There have been some pretty dark

articles published recently about all

the ways in which AI is about to destroy

the worldwide economy. Now, these

include tales of mass unemployment and

collapsing industries and white collar

workers trying to retrain for skilled

crafts jobs like woodworking and

plumbing. One of these pieces, a World

War IIstyle dispatch from the year 2028,

which was put out by a small financial

services firm named Catrini Research,

spread so widely and scared so many

people that it was blamed for a

temporary dip in the S&P 500. All that's

missing from these tales are the garbage

can fires. So, how seriously should we

take these economics doomsday articles?

Well, if you've been following AI news

recently, this is probably a question

that you've been asking. And today, I

want to try to find some measured

answers. I'm Cal Newport, and this is

the AI reality check.

All right, here's the thing. Coverage of

AI topics moves in waves. You'll have a

certain sort of take or idea that will

become popular and everyone is writing

and talking about it and then sort of

seemingly all at once, all the attention

will move on to a new topic as if the

other one didn't exist. Like back in

2023, for example, um I spent a lot of

time trying to explain to people that a

static feed forward large language model

could not be considered conscious. I had

fierce debates about this and then at

some point the whole conversation just

moved on with no resolution. Late last

year, to give another example, all the

discussion was around super

intelligence. And I found myself having

to argue about how you cannot uh infer

intention

in an anthropomorphized manner from the

auto reggressively produced outputs of a

chatbot. But then we've moved on from

that recently as well. The topic dour in

AI coverage is this idea that we might

not be ready for mass economic

displacement that AI is now poised to

wreak. Now I want to go over quickly a

few examples among many of some of the

articles recently that have been making

this point.

Uh the first article was published

online in February and it's part of the

March print issue of the Atlantic and it

was titled America isn't ready for what

AI will do for jobs. All right. So if

you read this piece, it opens on a

somewhat long history of the Bureau of

Labor Statistics, which is actually

quite interesting the the history of the

BLS. And so you're thinking, okay, maybe

this is going to be a sort of

thought-provoking exploration of job

cycles and technological disruption, but

nope. it uh it gets a little darker. Let

me read from the piece here. But like

all statistical bodies, the BLS has its

limits. It's excellent at revealing what

has happened and only moderately useful

at telling us what's about to. The data

can't foresee recessions or pandemics or

the arrival of a technology that might

do to the workforce what an asteroid did

to the dinosaurs. I'm referring, of

course, to artificial intelligence.

Yikes. Remember, the asteroid that

killed the dinosaurs uh killed off most

of life on Earth. So, we've kind of

raised the stakes pretty high for what's

about to happen with AI. All right. So,

the the article goes on, the author

says, "Tasks that once required skill

judgment and years of training are now

being executed relentlessly

and indifferently by software that

learns as it goes." I don't know what it

means for a language model to be

relentless or indifferent, but I guess

they are. Uh quick fact check. The

language models driving most of the

tools that are talking about here uh

they don't learn as they go. They're

static and trained in static batches. I

guess you could make a case that if

you're looking at like a a terminal

agent like cloud code that it could be

doing updates to a markdown file that it

uses as part of its prompting, but I

don't think that's a great understanding

of how this AI works. It's treat it more

like a human brain. All right. Anyways,

let's keep going here. But anyone

subcontracting task to AI is clever

enough to imagine what might come next.

a day when augmentation crosses into

automation and cognitive obsolescence

compels them to seek work at a food

truck, pet spa, or massage table, at

least until the humanoid robots arrive.

Man, the word might does a lot of work

in this essay. He said before, AI might

be like the asteroid that destroyed 99%

of life on Earth. And here he said, AI

might make us all have to work at pet

spas until the robots come. Um, but

there's evidence for this. So what's the

main argument for why we should be

concerned about this? Let me read from

the article again. In May 2025, Dario

Amade, the CEO of the AI company

Anthropic, said that AI could drive

unemployment up to 10 to 20% in the next

1 to 5 years and quote wipe out half of

all entry-level white collar jobs. End

quote. Jim Farley, the CEO of Ford,

estimated that it would eliminate

literally half of all white collar

workers in a decade. Sam Alman, the CEO

of OpenAI, revealed that quote, "My

little group chat with my tech CEO

friends in quote has a bet about the

inevitable date when a billion-doll

company is staffed by just one person."

