Time Worth Wasting: Preserving Meaning in a Predictive World

Uh we're kicking off with a headliner. It's got an intriguing title. Time worth wasting preserving meaning in a predictive world. Well, to tell us more, please welcome an incredible speaker and that is Jason Snyder who is a futurist and a Forbes contributor. Warm hand of applause, please. Hi, thanks so much. Uh, I'm very excited to be here. Um, I'm going to start um, you know, with that gratitude, but also if you indulge me because I've told I got a minute. Um, my son is really vexed. He's 17 years old. His name is Bruno and he couldn't come on this um, trip with me and he's really vexed about it. So, if everybody could just say hi to him, that would be awesome.

Um, say hi, Bruno. Hi. Hey, cool. Thanks. Awesome. Thanks so much. He'll be really pleased with that. Um, so I'm going to jump into it. Um, as Bill said, I'm going to be talking about wasting your time. Uh, because wasting your time is a really important concept in the construct that we've created uh with AI. And I'm going to start this talk about AI in a in a weird place at about 300 B. CE. And that's the Lighthouse of Alexandria there, which was um up and running during that time. That time in history was very important because uh during that time almost more than any other there was a lot of theological and apocalyptic writing happening.

And in that in this text in the book of Enoch um there's a story that to me is very very modern. In fact, it feels a lot more like a tech prophecy than a kind of ancient scripture. And the book of Enoch, if you're not familiar with it, is about a a group of divine beings. Uh they're known as the Watchers, and they come down to Earth, and one of them, Zazil, teaches humans how to work metal. And at first, this seems like this unbelievable gift, this tool that's going to be a massive shortcut to power. But it becomes clear very quickly that what's happening is that knowledge was premature and the humans weren't ready for it.

And so with that wisdom it be was unearned and out of order. It had become a curse for everyone because it knew something that we are only starting to realize which is that not all knowledge is neutral. And this idea threatened the theological order. not because it was incorrect or false, but because it was too crazy. It was too wild, too cosmic and really unconcerned with hierarchy. So, it's my opinion that the book of Enoch, you might not have heard of it, wasn't lost, but it was suppressed. Today, it became it's still part of the Ethiopian Ethiopian Orthodox faith, but it's excluded from all the other Bibles, and it was buried again because I think it was too powerful.

It suggests that divine rebellion and human curiosity, those two things are inseparable. And that's a very dangerous idea. And like our buddy Oenheimer here, he wrestled with these concepts. Is all knowledge sacred? And should all progress be pursued? These are questions that we need to ask ourselves today. So let's jump ahead to today. Today, our metal, like in that story, is silicon. And our forbidden knowledge is artificial intelligence. So, we've built machines that don't just process our world, they predict it. And they don't just watch what we do, they learn from us, they train us, and they reflect us at scale. But in this world that we've created that's completely optimized for efficiency and automation, a very human thing is starting to fall through the cracks.

And that thing is meaning. Because what's happening is we're flattening purpose into performance and confusing speed with substance. These systems that are filtering our lives are filtering every aspect of it. what we see, what we buy, who we hear, what we feel. Because these systems, they're not engineered and designed to nourish us. They're built to measure us. And we've optimized the entire internet to keep us there, not to make us wiser. And this is evidenced through all the habitual behaviors we have with these utilities. We autoplay the next thing. We scroll endlessly. We test headlines for clicks, not for truth. So, we've constructed this digital world that feeds on attention, but it's obfiscating context and intention.

And not everything that's measurable is meaningful. So, I'll talk a lot about friction. Friction is very important. Imperfection, wasted time, these aren't bugs in the human system. They're the foundation of meaning. And the thing that proves this out is stories. So that super hottie is my wife and clearly I got the better end of the deal. But um she's a professor of intercultural communications and years ago she said something to me that really changed the way that I think about brands and belief systems and everything. She said that mythologies are living entities and as a result my curiosity around these things became totally rrooted. So I went out and began to examine mythologies but I didn't treat mythologies like fossils.

I treated them like organic living material and I looked at them as systems that evolve and adapt and compete and I mapped them out with genealogies like in family trees and I understood or started to understand anyways not just what they meant but where they came from and how they mutated and why some survived and quite obviously some myths fade and others flourish but they don't do that because in a scientific sense they do that because they're more durable. They resonate and then they survive friction and they do that across generations. And what I learned as a result of that is that meaning isn't fixed. Meaning is something that's alive. Meaning is something that survives.

