Today’s labor market feels more volatile than ever, leaving many to wonder if artificial intelligence is the primary culprit behind recent layoffs and hiring freezes. While headlines often point toward a looming "AI apocalypse," the underlying data from the Bureau of Labor Statistics and the New York Fed tells a much more nuanced story.

Larry Port introduces the #WTFISUP Report and provides a deep dive exploring why we are currently in a "low hire, low fire" dynamic and why historical tech disruptions—from the printing press to the ATM—suggest that human-centric roles are more resilient than we think.

We explore the structural realities of the modern workforce, including how "talent hoarding" by big tech and the rising age of the workforce are impacting entry-level opportunities. We visit the academic study of diffusion, which sheds light on how new technologies often take decades to fully materialize. Consequently, societal and organizational constraints may put brakes on job disruption during the AI transition.

Whether you are a software engineer, a recent college graduate, or a professional concerned about automation, understanding these market forces is essential for long-term career planning.

What We Cover

• The "Low Hire, Low Fire" Dynamic: Understanding the stagnation in the current labor market.
• AI vs. Reality: Why data suggests AI likely isn’t the main culprit for youth unemployment—at least not yet.
• Historical Context: How past innovations like the telephone and the automobile faced similar skepticism before becoming essential.
• Talent Hoarding: Why major tech companies over-hired and how those "bench" roles led to recent layoffs.
• The Diffusion of Innovation: Why it takes decades for organizations to actually adapt to and benefit from new technology like AI.
• The Human Element: Why radiologists, translators, and bank tellers have seen job growth despite technological threats.

Connect With Us

• Find Larry Port on LinkedIn
• Subscribe to our Channel on YouTube

Dream job or nightmare?

It's hard to know if a career that looks

great on paper will actually lead you

to the life you want to live. So welcome

to DreamJob Cafe. I'm Larry Port.

I'll be asking different professionals

the questions you won't find anywhere

else. So grab a coffee, settle

in. This is Dream Job Cafe.

Sponsored by Wayspark.co,

where we help people navigate careers

in a crazy world. Hey everybody.

I'm Larry Port,

and this is a new type of episode

for the DreamJob Cafe Podcast.

I don't have a guest today where I'm

interviewing them about what it is that

they do or how to prepare for an interview

or something like that for the job

market. What I have today is

kind of what I like to do,

which is research what's happening with

the labor markets and AI and all this

kind of stuff. And I have a

lot of thoughts about this.

And there's a lot being published

through The Wall Street Journal and the

New York Times and a lot of different

other publications.

So I'm always trying to keep up

to speed with what's being done.

And there's a lot of

academic research coming out.

There's just a lot of economic reports

that come out from the Bureau of Labor

Statistics,

there's think tanks. Everybody kind of

wants to know what's going on with AI in

the labor market. Are we

all going to be laid off?

And there's a lot of people

that think that yes, we are.

But the truth of the matter is that the

data right now suggests that that's not

really what's happening.

And there's a lot to this.

But what I thought I would do is I would

review what's going on in the press

right now and why it may be

counterintuitive to think that, oh,

just because AI is out there, it's not

going to gobble up everybody's jobs.

That said,

I am an optimist and I always like

to look on the bright side of things.

But to me,

the arguments for us not having

all of our jobs consumed by

AI is a strong one.

I do think that there will be winners

and losers in this economy. And I think

that if there's a lot of work that you

do that's especially white collar work

that's very routine, that's an

area that we may have problems.

But I think for the

most part, the offsets,

the gains from new types of

employments are going to be

better than the losses

that we're going to see.

And that's not just my opinion,

that's shared by the

Brookings Institution,

that's shared by the New York Fed,

that's shared by the World Economic

of Work Report. So it's

kind of all over the place,

but let's kind of just dig into it

and I'll go through some of the recent

headlines. All right.

So another new thing we're doing with

the DreamJob Cafe is we're starting a

YouTube channel. So this is going to be

on YouTube if you want to watch there.

And if you want to just listen to it

and take a look at the slide decks,

we're also going to be publishing the

slide so you'll be able to download those

if you go to the show notes. So I'm

calling this new segment, by the way,

the WTF Is Up Report.