I step out of the quote here. Uh, the

Atlantic piece then goes on to mention

layoffs that recently happened at many

companies, including Meta, Amazon,

United Health, etc. All right, back to

the quote. Taken together, these

statements are extraordinary. the owners

of capital warning workers that the ice

beneath them is about to crack while

continuing to stomp on it. All right, we

got to hold on for a second here. I want

to break apart. This is the evidence for

the claim that well, we got two claims.

Either all life on Earth is going to be

wiped out like the dinosaurs or

knowledge workers are going to have to

be a massage therapist. It's worth

taking a little bit closer look uh at

exactly what this evidence is stating.

Um, I want to start with the layoff

piece because we covered this in last

week's episode of the AI reality check

and I've covered it on my newsletter at

calupport.com as well.

We don't, for the most part, these

layoffs have nothing to do with AI

automating jobs or increasing efficiency

to the point that you don't need more

workers. Now, I haven't covered every

one of these companies uh mentioned in

this article, but I did cover the first

two companies mentioned, Amazon and

Meta. I've talked on background to

multiple people within both of those

companies and they're both very clear.

Recent layoffs have nothing to do with

AI making those workers unnecessary.

They have everything to do with

overhiring during the pandemic that's

now being corrected for the bulk of the

layoffs at Meta recently where in the

reality labs which uh Zuckerberg had put

a massive amount of money in over the

last 5 years to try to build uh the

metaverse where we're all going to put

on virtual reality helmets and float

around space stations and play cards.

Remember that? Yeah. It was a bad idea.

So they're firing a lot of those people.

They want to put that money elsewhere.

So, right off the bat, okay, we um this

is vibe reporting 101. You you take a

fact that you have a scenario that's

scary and then you take a fact that

directionally seems aligned with that

scenario, but in reality is not and you

list it next to it to try to ground the

hypothetical into something that's

happening now, which vastly increases

its value to actually cause anxiety or

fear. All right, but what about the

other piece of this argument? the idea

that AI CEOs are making dire

predictions. If the owners of capital

are warning us, then for sure we have to

listen. But wait a second, we could flip

this on its head.

Of course, the CEOs of AI companies are

making dire predictions about how

powerful their tools are going to be

because they are like the Wizard and

Wizard of Oz say don't look behind a

curtain. Don't look behind a curtain.

terrified that people are going to spend

more time asking about their financials,

asking about the fact that in order for

them to keep up with their debt, I'm

talking about the major AI companies,

and not face implosion over the next one

to two years, they need to be the

fastest growing companies in the history

of companies. We're talking about

hundreds and hundreds of billions of

dollars of revenue that needs to be

generated at some point in the next year

or two. And it's unclear how they're

going to do this beyond putting ads on

chat GPT and claude code subscriptions

which they're currently losing money on.

So yes, of course they would rather be

talking about dire predictions of some

future because guess what? That makes

their technology the most important

technology in the world and justifies

investors continuing to put money into

their company. So, I'm not saying that's

definitely what's happening, but I don't

have to stretch to find an alternative

explanation for why Dario Amade or Sam

Alman love to spout out these sort of

big predictions.

It completely serves their purpose. And

I want to say, look, this is it's it's a

good writer. The rest of the art it's a

good article after this like it's well

researched. He talks to a lot of people.

Um, you learn a lot about labor

statistics. You hear from a lot of

experts. But I just want to kind of

point out the core. The beginning of the

article has this uh combination of vibe

reporting and appeal to biased authority

that as we're going to see is sort of a

theme in these economic doomsdays

article. All right, let me talk about

another one. Our second example here uh

this was from last week I think in the

New York Times. It was an op-ed that had

a uh a happy feel-good title. Mass

hysteria, thousands of jobs lost. Just

how bad is it going to get? Oh jeez. All

right. So, the piece opens, you know,

the you don't choose the titles if you

write an op-ed. So, let's put that

aside. Let's look at the piece to see

what it actually argues. The piece opens

with the story of a college graduate

having a hard time finding a job. Let me

read this here. Just a few years ago, an

entry-level role with a bank or an asset

management firm might have been Mr.

griefenburgers for the asking. But the

white collar job market has cooled

sharply. While the unemployment rate

remains relatively low, 4.3% office jobs

are suddenly a lot harder to come by for

recent college graduates and experienced

professionals alike. Now, this is uh

that's a this is an important real

story. Unemployment's pretty good, but

there is a cooling, especially on entry-

level hiring in knowledgework jobs that

has been persistent really for multiple

years now and isn't yet improving.

