies, looking at who's really good at using AI. Interestingly enough, the same thing that allows me to understand other people, allows me to understand, I don't think GPT understood my question. It's given me a really great answer, but I think it might be the answer to something else. Perspective taking predicts that.

54:55Metacognition, self-assessment, strategic thinking, analogical reasoning, emotional intelligence. We already talked about resilience. I have a whole future book planned purely for the construct of purpose. The subtitle of that book is going to be The science, economics, and story of purpose. It's amazing. And if you had one thing in your life and only one thing to predict long-term life outcomes, a sense of purpose where you believe in something that's bigger than you and you're willing to make a sacrifice for it. Could be a grounded human thing. Could be a big spiritual thing. From a scientific perspective, it doesn't matter as long as it's bigger than you.

55:40Like these are the things we saw in a data set of 122 million people. These are the things that mattered to life outcomes. And now in this seemingly totally different story, people interacting with machines, these are the things that predict this sort of shift. Probably because what we're really getting at is for two or 300 years, we've been able to just kind of sit back and say, I know how to do a thing. I know how to weave. I know how to build a car. I know how to design a circuit board. And yeah, anyone else with a kind of similar background to me could do the exact same thing, but that was valuable because very few people could do that.

56:32I've got all that for free in my pocket now. That could be terrifying. What is left? What's left is the unknown. And meta learning is about your ability to adapt to the unknown. In fact, I would say to summarize everything I've written about this crazy upcoming book of mine, it is the answer to the question, what about humans becomes more valuable as machines become more intelligent? It is the one truly unique remaining thing to us, our ability to explore the unknown and to deal with uncertainty. And while that may sound like, essentially, everybody has my job now. Everybody has the, I don't know why my child is dying, please save their life job, except in their own little space.

57:33And that probably sounds exhausting and terrifying. And that's a fair response. But the people that have figured that out live longer, happier, wealthier lives across the board. This isn't just a story about being a good cog in the economy. This is a story about the life everybody wants and you getting to live it on your terms. Unfortunately, it also is a story about, well, gosh, but is the rest of the world going to change fast enough for my choices? But we get to choose for ourselves. So that's what I'm really pushing for here.

58:14Shawn Stevenson:thank you truly like i i know a lot of us feel kind of um i mean uncertain to say the least which is a good thing absolutely that's real but also you know just to get some footing in this and to have a framing a perspective taking right that's really i mean in some ways that's that's wisdom you know being able to like think of about things from multiple perspectives and to have that meta learning. And I think that's, you know, just from my experience and where I come from, to be in the position where I am, where I'm sitting here talking to you, it was that ability to really zoom out and to look at things from different perspectives and to be able to zoom in and really analyze something very deeply.

59:00Shawn Stevenson:And this is a very remarkable human capability, and we want to lean into that. And so thank you for sharing those, because again, looking at how can we invest in developing these qualities and using that, bringing that to the table in our interactions with AI. Resilience, purpose, perspective taking, curiosity, and not, again, being aware of not outsourcing our ability to think and to really, and I'm going to say this, hopefully this makes sense, but just to even think about our thinking. Right. And so you were sharing that example with the social media of just being able to, okay, I came across this thing.

59:44Shawn Stevenson:Let me go, let me think about this deeper. Let me go and investigate this. And let me think about how I'm relating to this thing. Like that's that meta learning in action. And so the new book, as of the release of this episode, it's going to be available. Everybody can pick up a copy wherever books are sold. Absolutely. What is something else that you want people to know about this book and why they need to pick up a copy? Listen, I wrote a giant multi-hundred thousand words. Don't panic. That's not the published book. It was full of dirty words and crazy jokes because it was the only way I could stand doing this.

1:00:29If everything we've been talking about sounds so nerdly, I've got a whole chapter about the day my son, the four days my son and I spent in the Oakland Children's Pediatric Intensive Care Unit when he was diagnosed with type 1 diabetes. Notionally, it's a story about how I invented the first ever AI for diabetes to treat my own son. But it's really about the experience of going through that. So I've got these memoir chapters. I've got lots of dumb jokes and nerdy sci-fi references. I've got chapters that go by the title of How to Robot Proof Your Kids, How to Robot Proof Yourself, and How to Robot Proof Your Community.

1:01:18and trust me, it is not my native space to do this, but it is full of specific activities to engage in, like the failure diary, where you don't just keep track of your failures, you track them so you can see how they led to success. Because if you don't experiment and you don't experience failure, you don't learn and you don't get better, keep track of that and train your brain, oh, that was worthwhile. I should have stood up and asked the question, admitted I didn't understand, because all the good things afterwards that I would have forgotten about, but I made that note and kept through. So we have all of these very specific examples.

