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Chapter 1: What is the main topic discussed in this episode?
we're going live let's see how we're doing is locals live yep there's steven oh good morning you guys there's magician good morning bookish we have a special guest today you guys we're going to introduce you good morning good morning welcome to the scott adams school just a reminder This is not to replicate Scott where you don't think we're Scott. We could never be Scott.
This is the Scott Adams School. And we're just here to commune, have a good time, keep learning, keep growing. And hopefully we'll always have something interesting for us all to learn and understand and talk about. So we can't do any of that, you all, until we do one thing first. So gather in, gather in. We have to get this going. This is a short sip because we have a lot to talk about today.
So is everyone ready? Everyone looks good. Hey, Nikki. Okay, let's mute for the sip. Here we go.
Hey, everybody. It's good to see you. Come on in. Gather round. It's time for the best part of the day, except for the rest of it, which is going to be pretty good, too. Yes, it's going to be coffee with Scott Adams this morning. And all you need, you don't need much. You need a cup or a mug or a glass, a tank or chalice or stein, a canteen jug or flask, a vessel of any kind.
Fill it with your favorite liquid. I like coffee. And join me now for the unparalleled pleasure of the dopamine of the day that makes everything better. A simultaneous sip. Erica, I see you there. Dr. Funk Juice, grab your mugs. Marla, come on. Go.
Ah. Ah. I got a little bit of a headache. Okay. I needed that this Monday morning. Erica, he saw you. He saw me. So welcome, everyone. I'm Erica. And let me just pull this up here. You guys want to introduce yourselves really quick, and then I'll introduce John.
Good morning. This is Marcella.
Good morning. This is Sergio.
And Owen.
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Chapter 2: How does AI influence our cognitive processes?
your perspective on these things in a way we haven't before. So John Nostra, welcome to the Scott Adams School.
Thank you. What a pleasure to be here. I had some ideas about what to talk about, and then that clip completely took me off path. And I want to do something completely spontaneous. I warned you guys about this, that I'm going to channel this down. But Scott in that clip said, gather around. Sit down, gather around. That is the essence of technology today.
And I want to talk about that just briefly because the notion of gather around actually can be hearkened to ancient... text, the Upanishads, which are old Hindu spiritual texts. The Upanishad is actually Sanskrit for sit up close, to sit up close. Now, what does that mean? Doctors walking down a hallway on rounds, talking to one another.
A guru sitting with a master talking about a particular issue. a group of kids sitting around a campfire. That is the essence of sit down, come up close. That's gather around. And what we're seeing today for the first time is there's a technological component to this. And it's not fearful.
It's that now we have the ability to interact with AI with large language models where we can have that almost intimate conversation And that reflects very, very much as to what Scott was saying is, come on, sit down, gather around. And I think that's the essence of where technology is going today. It becomes personal. It becomes connected.
And probably the most interesting word here is iterative, that we have an engaged conversation. So I'm going to stop there and take a breath.
Well, don't take too long of a breath because you have so much to offer. And I think I also wanted to point out that you've written, what, over 500 articles for Psychology Today. Is that right? And when we first got on the phone, if you're old enough, you remember Doogie Howser. So you asked me if I know who Doogie Howser is and that you were writing medical papers for Harvard at 18 years old.
Yeah. And you were going in that field until... I was a smart aleck, I guess. But it wasn't because I was smart. It was because I was interested. It's because I had a real unique interest and connection with things like physiology and biology and stuff like that. So my early path took me to what was going to be medical school. And it's just too hard.
The nature of medicine today is very regurgitory. Class is, here's the cranial nerves. Here's a book on anatomy. Now, next week, we're going to have a test. So you memorize it, and then you're going to regurgitate it, or you're going to be a sponge, and they squeeze it out after that test. So for me, it didn't really align with my interests. I tend to be more of a creative or strategic thinker.
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Chapter 3: What role does cognitive offloading play in using AI?
And I want to take that note and go back, go back a few hundred years and kind of put this into a little bit of perspective because the word think is going to be real interesting and real important for us. So a few hundred years ago, a guy named Gutenberg did something that helped us think. He created a printing press. Now, what did that printing press do? The printing press unlocked words.
So we could disseminate something like a book. Now, in those days, it was principally the Bible. But here's an interesting observation. Back in those days, innovation, technology, if you will, created something that there was no need for. So that's the first sort of paradoxical thing here. So I'm going to invent a book when no one can read. So how the heck do you manage that?