All right. So, why is this happening?

Well, you can ask economist and there's

there's three reasons they'll give you

in a descending

order of importance. By far the number

one reason, most important reason

explaining this trend is that white

collar industries hired aggressively in

2020 to 2022 as pandemic era digital

growth was super strong.

Um, and there was like these great

resignation fears which led companies to

overcompensate and offer like very

attractive packages. It was like get

people in the door because we're worried

about uh losing workforce.

All right. Now, after that pandemic

period is over, the economy is trying to

correct for this. And we have a lot of

employers not firing people, but they're

going into what's called a no hire, no

fire phase where they say, "Okay, we

need to uh slow down here. We have too

many people. We don't most of us don't

want to do mass layoffs of too many

people because we might need, you know,

they might be useful in the future, but

let's let's uh let's do no hire, no

fire, which is how you get to this

unusual situation where unemployment is

actually pretty good. Um but you also

have low new job growth. All right. The

second secondary cause mentioned by

economists is the higher interest rates.

They started going up in 2022. They try

to offset the inflation caused by co era

stimulus investments that slows down

business expansion, right? That's

economics 101. Um the third cause is

global uncertainty

right with especially in you know the

American context we the tariffs what's

happening in educational and now

educational world. Um, and now we have

global wars. It's an uncertain time. So,

there's a lot of businesses that are

sort of like, let's just wait and see.

We don't need to, we are not sounding

the alarm bells yet. We don't have to,

you know, greatly reduce like we would

into a strong recession, but we're not

going to, let's be careful about hiring

right now as well. All right. So, let's

return now to that Times Opad. I'm sure

it says like this is what explains this.

So, uh, you know, it is what it is.

Hopefully, this will get better. All

right. Let's read what actually they

actually say instead. Many companies

went on hiring sprees of the pandemic

and the slowdown is perhaps just the

inevitable adjustment. All right, so far

so good. Are we going to leave it there?

Nope. Here's what comes next. But it is

happening against the backdrop of the

generative AI revolution and fears that

vast numbers of knowledge workers will

soon be evicted from their cubicles

replaced by machines. This is kind of a

remarkable statement because it's it's

vibe reporting, but it's vibe reporting

that's transparently acknowledging that

it's vibe reporting, right? They're

saying, "Look, there are good

explanations for this, but this other

thing is happening now that makes us

afraid. So, let's just pretend they're

connected. Even though we have other

explanations, it's directionally aligned

with this other fear we have. So, why

don't we just put them together?" What

is the main evidence site in this op-ed

uh for these fears? I'll quote here. The

people that the people selling the

artificial intelligence are among those

sounding the most ominous warnings about

its potential fallout is notable. Uh

some of them are prone to bombastic

claims, but it's hard to see how

spooking the public serves their

interest. It might be wise to take their

predictions at face value and assume

that AI is indeed going to devour a lot

of white collar jobs. Again, this is the

appeal to biased authority. It is not

hard to see why the CEOs of the

companies selling this technology like

stories that makes this the most

powerful important technology of the

last 200 years. Of course, they want

that story out there because without

that story again, it becomes how are you

going to generate $300 billion in

revenue in the next two years. They

don't want that question. So, they've

been spouting these things for the last

5 years. I I don't know why this idea of

like we need to take at face value what

the owners of the technologies

say about what their technology is going

to do. I don't think we should take them

at face value at all. We should be

highly suspicious of them. All right. So

anyways, again this this this article

goes on and it looks at a lot of things.

It's not a bad article but again we have

this sort of vibe reporting mention

stuff that's happening that's

directionally aligned with the fear.