It's shaped and stretched and adapted and strengthened by friction. So, and I'll say this a couple times, but stories aren't just content. Stories are memories encoded in myth. Stories are really a cultural immune system because they don't just reflect who they are. They protect us from what we might become. If you think about it, these myths aren't designed by a committee. They weren't optimized for engagement. They earned permanence through repetition, conflict, and reinterpretation. Generative AI doesn't do any of that. Generative AI is a big kinko machine that remixes data, right? It flattens information and stories. It reassembles them without context, without lineage, without exposure or without any stakes inside of it. And inside of that flattening, we are creating an illusion of progress because speed is not growth, prediction is not perception, and utility is not truth.

So let me talk about friction a little bit more. Friction is what structures our time and time is the canvas where we make our meaning. Without friction we don't have any resistance and we don't have resistance we don't have identity. So a smooth life is one without any texture. And that smooth life will become slippery and then empty. So the ultimate question we're facing now isn't what AI can do. It's what we're choosing to spend our time on. Because time is more than a unit of productivity. It's a measure of meaning. And I bucket time into two categories because not all time is created equal. I call some of it flat time and some of it deep time because time spent making isn't the same as time you spend clicking.

One time deepens and the other dissolves. So friction is what gives time weight and meaning only grows in the weighted kind of time. So I'm going to give some metaphors now and you'll probably be familiar with some of them. So this is the the lily pad anal metaphor. So imagine a lake and every day the number of lily pads on that lake will double, right? It's geometric growth. On day 30 the lake is totally covered. So, what day is the lake only half covered? The answer is on day 29. And that's geometric growth, right? It feels linear until that very last moment until you realize there's no time left. And that's where we are with AI.

We're on day 29 because progress has been doubling slowly. What we're seeing with AI didn't happen in the last 3 years. It's been decades, right? and we didn't notice it because it was kind of beneath the surface and bubbling up compounding itself in silence and along the way it's been optimizing everything but more isn't necessarily always better and here's another metaphor and I'll use a computer graphics metaphor for this so that's a 3D rendering of of Beethoven right so at 60 polyons you know that bust is abstract at 600 you start to see the face at 6,000 you can make out that it's Beethoven but at 60,000 there's not a big difference there's Not a big difference between 6,000 and 60,000.

And AI works in a similar way. Another metaphor is the coastline paradox. If you look at a picture of the coast from outer space and you keep zooming in on it, it's almost like that coast will grow infinitely because the closer we zoom in on it, the benchmarks change, but it doesn't mean that the size of the coast is infinite, right? It it doesn't mean that a system is growing in wisdom if we keep adding more processors to it, right? It means that we've simply changed the ruler of measurement. So that's Leopold Ashenberer. And I'm not making fun of Leopold or giving him a hard time. He's clearly a genius. At 15 years old, got into Columbia University, graduated validictorian, and led the super alignment team at OpenAI until he was fired by because he said that there were huge vulnerable safety issues with their product.

Once he was fired, he went on and published a manifesto um where he said it was, and I quote him, strikingly plausible that we'll get to AGI by 2027. Now, I don't necessarily agree with that. And the argument that he makes in there, and I'm being a slightly reductive here, is that AI is going to 27x its capabilities every year. But if you do the math, that is what he's saying. So, he's presenting AI development as this unstoppable exponential force that's destined to dominate everything we do, our global GDP. It's going to reshape our economy and our society, not in years, but in decades. And Ashen burner like so many other people are mistaking faster math for deeper intelligence.

Right? But just like the problems that I brought up, it's built on compute, not on consequences, right? He's predicating everything on curves, not on culture. And as I said before, stories aren't just content. And therefore, 27 times performance is not 27 times meaning. They're different things. So if we pause here for a minute, we have to think about what happens if we take exponential intelligence and run it on linear understanding or if we build machines that learn faster than we do, but they don't know what they're learning for. And that seems to be the situation we've gotten ourselves in. So that's like thinking we can continue to double those triangles and the face is going to change and become clearer and clearer or that we're going to measure that border with an ever shrinking ruler and say, "Oh, you know what?

The coastline of this country is infinite because at some point reality pushes back. Computers isolate complexity. They count it. They compress it and they predict it. Biology doesn't just observe complexity. It joins it. It entrains it. The distinction there isn't speed. The distinction is that it's a relationship. Because entrainment means syncing up. Right? When your heart rate adjusts to your breath. When you see fireflies blinking in unison in a field, when your brain waves sync with a rhythm at a con at a concert, or when a baby aligns its breathing with their parent when they're holding it, that's entrainment because biology adapts in real time. And that's a distinction that AI doesn't understand because life is non-local.