So that was sort of the first inflection point in the dissemination of thought and thinking and knowledge. So we unlock words. It took a few years, and we see that with innovation all the time. Just because something is new and innovative doesn't mean it aligns to market adoption. So sometimes it takes time. Sometimes it's immediate. Sometimes it takes time.
Then we move up in time when we get to this other thing called the Internet. And what did the internet do? The internet, and principally Google, I guess, if you really wanted to talk about search in its contemporary capacity, Google did something that was very similar to Gutenberg. Google unlocked fax. And that was the second stage in this sort of thinking dynamic, that it unlocked fax.
Now, that's the good news. The bad news is it unlocked fax in a way that is very cold- It's not very interactive. It's very reaction. Here's the question. Here's the answer. It's transactional if you're looking for a word. So Google is transactional. And you know, back in the days when you type up, you know, where's the best Mexican restaurant in Rumson, New Jersey?
We all know it's Casa Comida, by the way. But anyway, it gives you a long, complicated answer. You have to find the link. You got to back around. So that was the second sort of inflection point, if you will. We unlock words and we unlock facts. And that was great. That really transformed the way we could think.
But now what happens with these large language models that are really changing everything so dramatically? What large language models are doing is unlocking thought. So that's the transition, unlocking words, unlocking facts, and unlocking thought.
The interesting thing about large language models is that it is an iterative dynamic and that our ability to engage with a large language model back and forth actually activates thought. And that's kind of where we are today. Now, what does that mean? How does that fit into the construct of things like the industrial age and the digital age and all that kind of stuff?
I would argue that we're moving into a new domain, and that is the domain of thought. That's why I call it the cognitive age. And it goes right back to that fundamental reality written thousands of years ago in the Upanishads that simply says, as you think, so you act, as you act, so you become.
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Chapter 4: How can AI assist in medical diagnosis?
But there's also the opposite, which is I think the article I posted today talked about it as cognitive debt and that you might be offloading your thinking to the AI and therefore not learning how to think.
and i i have seen similar things across all of kind of education use cases for ai where it can be a great tutor and help you learn if you use it the right way but it could also just give you all the answers and keep you from learning and there's a big fear now that a lot of people are never going to learn the skills they have to know and
on top of that, the other thing I'll layer on and let you comment is I've noticed, or at least there's been people that have commented that AI is kind of reflect back your level of thinking that if you are really kind of dumb and ask it, questions that kind of are what an 80 IQ person might say, then it's going to kind of reflect that back at you and adapt to your level of thinking.
But if you're more of a PhD super genius and you use all sorts of big words and you know, it's different than it's going to reflect back that level of thinking or that level of conversation. So what do you, what do you think about all this? Is this going to make us all stupid?
This is, you've touched on, I'm going to reach over here. I'm going to grab something. So this is the shameless self-promotion of my book, which is The Borrowed Mind. It's coming out this week. Yes, we are doing a certain element of cognitive offloading. And there's, oh my God, there's so much to talk about in that question. So let's back up and let's humanize this a little bit.
Have you ever had a favorite teacher?
Absolutely.
Everybody's had a favorite teacher. And interestingly, it's generally one or two people. Like nobody has 10 favorite teachers. Nobody has a whole load of famous teachers. It's usually one. It's oftentimes a woman, which is because elementary education was sort of biased to more female. But I find that interesting. What did that teacher do? What did she do for you? She got you. She got you.
She delivered information in a way that was tuned to the creative frequency of your brain. And I think that's something we have to consider. So did the teacher rob your intelligence by pandering to your proclivities or insecurities? I don't think so.
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Chapter 5: What are the potential risks of relying on AI for learning?
It's a device where he actually hired a photographer, created a set, took a picture, and then took that image and enlarged it and changed it using this mechanism called the Lucy, and then painstakingly traced it and colored it in. Next time you look at a Norman Rockwell painting, take a close look. Take a close look at the, it's almost like painting by numbers.
Remember those things when we were kids, the painting by number thing? Norman Rockwell's art is very, very specific because he was constrained by the technology he embraced. And that's a really interesting dynamic, constrained by the technology you embrace. Now, if you look at the Norman Rockwell, the more contemporary, his most contemporary work, look at his signature. It's a stencil.
I almost want to curse here. This gets me so angry. He didn't even sign his name. The signature is an expression of our humanity, right? It's Picasso. It's whatever it is, right? It has a certain energy, a certain style. Well, what he did is he actually took a stencil and made Norman Rockwell.