Then you mention the fear and then you

justify the fear by saying, "Look, the

CEOs of these companies are the ones

sounding the alarm. Why would they sound

the alarm if it wasn't real?" All right,

let me get to the third article, which

is the one that spooked the stock

market. And this will be the the sort of

final example I point out here before I

get to some stronger responses. This

article was called the 2028 global

intelligent crisis. Intelligence crisis,

a thought exercise in financial history

from the future. It was published on

Substack by a small financial services

firm called Satrini Research. Now look

right off the bat if you read this

Substack piece. The authors are clear

that this is a they say this is a

thought experiment

and not a prediction.

And you'll hear actually that the

authors have been interviewed a lot in

the aftermath of this article going

viral and spooking people. And they're

really leaning into this. This was just

a thought experiment. I was writing

fanfiction. like why are people taking

this so seriously? But if you read their

same introduction, they then go on to

say hopefully reading this leaves you

more prepared for potential left tail

risk as AI makes the economy

increasingly weird. So clearly they're

saying this is a possibility. This is a

prediction. We're not saying it will

definitely happen, but it's on the table

and we need to be worried about it. So I

don't think they get off the hook by

saying, "Hey, we said this is not a

prediction." But you did say pay

attention to this so you're prepared for

what might come.

I'm not a linguist, but that kind of

sounds like the definition of a

prediction. All right. So, what does

this article actually say? Well, it is

written in the style of World War Z.

That is, it's written like a uh a

dispatch. I think it's a it's like a a

financial report like these companies

write, but from the year 2028,

reflecting on the dire current

circumstances and how the economy got

there. So, it's told in this sort of

fake future retelling style, which is a

very powerful style. Um, let me let me

read a quote here from early in this

sort of fake dispatch from the future.

Two years, that's all it took to get

from contained and sector specific to an

economy that no longer resembles the one

any of us grew up in. This quarter's

macro memo is our attempt to reconstruct

the sequence, a post-mortem on the

precrisis economy. And then it goes on

to lay out this scenario where it starts

like right now and it's like well

there's layoffs happening but we we were

happy about productivity booms and the

stock market goes up until about the

fall of 2026 and then as automation

continues these cyclally reinforcing

negative feedback loops emerge. The

economy crashes the next year in

November 2027 and you know again we're

back to garbage can fires and knowledge

workers having to eat their dogs. All

right, this was a very effective

article. It spread really far for two

reasons. One, that World War Z style of

storytelling where you're you're telling

a story like this is what happened. Let

me look back on it is very emotionally

engaging and it presses fear buttons

much more than sort of straightforward

analysis or prognostication. And two,

there's a vibe reporting trick here that

we've seen in the other two examples.

They peg their fake scenario to

something that's real happening right

now. It began with layoffs in the tech

sector in 2026, which there are

happening right now. Now, of course, as

I've covered in this episode, in the

last episode, and ad nauseium,

the layoffs in tech industry started a

few years ago, it's in response to

overhiring during the pandemic, but

whatever. When you you peg a story that

ends somewhere fantastical and terrible

with something that's happening right

now, your mind puts it on a reality

trajectory and it makes it much more

believable. So, that went viral. It was

uh people said it had to do with a

collapse in the S, not a collapse, a a

minor dip in the S&P 500. Other

commentators have said there's a lot of

factors why there might have been that

temporary collapse in SP500, but it got

a lot of news, especially in the

financial world. All right. So, how

seriously I mean, I talked about some of

the bad reporting techniques in these

articles, but it doesn't mean that

doesn't mean

a priori that they're also wrong. So,

how seriously should we take these

scenarios of economic doom? Well, I got

to say they're they're very

anxietyprovoking.

I I don't like dystopian

fiction, right? Like, I read World War

Z. I really didn't like it. I don't like

watching zombie movies. Dystopian,

especially like collapse of society,

tales and movies. They press a lot of

buttons for me. So, I'm someone who

knows a lot about AI

and uh am a critic of hype. And even for

me, these were distressing. So, I can

only imagine how much distress these

type of articles are causing for the

millions of people that are reading

these in major publications. So, how

seriously should we take them? Let me

tell you what made me feel better and

hopefully it'll make you feel a little

better as well in the wake of the

Satrini article because that spread

through the financial world and it might

have had an actual impact on the stock

market. In the wake of that Catrini

article,

professional economic economists and

global macro strategy analysts, people

who uh their their goal is not

engagement or impacting the

conversation. It's to make money based

on accurate understandings of what's

likely to happen in the economy. They

came out of the woodwork and said, "Hey,

enough.

