And if your company has no value as a result, that's how the market works.

We should.

I would argue we should do three things.

One, we should actually probably pass policy to to guard against catastrophic outcomes.

This is a role of government.

This is an important role of government.

Don't kill us.

And you're close from evacuating much of southern Europe.

I'm Rex Briggs, an author, marketing researcher, and entrepreneur, and this is Decoding AI for Marketing.

[gentle music] I've spent 16 years on the front lines of artificial intelligence.

I've seen what happens when machines begin to reason and when code starts to surprise its own creators.

I joined OpenAI when there were just a handful of customers and a few million in revenue.

Even then, we knew that if we got this right, it would change the world.

Since then, I've watched AI move from research papers to boardrooms, from prototypes to policies, and from curiosity to necessity.

I've advised Fortune 5000 leaders and governments who all ask the same question in different ways: how do we lead in a world where intelligence is no longer scarce? And after all these years, I've come to believe something simple but powerful.

Yeah

Hmm

HmmBut the policymakers are still ignoring it, in part because Meta's tentacles are wrapped around them, but also in part because it's actually not popular.

It's still not, it's still not a politically popular idea to take phones away from kids, which is crazy.

Hmm.

It's still not a pol- particularly popular, politically popular idea to, to create social media bans for certain age groups or, or device policy limits.

So I think we gotta start there.

The other thing I think we need to acknowledge is everything else that we are talking about right now, future of work, data center job creation, economic spoils, it doesn't actually pl- it doesn't address the root issue, which is the average young person's future of living.

Uh-huh.

Yeah

... z- uh, I, I think, um, my point is the signatories and the support that is now the, that is sweeping through these companies.

But let, let me, let me...

I'll go through the list and then, and then we can talk about it.

The other reason is recursive research is here, and everyone's realizing it's kind of the dog that maybe caught the car.

And it's like, okay, we did it.

Now should we, for the-- Now everyone's stay-- putting on the live hat and going, "Wait a second," their hat and going, "Okay, maybe we should pause for a second.

Uh-

All

right.

So, so this, this brings me to the part of, sorry, that's kind of a loaded question.

That's a totally reasonable question.

It's a question that everyone should be asking.

It's a question that a lot of people are asking.

I have no, I don't take any issue with the question.

Barbara, you're hitting a chord, right?

What's behind these early-stage results, Zach? Is the issue technological, operational, or is it simply that returns are harder to measure on such a nascent technology?

In the avoidance of saying obvious things, I think we should call out a couple problems.

The first is people got so excited about AI that they were willing to do non-economic things that would obviously skew a lot of the return on investments that we would've normally expected.

The second problem is no one knows how this technology works, and it's moving so quickly that the experts aren't in the room.

Everyone is trying to figure this out in real time, so it's a bit inevitable when you have companies willing to spend any amount of money to get ahead and employees who don't actually know how the technology works that you'll have a gross overspending, and we've seen that.

But the third issue, I think, is a principle one, which is that companies don't actually agree, often internally, on what they should build and where they should go.

And when you actually look under the hood, as often as I have, you discover that companies are not actually pointing employees at a North Star anymore.

Can you expand on your argument about AI's potential impact on human progress? And secondly, how do leaders build trust with their internal teams so they see AI as a collaborative catalyst rather than a threat to their job security?

Yeah.

And we observed that most things in our life have actually become exceptionally cheap.

Food, you know, we will eat food that our grandparents had never even heard of.

We will travel to places that our parents couldn't have dreamed of.

And yet, despite all of that deflation across what feels like discretionary spending, the pillars of a great society, housing, healthcare, and education have become more expensive, about 300 to 400% more expensive in the developed world over the last 25 years.

And then the question is actually why? And the answer rests in a policy failure, not a technology one.

And there are a lot of reasons for this that I can go into, and I won't go on my political diatribe right now, but the kids have figured out that they can drive across Los Angeles for $15 in an autonomous vehicle, but a trip five blocks away in an ambulance might actually bankrupt them.

Because I know that whenever I'm sitting around the dinner table with mum and There's a friction there now, right? With how it was versus what I'm dealing with and what Sonia's dealing with and what you're dealing with, Zach.

So what do you think are some of the biggest misconceptions when it comes to AI, especially in a corporate setting?

I think right now people are grossly overestimating the economic detriment of AI and grossly underestimating the emotional one.

So October 1st, 2024, the Longshoremen go on strike.

I don't know if you remember this.

The dock workers of America walk off the eastern seaboard.

And on the morning of October 2nd, the head of the Longshoremen, Harold Daggett, goes on CNN and gives this very long, pretty powerful interview.

And he opens the interview by pointing at the camera.

How old?

How else do you feel like it's gonna change the way that we interact with each other?