So it's the Wayspark WTF Is Up Report.

Wayspark is the company that sponsors

this podcast. It's my company.

So here we go.

So the first article in the

WTF Is Up Report is this one.

This is from the New York Times.

The headline is all scary,

but I think that's just clickbait.

But I would have to say,

and I'll include a link to this article

unlocked in my notes for this episode,

that this is probably the best

article to read that kind of goes

over this uncertainty about what

is actually happening in the job

market. Is it AI or is it

something else? So the headline,

which could change based

on what link you click on,

but the subheadline is

artificial intelligence could

reshape work, but for now,

a low higher,

low fire labor market is the main

impediment for young people seeking

employment. There's no doubt that it's

hard right now for young people to find a

job in the spring of 2026.

But this isn't the first time it's been

hard for young graduates to find work

upon graduation.

This happened to me when I was

graduating school in the early '90s.

Actually, I graduated in the mid '90s,

but the people that were graduating in

the early '90s who really had a hard

time.

This happened after the economic collapse

COVID.

But I think the issue is that

because AI is developing so

rapidly in the backdrop, is

this what's causing everything?

At least that's what

people are concerned about.

So people are seeing two things

happening simultaneously,

a bad job market for entry level work,

and they're saying also

AI transforming work,

and they're kind of putting

those two things together,

but it might not necessarily be the case.

So this is from the article. It says,

although AI may be replacing some

entry level jobs on the margins,

there is little evidence that it is

the main culprit. I'll repeat that.

There's little evidence that it's the

main culprit, at least not yet. Rather,

many economists believe employment

challenges for young people with college

degrees stem more from the low hire,

low fire dynamics in the labor market.

And there's a lot of different

reasons why we're in a low higher,

low fire dynamic.

Part of the reason a lot of software

engineers were laid off was because there

was a lot of talent hoarding.

So there were major talent wars between

the big companies like Facebook and

Microsoft and Amazon and these big

technology companies that needed

as much brain power as they could get.

And a lot of times these people were

kept on the bench. So part of the major

layoffs had to do with getting rid

of all this extra talent, right?

That's one dynamic. So what

else do they point out? Well,

if you look at these trends, it's kind

of like what I was talking about before.

So this is kind of a chart which is

an unemployment rate for all people.

If you see one bad trend

that we're seeing is that

the number of people,

and you can see the gray line is

all the workers and the yellowish

line is people without a degree, and the

orange line are people with a degree.

And normally you see all

workers have a higher

unemployment rate than young people.

That's upside down right now.

Now young people are more

unemployed than all workers.

So that's not good. That

is definitely not good.

This was the case back in COVID as well,

I will say. And if you see

those without a college degree,

you see that big spike that was COVID

where a lot of people didn't have any

work.

And you see a huge uptick

We're not where we were in 2010, 2009,

that was after the economic collapse.

We're not there. In fact, historically,

we're kind of in the middle,

if you were to draw lines to this

graph, right? It is going up,

but where we currently stand

is somewhere in the middle.

So this kind of gives a little bit of

context is that yes, it is a problem.

It's always a problem when not enough

people can find work, to be honest,

but across the entire spectrum of people,

it's not as bad as it has been in

recent history by a wide margin. So

that's one thing to keep in mind.

In terms of why they're slow to ...

Why people aren't getting jobs so

quickly, there's a number of explanations,

but one is,

and this is another reason for maybe Gen

Z people to get mad at the boomers. And

if that's how you feel, listen,

whatever, I don't want to go there.

But part of the reality is that

there's just more older workers in

the workforce. The article goes on to say,

since the 1970s, the share of

older workers in the labor force,

particularly in private

sector white collar jobs,

has grown as life expectancy has

increased and Americans have worked

longer. I mean,

one thing that's also not being mentioned

here is that most people get their

healthcare through their

employers. And when you're older,

you're going to have more healthcare

problems and that insurance becomes more

valuable.