This is ghost stories and they're not.

We have no reason to believe they're

true." And hearing from these

economists, I have to say, made me feel

a little bit better. I'm going to give

you some quotes and hopefully it'll make

you feel a little better as well. The

New York Times, to their credit, um,

published an article called Bleak

Research Report, Stokes AI debate on

Wall Street. It's written by Financial

Reporter and they actually quoted some

serious economist

who were not that impressed by the

Satrini article. Let me read you two

quotes. Here's one.

The argument leans heavily on narrative

and emotion rather than hard evidence.

Jim Reed, a strategist at Deutsche Bake,

said of the report, "That doesn't mean

it will ultimately be wrong, but he

added that the vibes to substance ratio

is undeniably high." All right, here's

another quote. On Tuesday, Christopher

Waller, a governor on the Fed board,

noted that he had not read the Satrini

report quote deeply in quote, but push

back on the broader idea that AI will

lead to a rapid rise in unemployment as

technology displaces white collar

workers. I don't think that is going to

happen, Mr. Waller said, adding that he

is not a doom and gloomer like that

report was. I think my favorite

response, however,

came from uh Citadel Securities. So, a

global macro strategy analyst for

Citadel Securities named Frank Fle put

out a report in the aftermath of the sup

the catrini article um that had a a sort

of sarcastic title, the 2026 global

intelligence crisis. So the Catrini

report was the 2028 global intelligence

crisis. Say like, hey, everything has

gone wrong in these two years. And so he

called it the 2026 global intelligence

crisis. But here he's referring to the

intelligence crisis being people

believing these types of stories. And so

he does a sort of faux opening. He's

like here I'm make he's doing an

describing our current situation. And it

and that sort of faux opening describing

our current situation uh sort of sticks

in the dagger with the following.

Despite the macroeconomic community

struggling to forecast two-month forward

payroll growth with any reliable

accuracy, the forward path of labor

destruction can apparently be inferred

with significant certainty from a

hypothetical scenario posted on

Substack. He's sort of making fun of

people in the community who were taking

that Substack post with any seriousness.

He then proceeds to kind of educate in a

semi-accessible way the types of things

that global macro financial analysts

look at especially when it comes to

technological disruption and why they

don't see signs of some sort of major

calamity coming and they're not

particularly worried about some sort of

collapse of the economy. I'm going to

read a few of these quotes just to give

you a sense of the type of things

covered in this article.

Number one, we would posit that if AI

represents imminent displacement risk,

the real-time population data would show

an inflection upwards in the daily use

of AI for work. The data seems

unexpectedly stable and presents little

evidence of any imminent displacement.

Right? So again, there's lots of

discussion about this, but they're

looking at the Fed's data out of the St.

Louis Fed, and they say there's no rapid

uptake uh in the way that the news media

would have you um believe in AI use.

Second quote, the current debate around

artificial intelligence conflates the

recursive potential of the technology

with expectations of recursive economic

deployment. Technological diffusion has

historically followed an S-curve. Early

adoption is slow and expensive. Growth

accelerates as cost fall and

complimentary infrastructure develops.

Eventually, saturation sets in and the

marginal adopter is less productive or

less profitable, which causes growth to

accelerate. Um, I'm seeing this argument

from a lot of professional analysts of

technological disruption. They say,

"Man, we always make the exact same

mistake.