Okay, now why I'm bringing this up is because this goes back to the earlier question is, is it going to hurt us? Is it going to offload cognition? And I think that the answer is yes and no. What I find interesting is the way Norman Rockwell responded when asked about the Lucy, the Lucy machine. Now, keep in mind, no one talks about the Lucy. That was his secret.
If you go to the Norman Rockwell Museum in Lenox, Massachusetts, don't ask them about the Lucy. They get very angry. They get very upset. Because it's kind of like asking, did you write that essay or did ChatGPT write that essay? It's that same social, cognitive, emotional dynamic that we're seeing play out here today. So what Norman Rockwell said I thought was really interesting.
He said, the Lucy is a horrible machine and I'd be lost without it. And I think to a certain degree, that's the delicate balance that we're seeing with large language models. Do they cause cognitive offloading? Well... I don't know Erica's cell phone number, right? I just type in her name. I don't remember. Do I need to remember it?
What is the appropriate level of cognitive offloading in our world? If a medical student needs to know the second metabolic intermediary in the Krebs cycle, which happens to be 1,6-fructose diphosphate, probably going to get an A on his biochemistry test in medical school. But does that make her or him a better clinician? These are very, very complicated questions now.
Yeah. And I mean, I think it will depend on the type of thing you're talking about.
It will depend. That's such an empty answer.
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Chapter 6: How does AI reflect the user's cognitive level?
But we often statistically guess into that spot. There was a study that showed how well LLMs did, doctors did, and doctors using an LLM do in looking at clinical scenarios. And they found something very interesting here. All three of those constructs did the same. They all got 76% correct. Doctor alone, LLM, or an LLM and a doctor combined, which I thought was really interesting.
But here's the interesting thing. And this is where it gets to the point where you're worried about about this idea. Well, I want the doctor right there to make the diagnosis for me. If you look at the clinical chain of reasoning, in other words, don't tell me you had a heart attack, okay, doctor. Tell me the five reasons why the ST segment is elevated on my EKG. That's a classic side.
It's called a STEMI, classic side of a heart attack. Tell me the five reasons why that might be elevated. pericarditis, early repolarization, ventricular aneurysm. There's a list. Most clinicians will not get that. So here's the challenge. Sometimes augmenting clinical thinking and reasoning is very, very helpful. So I think that we're going to see...
The interesting thing here is when my wife comes back from the pediatrician, I ask her, what did the doctor say? And she usually gives me an answer. Oh, we got a prescription. Everything's fine. Tomorrow, the question is, what did the computer say? But that's not a full sentence. That's actually, there's a comma there. So the rest of that question is really very telling.
It's what did the computer say, comma, and what did the doctor do? And it's that sort of cognitive functional dance that's going to be very, very powerful. So when I go into the emergency room and they say I have a heart attack, my differential diagnosis should be scrubbed analytically by an AI. So it's not one versus the other.
That's one of the pitfalls that we find with AI is it becomes a zero-sum game. It's they win, we lose.
Yeah. And what I've also noticed is that at least in my use of AI, I found that it's very useful, but it's also based on my expertise. Like I know what questions to ask to get good answers. And I think from everything I've read about it, people who don't have a lot of expertise don't get good answers a lot of the time.
And it's because they don't know what questions to ask and they don't know how to guide the AI in the right way.
so it seems to me like we do need to maintain some ability for people to gain enough expertise to control and guide the ai at least until they don't need people anymore well also oh and the other thing i want to chime in because i see it in the chat is that a lot of us don't trust doctors anymore so do they have an agenda you know do they have a political issue are they jaded like who knows so
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Chapter 7: What are the implications of AI on human creativity?
Well, What about the doctor? You know, Erica, you mentioned that, and I think that's so true that maybe we should worry about the human bias in a lot of our information. So yeah, AI is biased, but I think that AI is very helpful to me because I'm a geek. I was in the car the other day and I was actually having a conversation.
I think I was using ChatGPT and I wanted the model to teach me about the strange qualities of subatomic particles. what I find, what I know, I know I'm a complete geek, but they ran out of words. Like when you had these quirks, these funky quirks, well, they ran out of words to describe them. So they started using words like beauty, truth, charm, upness, downness to describe them.