Well, screens have already become less necessary to living life.

They've just become more necessary, or they've become more addicting in life.

But so much of my hope actually comes from watching...

So this is, this is a little strange, but watching Gen Z is really hard.

I mean, honestly, like, it's actually, like, heartbreaking to watch a, an entire population that has so much opportunity and feels so broken spiritually, emotionally, and we should never have given kids smartphones.

We should n- most people shouldn't have social media, I, I believe.

Yeah.

Mm.

And it's very hard to arrive at a day other than today, and there's a good reason for that.

Humans do things better little by little, and sometimes a lot by a lot.

Now, we, we, we re- we regress in other ways, and, and you have to acknowledge all these things, but we usually fix those things, and increasingly we're fixing them faster, which is a remarkable thing.

The other reason I think people do this is because they are...

The, the other reason people stand and, and clap is because they are really tired of hating.

I, I, I see a very different...

Mm.

Mm-hmm.

You were-- You could be very confident that in most cases, your son would do the job that you did, and so you could...

We just started co-opting the name of the profession, and then you would pass that profession as an apprenticeship to your child, often your son, and that, that carried forever, and that is no longer true.

Borrowing that is this idea in The Next Renaissance, which I use somewhat tongue in cheek, tongue in cheek as, as, as evident in the title, that we are approaching this sort of profound awakening in, uh, on economic terms, on political terms, on spiritual terms, uh, art and culture, and that much like the first Renaissance, the technology and, and w-we sort of attribute the printing press to be the major catalyst for that moment.

The technology in our case is probably gonna be some combination of electricity and AI, electricity, internet, and AI.

But maybe not even internet, maybe just be the, the com...

the local computer that, that does the most work.

Yeah

That's Fear and Loathing in Las Vegas, uh, is his most famous title, I think.

It's certainly one of them, yeah, yeah, Fear and Loathing in Las, in, in Las Vegas.

Fear and Loathing on the Campaign Trail is, is, you know, anyway, there's, there's a long list.

But um, but he, uh, [laughs] he wrote once, "The worst part about writing a book of meaning is that someone smart will have to read it." And he, for all of his sort of, uh, nihilism, he was quite sensitive and, like, didn't, like, didn't like the idea, like, didn't like critics and didn't like the idea that people...

I mean, most great artists don't.

And I b- became paralyzed when I realized as we were wrapping up the book that people outside of my circle would have to start reading it, and was, a- and, and, like, still to this day, I'm quite nervous for people to like it.

But I also, in the process, didn't consider who would read it.

And so I see, I see the sign, and I see the kids coming out with their uniforms on, uh, but I actually don't know anything about it other than there's that, yeah, this kind of weird connection that I see it all the time.

And so I see, I see the sign, and I see the kids coming out with their uniforms on, uh, but I actually don't know anything about it other than there's that, yeah, this kind of weird connection that I see it all the time.

It is a remarkable...

So it's the largest public school system in the, in the country, I think now she runs.

Now, it's not technically public because it's, it's charter, or it's not defined as public.

And you will...

If you...

The more you learn about Eva and the more you learn about Success Academy, you learn that she's sort of become an enemy to the, to the traditional education state.

[laughs]

[chuckles]

We've been talking about thinking machines since about 1900, and we've been talking about AI, the term artificial intelligence, since 1954, and these concepts have been pretty theoretical.

We didn't really know what it would look like.

We just knew that we would eventually, or thought we could eventually, build machines that were smarter than humans.

And that journey took us on quite an interesting ride that we cover in the book, and honestly, when I wrote up the history of AI in the book, it occurs to me that it's kind of boring to people, but it is important to teach people because I think we will talk about modern AI the way we talk about electricity.

Every child grows up knowing that Benjamin Franklin discovered electricity and how he did it, right? The story of the kite and the key....

is almost lore, and the reason it's lore is that electricity is so important to us.

[laughing]

In your mind, has that been shattered or do we just need to reassess what that moat was? Because it seemed like a lot of that moat was based on capital and scale.

Well, I'll start by saying I think outside of the investment world, I think a lot of people have been waiting for a moment where we started to see the research commoditize.

And certainly, this is one of those moments.

I mean, seeing a Chinese firm produce a GPT-4 equivalent model of any kind was remarkable.

Then to see it actually be so economically efficient is truly astounding.

Calling a paradigm shattered because of one model is pretty complicated.

But I do think it is a reminder to everyone that just because we live in a world today where models require an exceptional amount of compute, an exceptional amount of data, an exceptional amount of energy, does not mean that we will always live in that world.

When we're looking at the development of AI and the idea of the U.S. having dominance or at least a lead when it comes to AI, how significantly has that changed? Do we need to see a government response, a private company response, a partnership response? What would you say?