So there are things that can influence each other without proximity. And that's how quantum particles do it, right? Well, humans do it in the same way and so does culture. Life is also a causal. There's no real clean traceable line from action to outcome in life. And life, most importantly, is entangled. You can't always say what caused a movement because memes don't go viral because one person clicked on it. And a revolution doesn't happen because one speech is made. In the same way, your mood doesn't shift because one neuron fires in your brain. And that's because influence jumps. So real life is about fields and feedback and emergence. It's about people that are non-local sinking to a shared belief.

Meaning itself isn't just bi biological, it's social and it's viral. And that's why prediction isn't understanding. AI trains on everything we do, but never on why we do it. It sees the purchase, but not why you're longing for that thing. the scroll that you're you're scrolling for but not the ache of why you're scrolling for whatever reason. It sees the playlist but not the memories that it evokes. As a result, we're not really able to understand what's real anymore because we're drowning in prediction and simulation and spectacle. The fake news isn't a glitch. It's the system. And the reality, the shared kind is slipping as a result of this. So Bruno that I mentioned at the top, my son, when he was about four years old, for the first time I took him to see fireworks for the Fourth of July in the United States, and we're laying on a field on a blanket underneath the night sky and the fireworks started.

And he leaned over to me and he said, "Dad, is that is that real?" And I thought that was like the greatest thing in the world, right? because I just spent decades uh inventing at patenting commercializing uh artificial reality virt virtual reality uh massive in this field and deploying these things at scale and I thought wow what a seminal moment that my son is asking me this question that we can't distinguish it but the truth is that wasn't validation it shouldn't have been validation for me it was actually more of a warning and it took me a minute to understand that so building these synthetic worlds have real consequences. And as I said, I've spent my career building these environments, these fictional realities, these artificial agents.

And now we've trained machines not just to simulate the world, but to predict it. They're designed to predict it, to rewrite it, and ultimately to replace it because we're abdicating control and consenting to that. But prediction, it turns out, comes with secrecy. Because AI is actually designed to censor, not to oppress, but to protect the illusion of control. And you've heard many other speakers up on the stage talking about that today, right? The proprietary data, the proprietary models, the black box that's behind it. You can't see how it arrived at its conclusions. Um, and you're not meant to. That's not intelligence. That's secrecy at scale. Friction is reality's anchor. And without the friction, we lose touch of what's real.

And without the resistance, we accept that simulation as truth. So we don't just need friction to slow things down. We need it to remember who we are. And the same thing is happening with AI, right? We're throwing more chips at the problem and saying that that's going to give us deeper meaning or give us meaning, right? Stacking GPUs instead of asking better questions because meaning is never going to compound at 27 times a year. It doesn't double on command and it doesn't scale. So, you know what? If we really can't predict what we'll do, you know, what we'll want, uh, all of these things, are we going to lose mystery? Are we going to lose our agency?

Are we going to lose the joy of not knowing? Because the greatest danger isn't that AI is going to fail. It's that it doesn't. And so, maybe that book of Enoch that I was talking about at the beginning of this thing wasn't a warning about disobedience. I think it was a warning about acceleration and what happens when power arrives before readiness is established. And like Zazzle, I don't think he was necessarily the villain in the story. He was just early and that mythology maybe needed to resonate for a couple thousand years. Um, you know, before we got to a reason for it. So these modernles, the compute curves, the benchmarks, the tokens, the trends, they're maybe bringing us gifts before we're ready.

And like the watchers, we might not survive them. So the question is, what do we do, right? And so I put these five axioms together. Maybe they're gu guidelines to help to guide to to guard our reflection, right? Because truth isn't created by machines. In fact, it's distorted by them if we aren't careful. We need to protect our agency because the machine can act, but you have to decide. We need to choose what's worth doing, right? Time worth wasting. Prediction is cheap, but pursuit of things is sacred. We don't want to outsource our judgment. We need to be careful what we abdicate in our willingness to surrender control. And we need to remember that AI is the mirror and whatever we feed it is what it becomes.

So we can't predict forgiveness or playfulness, interpretation or disobedience. Right? AI can simulate knowledge but not wisdom. It can replicate tone. It does rhetoric very well but it can't do that with tenderness. Right? It can model behavior but it can't do that with meaning. Prediction requires patterns. But humanity, we interrupt patterns. And that's where the soul, if you believe in that kind of thing, lives. So to make it more concrete, um these are things that don't scale, that don't optimize because they're sacred and things that AI fails to grasp. And these are all very personal and very real for me. So that's me. Um I wore a Star Trek uniform to school when I was little every day.