So the whole way that our health

insurance works in this country also

contributes to people like

sticking around their jobs longer,

which impacts youth employment. Anyhow,

this economist Pardue says,

this has created a congestion

in the workplace resulting

in less progression for

mid and early career employees who

would otherwise have moved up the career

ladder.

When more senior workers retired,

basically there's people at the top who

are gumming up all the works without as

much improvement in their ranks, without

as much movement rather in their ranks.

Many businesses found they did not need

to replace as many entry level workers.

And the quote is, "As the

US population has aged,

older workers are continuing to hold

onto their positions." That is showing up

in terms of diminished job

prospects for younger workers.

So that's another explanation.

So there's multiple explanations

for why this is going on.

It's not just that AI is

coming in and wiping out jobs.

So there's kind of an

opinion economist that writes

for The Wall Street Journal.

His name is Greg Ip.

This came out last month and this was

kind of an interesting response to what

happened where Jack Dorsey ...

Jack Dorsey is the guy who started Twitter

and now he has a payments company and

he laid off 4,000 people and he said

he was just being honest. We're going

to have to do this because AI's going to

do it. I'm just the first to the table.

Okay, maybe, maybe not. So

Greg Ip's argument is basically going

into history and looking at these

disruptions. He says, neither

theory, history, nor the latest data.

That's true.

The latest data too suggests recession

driven by AI dislocation is likely.

So what Mr. Ipp says here is that

if such a revolution were upon us,

we should see some sign of it.

We don't, at least not yet. Now,

he also says at least not yet,

which is like what the New

York Times article said.

"The ranks of software developers widely

assumed to be acutely vulnerable to AI

because ClaudeCode can write software

development are up 5% in January.

That's 2026 from a year earlier,

a pace largely consistent

with the past 23 years.

That's according to labor department

data analyzed by James Besson,

executive director of the Technology

and Policy Research Initiative at Boston

University. So heavy hitters,

looking at all this stuff.

That's the good news if you're

feeling like, " Oh, shit,

this situation is hopeless for me. "A

lot of people are looking at this. Heavy,

heavy hitters are looking at

this. What this guy says, Greg Ip,

he says," In reality,

businesses are risk averse and

consumers creatures of habit.

Radiologists were supposed to lose

their jobs to offshoring and then to AI

because a radiologist's job is

to be able to look at a scan,

a digital image and identify things.

And so everybody was always predicting

that these jobs were going to go away

because they could just send the jobs

to India for overnight processing,

but they didn't because patients

and providers like having

humans around to explain

their medical images.

This is another one that's

kind of mind-boggling.

Since Google Translate launched in 2006,

the number of human translator and

interpreter employees in the US has risen

73%,

which is kind of mind-blowing.

So this is like a big

topic of conversation.

You have the people in the AI companies

that are losing their minds that we're

going to create this general intelligence

and it's going to completely screw us

up, but not everybody feels that way.

So this book is written by Reid

Hoffman and Greg Beto. Reed Hoffman,

I don't know who Greg Beto is.

I'm assuming he's a ghostwriter,

but Reid Hoffman is the guy

who started and runs LinkedIn.

And I'm just going to read from the

introduction to his book because I just

started it and that's all the

further I've gotten, by the way,

but it's particularly germane to

this discussion. So he writes this.

"Throughout history,

new technologies have regularly sparked

visions of impending dehumanization

and societal collapse. The

printing press, the power loom,

the power loom is where the Luddite term

came from, the telephone, the camera,

and the automobile all face

significant skepticism,

and sometimes even violent

opposition on their way to becoming

mainstays of modern living. "So as a

case in point, he points this thing out,

and this is kind of an

interesting story. 15th century,

so you're in the 1400 now,

doommongers argue that the printing press

would dramatically destabilize society

by enabling heresy and misinformation

and by undermining the authority of

the clergy and the scholars.

Well, that kind of did happen,

if I'm not mistaken, I do think that the

Protestant Reformation was driven

by the printing press, but anyhow,

let's keep going.

The telephone was characterized as a

device that could display the intimacy of

in- person visits and also make

friends too transparent to one another.