You have slow and then you get a period

of speed up." And we say that speed up

will go on forever and let's keep

extrapolating out that curve. And if we

keep extrapolating out that curve,

collapse or singularity or whatever the

thing is that you want to say is going

to happen. But this is never what

happens. It scurves. It goes up and then

it begins other sort of factors

contained to growth. It goes slower than

you think. There's time to adjust. They

say have no reason to believe. Why would

this be different? All right, let me

read another quote here. Displacing

white collar work would require orders

of magnitude more compute intensity than

the current level utilization. If

automation expands rapidly, demand for

compute definitionally rises, pushing up

its marginal cost. If the marginal cost

of compute rises above the marginal cost

of human labor for certain tasks,

substitution will not occur, creating a

natural economic boundary. We don't have

nearly enough compute for these

scenarios. And as they're saying, as you

try to build out compute for more and

more use, it's going to uh drive up the

cost because we're going to have a

mismatch between demand and actual

supply. As the cost comes up, it drives

back down the demand. We are already

actually seeing this with the one sector

where after 5 years of work, we're

finally seeing tools. It's the best case

scenario for AI. We're finally seeing

tools that are really catching the

interest of a sector, and that's in

computer programming. All of the

evidence I can find right now seems to

imply that these companies are selling

the compute for these agents for

computer programming at a significant

loss because they're trying to fight for

market share when they have to actually

go because again they are have huge

debt. When these companies actually have

to try to make more profit off of this

and these costs get adjusted to the

reality of how much expense they're

incurring at the AI companies, you're

going to see like a real moderation

probably and like how much we use for

programming and is it really worth is

worth $2,000 a month for an individual

$5,000 a month? I mean, it's it's going

to be uh interesting and that's just for

this one first use case. So, I think

that's interesting to see as well. They

also say, quote, "Moreover, there's

little evidence of AI disruption in

labor market data as of today. In fact,

the forward-looking components of our

labor market tracking have improved

recently, though huge mismatch between

what the financial analysts are seeing

and what the oped writers are

hypothesizing. The evidence of the

financial analyst is their decades of

experience of trying to understand the

labor market and technological

disruption. the evidence of the article

in oped writers.

Amazon laid off people and Dario Amade

says his technology is the most powerful

thing ever. All right, let me read the

conclusion from this Citadel Securities

piece. For AI to produce a substained

negative demand shock, the economy must

see a material acceleration and

adoption, experience near total labor

substitution, no fiscal response,

negligible investment absorption, and

unconstrained scaling of compute. It is

also worth recalling that over the past

century, successive waves of

technological change have not produced

runaway exponential growth, nor have

they rendered labor obsolete. Instead,

they have been just sufficient to keep

long-term trend growth in advanced

economies near 2%. Today's secular

forces of aging population, climate

change, and deglobalization exert

downward pressure on potential growth

and productivity. Perhaps AI is just

enough to offset these headwinds. So

they're saying, and I think this is

actually pretty optimistic, they're

saying the reality of major major

disruptive technological changes

historically,

has been just enough to offset all sorts

of negative trends and keep at least

some growth happening in the economy.

They say, "Well, we hope for here's what

they're predicting from AI." They're

like, "We have lots of negative growth

forces that we're going to have to

encounter in the next couple of decades

that are going to pull down the economy.

Hopefully, we'll get enough out of AI to

sort of stave those off and still get at

least some economic growth. That is a

very different vision. Like AI is the

latest technological innovation to stave

off DGrowth

is a completely different argument than

no, it's going to that this is the one

technology in history where the S-curve

doesn't happen and it's going to go

exponentially um and it's going to crash

the economy. So, they kind of end on a

positive note there. All right. So,

here's let's step back. First of all, I

want to say the economist make me feel

better.

It doesn't necessarily mean, of course,

they're right and maybe we are going to

have all these factors will come

together, right, to destroy the economy,

but I do like the fact the economists

aren't uh they're not that worried about

it. I think we see this reflected in the

stock market where we're seeing, you

know, again, if serious investors really

believe that the economy was going to

crash in the fall of 2027 and that we're

going to have massive uh decline

starting in October of 2026,

the COVID dip from 2020 is going to look

like a minor correction, right? Like it

would be substantial, but the reactions

are small. like they're actually being

they're they're they're pessimistic on

the frontier AI companies because they

think they're spending too much money.

So they don't buy the AI tech CEO

stories that their technology is going

to automate all work which would make

them the most valuable companies in the

history of companies. The stock market

doesn't buy it. We see more moderate

bets against specific sectors where they

think they're going to have practical

disruption like the SAS uh um sector and

even those are modest. And we're seeing

actually much bigger reaction from

things like the cost of oil going up to

$100 a barrel. That caused way bigger

impacts on the stock market than these

scenarios of the last two months about

the economy collapsing. So to me that

makes me feel better. But it doesn't

mean there's not going to be an impact.

And they could be wrong or maybe the

impact is going to be smaller.

But let's let's put that on the table

now, right? Let's say, okay, maybe the

economy is not going to collapse. so I

don't have to learn how to light a uh

garbage can fire and become a pet

masseuse. But maybe we're going to have

like it's going to be a hard run.