Um so I've always kind of been like this. Um and no prompt could have generated the weirdness that embodies me. this person sitting in the audience, she's there. I raised her up and got her to walk her down the aisle last year. Um, and that's that moment here that you see before that happened. That was a lifetime unfolding. There was no audience, no output, no metric for that, right? These things don't scale. And Bruno drew this when he was little, right? So that's more expressive than 10,000 frames of training data. These are the types of things I'm talking about. This is the kind of friction that I'm talking about introducing. This is the dissonance that exists today.

So meaning isn't a straight path. It spirals and deepens and echoes. It's more like a micelium network than it is a SQL database. Right? You can't map it out. It's not a pipeline. So the paradox is this. Just as destruction compounds, so does redemption. So if we orient ourselves now in the right way, right, geometry can still be our friend. all those things we talked about and those small acts of resistance that cause friction can ripple through. It can scale. So why am I saying this? I'm not saying this as an engineer or a scientist. I'm saying it as a father. I'm saying it as a husband. I'm saying it as a son. And I'm saying it as a human being because I'm watching the future come too fast for the structures that we're still living inside of.

So we need to stop designing systems to eliminate inefficiency. We need to design for authorship, for difference, and for depth. Because the future isn't predictive. The future is participatory. What can you do? Be conscious of what you're feeding the machines. Resist the urge to optimize everything in your life. Teach children boredom. Make something that doesn't scale. And let time feel slow. Because slowness isn't inefficiency. It's reverence. And every time you choose friction, you're choosing to decide to matter. Ultimately, what you should do, stay human deliberately. Thank you.

Thanks so much, Jason. That was really thoughtprovoking, I have to say. And I've got a lot of thoughts here crammed into my head, but one thing I was thinking, you know, you're you're talking about your son Bruno. Yeah.

Talking about meaning, and to paraphrase it, you know, meaning is messy in many respects, but how do you uh foster that sense of meaning in your sense of the word of, you know, I suppose making the most of wasting time

With children when they're growing up?

Yeah. Yeah, I mean I think it's about being deliberate. Um I certainly went out of my way not to regulate access to technology in any way. Um because I think when we restrict those things, it makes them precious in it makes them vulnerable to wanting those things more. Right? So um I tried to make sure ensure that engagement uh kind of on an interpersonal level kind of was was the priority and the most enjoyable thing.

Okay. And I think so make your time deliberate. I think we might have time for a few questions. Uh so if you have a question do raise your hand. We have a couple of questions here or lady in the one two three fourth row. I think let's move forward so they can the chairs can be put in without us getting in the way.

Sorry there's some fabulous red hats there as well. I note very very smart. Yeah. Well, first thank you for that was really thoughtprovoking, meaningful and deeply touched to me actually. I think a lot of Yes. Um I work with narratives and communication and so my question to you is what are the stories we need to be telling ourselves today about AI. We've heard a lot about safety, about trust, about, you know, we hear a lot about how things are getting automated and they're going to make life better in every aspect. And then we hear stories of uh scare you, you know, fear and uncertainty. So what really is the story that will bind us together as humans and take us into the next level while dealing with this?

Great question.

Well, I think you know that obviously it's a very complicated question to unpack, but the the the the reductive answer is that we have to be human first in everything that we do. That AI is not something that would replace us. It's something to augment us. Certainly not the first person on the stage today that said that, but that's the reality. And we need to look to construct stories and to look to one another in order to build those things to ensure that what is being constructed isn't synthetic, right? And to learn to discern the difference between artificial and synthetic stories, right? Those metaphors, are they traceable back to some sort of purpose and intent that is human uh without uh any sort of sponsorship?

Yeah,

Brilliant advice. Okay, do we have any more questions?

Just over there. Thank you.

Hi. Thank you. Um, so yeah, you talk a lot about, you know, staying human, which I think is a beautiful thing. Um, and do you have like a framework for kids, for example, they write their essays using AI to make it sound nice, to make it read nice, and then the teacher uses AI to summarize it back again? Do you have like a framework where you say, well, you can use AI as a tool, you can use it to write your essay, but you should also learn how to do it yourself to be a good human.