So I had a really good discussion with AI about something I know very little about. So Yes, you need to be a master of your domain, but you don't have to be a master of the knowledge domain. So I think that that's very helpful for me. Now, I want to get to something because I know we've gone like almost a half hour into this mumbo jumbo.
I quick just wanted to, if you don't mind, ask Sergio and Marcella if they have a question at this point for you before we move on.
You thought Brian talked a lot? now you guys can't even shut me up so yes no i want you to keep going to brother by the way we we get together and like little sparks fly anyway yes please ask some questions
surgeon hey john yes i i checked your stuff yesterday i was trying to learn more about what you do and um i love that uh you are focused on the health uh part you know and because that's a very important uh um aspect for me to always to know how are we maximizing our doctors And you already answered a lot of those questions. That was great. Brian Romeli gave us this reframe, right?
That instead of calling it AI, calling it IA, right? Intelligence amplifier. And I love that reframe. I wanted to ask you, I always tell people to not get into conversations with AI, like chats back and forth. Because I personally feel like it's getting me, like Owen was saying, he tries to agree with me a lot. And it takes me down different paths. So what I do is I just dictate to it.
I just put a little microphone and I say in a voice memo, I don't allow it to say like, stop, you know, let me, and I just, and she answers to me. My question is, when it comes to health, right, and the mental health part of it, of talking to an AI like this, can you also, agreed that some people are more susceptible to that. And because I am, that's why, because I know I am, I avoid it.
So you are so spot. I'm a sucker for AI because, you know, I type in a sentence and then Claude or, or, or whomever, uh, writes back, oh, John, that is such an interesting observation, right? And then I'm stuck. I'm like, oh, yeah, really? Is that really? I'm so smart. So you got it. In my book, I talk about AI in three contexts. The first is the promise, right?
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Chapter 8: How can we balance AI use with maintaining critical thinking?
to psychiatry and psychology. There's been a lot of action there. I think that probably the fringe cases, we have a normal distribution of bell curve. Those 10% on either side are vulnerable. So let's say I told an LLM, I'm feeling a little blue today. And then all of a sudden we start falling down the rabbit hole. Oh, what shade of blue? Well, it's really dark. Oh, how dark is it?
Well, it's a black hole of conscious awareness, whatever that is. So we have to be careful about that. Most normal people can tolerate that. In fact, I would argue that that's the friction of life. And that friction is what drives... the process of understanding. So when I said getting to A to B, getting from A to B with an LLM is instant, right? It just goes from one to the other.
Getting from A to B for a human is often toil, controversy, struggle, joy, wisdom, insight, all sorts of things. But I think that we have to be careful with large language models because they are... Now, what did Brian... Brian flipped it, right? AI, IA, intelligence amplified. I'm going to give you mine because I disagree with Brian on this point.
I think that intelligence amplified is not intrinsic to the model. I think that's a result of the model. So I can say, I can call a hammer house amplified, builder amplified, right? Because it's just going to help me, you know, whatever. I think that, and this is really a bit controversial. I don't think that artificial intelligence is intelligence at all. I think it's anti-intelligence.
I think it's anti-intelligence. Now, let's unpack this a little bit because it's a little complicated. What does an apple look like to a large language model? What does an apple look like? Well, let's talk about what it looks like to us. We see an apple in... Three dimensions, right? Three spatial dimensions. Okay, pretty simple. There's the apple in my hand.
Some smarty pants might include time, but that's a very interesting thing. And we'll get to that later. Do you know that large language models don't have any idea what time is? They are atemporal. They don't exist in time. But when they see an apple, the old models from a few months ago would see that model in 12,288 dimensions, right? What the hell does that even mean, right?
The new frontier models, the new chat GPTs actually look at the apple in 25,000 dimensions. Now, the reason I'm talking about this is because I want you to be confused deliberately. The perceptual domain, the cognitive capability of a large language model is vastly different than humans. When we think of an apple, we think of three dimensions.
We think of, let's see, apple a day keeps the doctor away. We think of apple computer. We think of apple Garden of Eden, right? Adam and Eve. We think of about 25 linguistic associations combined with three spatial dimensions. That's it. But an LLM looks at an apple in 25,000 dimensions. Now, so we live in three dimensions.
Sometimes people talk about multiple dimensions called hypercubes, which are really cool mathematical structures. Sometimes people who study string theory get really wacky and they look at string theory in the context of 11 dimensions, which blows their mind. 11 dimensions? As a human, we have no ability to conceptually understand that.
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