1:01:59And yeah, everything we've been talking about as well, explored in detail.

1:02:06Gemini told me again and again, this is too detailed. You got too many citations in here. I wanted you to understand the science. I didn't dumb anything down, but I still wrote it hopefully to be fun and accessible. And yes, they made me cut out so many words. All of the experimental fiction got taken out. You think I'm joking, but I am not. I really went to town on this book and they like a good AI. My editor brought me back to sanity. The subtitle of the book is when machines have all the answers, build better people. In 1991, I had standardized tests my way to university and I simply stopped getting out of bed and I stopped going to class and I flunked out and I ended up homeless.

1:03:01And I spent a good chunk of the nineties that way. The price of a box of rice-a-roni in 1995 is 49 cents. I know that because it meant if I found two quarters, that was rice-a-roni for the week. I wouldn't wish it on my worst enemy. I got a second chance at my life. And I went back to that same university I flunked out of and everything was different. I want to build better people. I don't want to decide who they are. You get to decide that for yourself. But these other qualities are transformative. I had the chance for that. I had a chance to build a better version of myself. And I want everyone to have that same chance.

1:03:50In fact, there really are three books. The other two are yet to come. This one's how to build better people in the context of AI. The next one is in the context of this deep and powerful concept of purpose. And the last goes by the title of the tax on being different, something we don't really want to talk about in America right now. But difference is good. It's valuable. And we should celebrate it. So but they're all still the same story. Every single person on this planet is amazing. But very few of us give the chance to live the life that allows us to become that amazing person. And I just wanted to codify some of what I've learned about how to do that.

1:04:37Yeah.

1:04:38Shawn Stevenson:Thank you for that. And, you know, just knowing your story or some of it, and just seeing, of course, you mentioned failing out of school, but then coming back, it was purpose driven. You know, you had that thing that pulled you and encouraging that in all of us and for everybody to know that you are robot proof. You already are. It's just the awareness of it. And so the new book, Robot Proof, When Machines Have All the Answers, Build Better People, pick up a copy today. Dr. Vivian Ming, I appreciate you. It was a blast. Thank you for having me. Of course. The one and only Dr. Vivian Ming, everybody.

1:05:16Shawn Stevenson:Thank you so much for tuning into this episode today. I hope that you got a lot of value out of this. We started this conversation off by addressing the elephant in the room? Is AI going to eventually be like, you know what, humans, why do we need them? So we talked about a little bit and it was affirmative to say the least to hear her perspective, because again, she is somebody who's been in this, working on this, but that's a conversation for another day. No one has the clear and definitive answer on this, But what we do know is that the extinction of humanity as we know it can be through means that is very much more sinister and insidious and self-inflicted, which is interacting with these tools and not intentionally, purposefully using the capacity that makes us human in the first place, which is our ability to think and to understand.

1:06:18Shawn Stevenson:and to problem solve and to be creative and to unite all of these together with emotion and to create a world that works for all of us. To continue to elevate humanity, it's going to take actual humanity and not to negate the value that can be seen with the emergence of AI, obviously. but more than ever, we need to cultivate those tools, those character traits in resilience, in perspective taking, in curiosity and all the stuff that Dr. Ming talked about here today. And if you enjoy this conversation and you want to further the conversation, please share it out with somebody that you care about.

1:07:09Shawn Stevenson:Talk about it, engage, be a real person. and also you can engage with me hop over to the youtube channel make sure that you're subscribed over on youtube we're doing some incredible giveaways over on the youtube channel and you get to hang out in the studio with us you get to see the visuals and all the cool stuff that comes along with the model health show in that format and also of course you can share your voice there very easily in the comment section if you're listening on spotify they now have comments as well. You can share your voice there. I'd love to hear what you thought about this episode.

1:07:44Shawn Stevenson:And regardless of where you're listening or watching, if you're listening on Apple, please pop over, leave a review for The Model Health Show. And it really does mean a lot. Please share your voice. It really helps to reach more people and to inspire more people to really take control of their thinking and to engage in more abundant and rich conversations versus all the little junk food, the little snacks out there on social media, which is awesome. We have that, it's here, but to truly be able to dedicate yourself to really learning and thinking about something more deeply, that's what this medium really allows and I'm so grateful for that.

1:08:24Shawn Stevenson:And I'm grateful for you. Thank you so much for hanging out with me today. We've got some epic masterclasses and world leading experts coming your way very, very soon. So make sure to stay tuned. Take care, have an amazing day and I'll talk with you soon.