Yeah, I couldn't agree more. Um you know again it should be something that augment it right to help you know perhaps you know with with the prompting process but authorship you know in the truth sense needs to remain individual and and human uh it shouldn't be a substitute for authorship.

Fabulous. Um okay any more questions? Do we have any more questions in the audience? Oh fantastic. We'll just

So I compare this era with like you know the gold rush era and um they're like every day hundreds of new AI tools are developed and released. So um slow the time.

Yeah.

But everyone is you know hunting for something.

So h how is your take on that?

How do we slow how do we slow time? It's like it's you know it's um I I can even say it's it's um greed or

How do we waste time as you were saying?

Yeah. I I think in order to waste time, you have to discern or focus on your priorities, right? And ensure that those things are not being uh driven by external forces, but driven by your own needs and desires, right? And I think what's happening now is we start to compress things and abdicate more control to all of the algorithms that that's becoming a little bit confused and sorting our priorities based on our desire rather than our dictate is is kind of the challenge right now.

Amazing. So, look, we got a lot of good life lessons here and I think everybody's really quite intrigued. Do Do we I think we might have time for one more question. Do we have any more questions in the room?

Just here. Third, third row.

So, yeah. So, so it's a real balancing act is what you're saying. You've kind of got to figure it out. And is that something that we've all got to figure out personally? Are we going to have to turn to AI to figure that out? How how do we get that friction right? I again I think it's this this this this is the rebellion right this is the this is the struggle on an individual level to introduce that at scale and and start to demand that you know we need to step back and take a break you know to say like no I'm going to set time aside in my day to think I'm going to set time uh aside to step back from kind of what's being fed and make sure that I'm not inside this echo chamber or this continuous loop that's amplifying ideas that may or may not really represent the direction that I want to travel And how do you think then, you know, if because I think this is really we're at this kind of inflection point and people thinking, okay, how am I not going to give away my ability to think critically?

How am I going to actually allow myself to learn to think and and actually have enough confidence in my beliefs when I'm facing an AI that can almost predict what I'm thinking and what I'm going to say next? So, so what would be your tips on doing that? Uh again, it's to make sure that we're if you're engaging the AI to make sure you're asking enough good questions for the answers it's providing you, right? And to say, wait a minute, you know, is that

So you question AI?

You must Yeah. So if you're if that if if that's what you're doing, if you're engineering these prompts to get a response back from it, then the question needs to be is that is that right? Is that well what if it's this other thing? So I think to make sure that you're always, for lack of a better term, being the devil's advocate or being the having the contrarian view inside of what you're being fed, I think that can help to identify balance inside of it.

Well, that's really interesting. So be the devil's advocate when you're kind of questioning AI. Don't necessarily give what you're told as a given. So So step us into your life for a minute, Jason. So how do you do this? How do you employ all of us? I mean, I think that's I I do exactly that. Frankly, I do exactly that. And building construct agents that allow for that balance where I'm intentionally, you know, kind of creating an adversarial uh prompt model to say, okay, well, whatever this thing's going to tell me, right? First of all, I need to fact check everything. Second of all, I need to say, okay, well, what's the al what would be the alternative that how can I get to the medium where I can try to figure out what's really happening here?

Okay. What have been your inspirations when you've been going down your path? I know you mentioned your wife, your family, but um what have been your inspirations have you started to think, okay, no, we we've got to create friction.

I mean, I think that's it 100%. You know, uh kind of uh being able to imagine a world where, you know, the technology is merging with our biology and becoming more and more transparent inside of everything we do. And so like I felt like this desperate sense in order to uh ensure that we don't get you know smoothed and flattened you know in in into a reality that that that we're not constructed. So for me it's been more of a a call to you know arms if you will to say look no I need to to really focus on uh building friction into this to ensure that what I'm being given like what I'm being provided uh isn't uh an alternate you know reality to you know what I want I'm discerning my outcome to be and then actually using those tools to help to discern that best outcome.

Can you give us an example? Um, yeah. So, I'm I I'm writing a book that that's going to be out and and so I will often uh ask AI to take on the role of another author or an editor that that I'm fond of to give me kind of a response if I finished a chapter, if I if I finish something like this to start those to start those arguments, but not to reinforce that what I'm doing is correct or the belief that it's going to be additive to something that I've constructed, but to give me a contrarian view on the thing that I've produced.

Wow. Okay. So, um, do we have any more questions in the room? So, with that, I think we can give Jason an absolutely huge hand of applause. Thank you so much for taking the time.

Thank you. to speak to us and answer all those questions.