There's going to be economic disruption

and it's going to be like more so than

almost any other technology in the past

and it is going to be disruptive in some

way. Let's say that was the case. If

that is, and it could be true, and I

hope not, but it could be true.

AI doomsday reporting isn't helping.

What I'm seeing is that these sort of AI

doomsday articles where you try to oneup

each other with how uh precient you are

about how bad things are going to get

prevents us from responding

in effective ways. If we instead treat

AI like a normal technology and we

respond with our normal tools when we

see it doing things that we would

normally say this is a problem that we

need to correct. I think we can have

much better progress in containing,

shaping, and directing the AI revolution

than instead falling back to these

massive dystopian World War Z tales.

The fall back on doomsday writing is

letting the AI companies off the hook.

Look at what I covered last week.

Jack Dorsey

uh negligently goes off and makes these

huge acquisitions sort of in an

impulsive fashion throughout the

pandemic of these crypto and blockchain

companies. they don't go well. So he

then impulsively fires half of his

workforce because he can't do anything

injectors. He can't do anything in

measured increments. Everything he does

is drastic, right?

But because he comes out and says, "This

is just the first sign of the AI

economic apocalypse. I for one am

learning how to make trash can fires

because I'm going to not only be a pet

masseuse, but I have to maybe eat the

dogs because there'll be no money left

in the world." Because he leaned in the

doomsday reporting. what was the

coverage of the block layoffs?

Reporters would rather treat it as

evidence of the narrative economic

doomsday. That's what they focused on.

In fact, he cited in uh one of those two

art one of the articles I talked about,

the block layoffs are cited as evidence

of what's coming. The right way to treat

that was like, yeah, sure, and like I'm

sure you have a perpetual motion machine

and you can fly. Back to the point, what

happened to those crypto investments?

Why did you have to lay off that many

people? Who did you lay off? wait a

second, most of these jobs have nothing

to do with AI automatable roles. We

would hold his feet to the fire. Like,

you're being negligent and impulsive.

But instead, we're like, "Oh, yeah.

Thank you, Cassandra, for helping us

understand what's coming."

The same thing has happened with these

AI CEOs. They find like the more the

more dramatic and fearful of a thing to

say, the more the attention turns away

from what's actually happening.

Journalists used to severely distrust

billionaire tech CEOs, but not when it

comes to this issue. We look to them as

like they are guiding us to understand

what's happening with this technology.

They these CEOs have been covering this

have been saying crazy stuff for the

last four years. They keep changing what

it is on mass.

They were all talking about super

intelligence

and the machines getting out of control

and like an alien mind. They're all

talking about that and they all shifted

at some point to to something else and

now they've shifted to like the economy

is going. just follow they they just say

stuff and it's entirely in their favor

because again your technology automates

all jobs. Well, where am I going to put

my money? The only place left to put my

money is in like the three companies

that are going to run all the jobs. So,

I think doomsday reporting prevents us

from actually responding. Prevents us

from saying when Derry is like 50% of

white collar jobs are going to be gone.

I'm like, uh-huh. Uh-huh. um you need to

make $300 billion dollars somehow in the

next four years in order to like save

off like to to get anywhere near

profitability. Uh how are you doing

that? Right? That's the question we

could be asking.

So I I think that we don't need to

ignore AI or its impact on jobs. But we

need to cover it like a normal

technology so we can deploy the type of

normal things we would do when we see

disruption or changes when we see that

as cover for malfeasants or

impulsiveness or whatever is going on.

And so I hope we move past by the time

this comes out we'll probably have moved

on to you know something else. Uh I

don't know what AI and birds are going

to spy on us whatever it is. And I hope

so because I think this AI doomsday

reporting not only is stressing people

like me out, but it's preventing us from

actually respond to real impacts of this

technology in a way that could really

matter. All right, enough of my sermon.

Uh hopefully some of this makes you a

little bit feel a little bit better this

week. Uh we'll be back probably next

week. I'm doing this on Thursdays, maybe

not every Thursday, but if there's

something to talk about, I'll be back

next Thursday. Remember, take AI

seriously, but not everything that's

written about it. See you next time.

Hey, if you like this video, I think

you'll really like this one as well.