It's really crazy when you

look back on these inventions,

what the concerns were. In the

early decades of the cars ascent,

this one is wild,

critics claimed it was destroying

family life with unmarried men

choosing to save up for model Ts instead

of getting married and having kids

and married men resorting to

divorce to escape the pressures

of consumptions that cars help create.

They talk about stuff that

happened in the 1950s. When

I was a kid growing up,

ATMs were introduced,

automatic telling machines,

everybody thought there's

going to be no bank work.

And what happens is

that we kind of endure.

We like the face-to-face interaction.

So that's one argument is

that just because it's there

doesn't mean we're going

to use it. People still use candles.

People still listen to vinyl records.

There are technologies that have

come in to replace these things,

but we choose to use certain

items for certain things.

And it appears that one of the things

that we're seeing in the workforce so far

is that people still want humans around.

They still want their bank tellers and

they still want their radiologists to be

face-to-face.

So the other thing that I consumed

recently that I thought you might be

interested in was a podcast for those

of you that don't like to read. So

there is a very interesting

series called The Last

Invention, and it's about AI.

And in the last episode, episode 11,

he interviews, the journalist

interviews three AI,

he calls them skeptics. I don't know

that they're necessarily skeptics.

They might just have a different

take than the AI doomers out there.

The first skeptic can skip over that

guy. He has nothing interesting to say.

He just sounds like a kind of

crazed conspiracy theorist.

The second and third ones

are worth listening to,

but I want to highlight the third one.

The second one has kind of

more of a technical argument,

but the third one goes along these lines.

And his whole thing is that AI is going to

roll out,

but it's not going to have the kind

of pivot event that everybody's

anticipating,

which is going to cause kind of

widespread societal collapse.

So he argues that it is

more like everything else,

that it just takes a long time for

things to roll out. And he points to the

electrification of America.

The electrification of America is a big

thing that people talk about when they

talk about how ideas

and technology changes.

Nicholas Carr in the book, The Big Switch,

talks about the electrification

of America and how cloud computing

is likely to follow a similar

trajectory, and he's largely right.

So the electrification of America is one

of these things that people point to,

and it took a long, long time.

It just didn't happen overnight.

And this field of how technology

is transmitted and used

by people, the term is called diffusions.

And there was a seminal work on

this by a guy named Everett Rogers,

and his book is called The

Diffusions of Innovations.

And you're probably familiar with maybe

the technology adoption lifecycle curve

where you had early adopters and you had

late laggards and things like that,

but this field is studied.

And what the author is

saying, and his name is very

long, and I'm going to butcher it,

so I'm not going to say it,

but they say that the speed of diffusion

is inherently limited by the speed at

which not only individuals,

but also organizations and

institutions can adapt to technology.

So it's not just the

fact that AI is invented,

but it's how fast can people communicate

with one another to figure out

how to use it inside of their workplaces

and inside of government institutions

and any other organizations where

people have to work together.

So in the academic paper, the

authors write, "As an example,

Paul A.

David's analysis of electrification

shows that the productivity benefits took

decades to fully materialize."

Electric dynamos were everywhere,

but in the productivity statistics

for nearly 40 years after Edison's

first central generating station.

This was not just technological inertia.

Factory owners found that

electrification did not bring

substantial efficiency gains.

So there's market forces at play as well.

And you're starting to

see this as well too,

where you've started to see a lot

of CEOs say that they're planning on

reducing their workforces,

but then recently they've been saying

that the gains they're seeing from AI are

not all that, at least not yet.

So everything's kind

of like a wait and see,

and it's at least not yet. But if we're

going to look at the current evidence,

and if we're going to

take a look at history,

I think humans have a

lot to root for here.

So my advice to you is

to maybe read about this

stuff, follow the links in the show notes

and make your own informed decision,

but I think we're in good

shape. And with that,

I'll let you go. And thank you for

listening. If you like this show,

please like it or send it to

your friends. And if you can,

please be grateful for something today.

Thanks for listening.

Don't forget to like and subscribe to

DreamJob Cafe on Spotify, Apple Podcasts,

or wherever you listen. And don't

forget to check out Wayspark.co,

where we help people navigate

careers in a crazy world. I