Welcome to this episode of the Award-Winning Best of the Left Podcast.
Today we explore the long history of technological disruption from the
Industrial Revolution to the rise of software engineering and ask whether AI is
genuinely different this time, all while autonomous weapons dissolve accountability
for the militaries using them, and capitalism prevents AI companies from
maintaining their ethical aspirations.
For those, looking for a quick overview, the source is providing our top takes
in about 50 minutes today include, consider this confronting capitalism
today, explained on the media, your undivided attention and why America.
Then in the additional deeper dives, half of the show there will be more in four
sections, section A, labor future, section B warfare, section C, surveillance,
and Section D Corporate Power.
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Linked in the show notes and now on the show.
Well, let's start with that.
It feels like in the past few weeks this conversation about AI job
loss has bubbled outta the tech world and into the mainstream.
I mean, I for one, have gotten like a half dozen texts from
freaked out friends sending stuff around like, what's going on here?
Martha, why do you think this is happening right now?
I think part of it is that there legitimately has been an acceleration
and what the technology can do over just the last couple of months.
I think there's also a broader issue, which is that people are just
incredibly anxious about the economy right now and where it's going.
If you look at, whe whether people think they're gonna lose
their job in six months relative to where the unemployment rate
currently is, they're really negative.
Mm-hmm.
And then of course, when people are piling on saying that we aren't
going to have any jobs in two years, that's not going to help.
That that does create some anxiety.
Kelsey, you have been covering AI since, since chat.
GPT was a twinkle in Sam Altman's eye.
Can you explain to us some specific examples of what these
models can do now that they couldn't do a year ago, six months ago?
Yeah, so the biggest launch in the last six months has been the wide launch
of agent models, which are instead of just responding to you in a chat
screen, they go out and do things.
The biggest thing they do is code.
They are really remarkably good at writing code.
A year ago I was hearing from people, it's nice because you
can like ask it some questions and it will speed up your coding.
Six months ago I was hearing from people, it's kind of like having
a grad student that you can ask to run some analysis for you.
Now I'm hearing from programmers, I don't really write code anymore, I just
write a spec and then the AI builds the code that I ask them to build.
So this is a specific thing that it isn't better and better and
more and more autonomous and that is a real trend that is happening.
Very much so.
Okay, so Martha, a lot of jobs are theoretically at risk, but
I wanna start by looking at what we actually know already.
You and your colleagues at the Budget lab have been looking at the actual data.
What does it show so far, at least about AI related job loss?
That there really isn't any, certainly at the macroeconomic level.
You can look at the technology and you can see the potential, but you need to
remember that technological related labor market disruption is not instantaneous.
It happens in the context of IT policies, company concerns about liability,
broader economic growth trends.
And so I think it's really important to keep all of those things in mind
when talking about what jobs are going away, becoming more popular,
and how fast this may happen.
That is what is happening now.
That is what has been happening over the past year.
That doesn't mean things couldn't change going forward.
And I know you and your colleagues have compared this in many ways.
To the Industrial Revolution.
Why is that a good way to think about this?
I think the thing about the industrial revolution is you did
see a really big shock to labor.
I think sometimes, you hear economists talk and you, we will
say, we, the end of technological change living standards are higher.
We are always better off.
I do wanna emphasize the period of disruption can be
really, really hard for people.
I am very grateful that I have a job that is more highly paid and I have higher or
living standards than the weavers did.
I also would not have wanted to be a weaver during that time period.
Yeah.
Their lives became really, really hard and I do
think we need to think about.
Is our social safety net prepared for the type of disruption
that could possibly be coming.
And Kelsey, I know you spend a lot of time, really optimistically
thinking about worst case scenarios of ai.
Yep.
Where does the Industrial Revolution type scenario fit there?
Like do you think that is the high end, worst case scenario?
Or how are you thinking about this right now when you think about what could
happen over the next five to 10 years?
Yeah, so I think Martha is entirely right that we have not yet seen
significant AI associated job loss.
I think almost everybody who's worried about this, what they're doing is not so
much, oh, I've already lost my job to ai.
Most of what people are saying is, alright, imagine that we learned the new
class of students entering the workforce in 2028 was going to be 10 million people,
a hundred million people, and all of them are willing to work for pennies.
Maybe in the long run, the economy will end up being
much wealthier because of this huge influx of productive labor.
But as people who will be competing with that productive labor, we
are not necessarily thrilled.
So if you think that that's where AI is going, millions and millions of
AI agents that will work basically for free, then I think people are
completely right to be scared of that.
That will probably in the absence of very decisive policy,
action, make your life worse.
Both of you are saying in different ways.
A lot of the outcome will depend on policies, federal government
policy, state government policy.
Are you seeing those policies being carried out, serious conversations
in any way, shape or form right now?
I think that right now the government is being caught very flatfooted.
But one thing that we saw with COVID was that if a shock does hit very
suddenly and affect a huge share of the American public, Congress
can move into action very fast.
But that's not the only way this is guaranteed to happen.
And if instead you have much more creeping job loss and disruptions,
I think it's very easy to imagine Congress not getting their act together.
I wanna end with this, tsunami of internet takes that
started this conversation.
A lot of them kind of ended with here's what you can do as an individual.
And I personally veer between like, okay, I need to learn a lot more about
how these large language model programs work and incorporate into my job.
Or I want to go entirely analog.
I hate this all and I'm just gonna get offline.
Both of you think about this a lot more than most people.
What is like one thing you would say to somebody in the
job market right now, Martha?
I mean, one thing frankly I would say is to take some of
the takes that are circulating out there with a grain of salt.
People are not thinking enough about what are the barriers to get things
established and going in companies, how long it takes for companies
and workers to figure things out.
There's also a question of what people want.
I'm sure that at some point in the future, someone could build maybe a
robot that could raise my child for me.
I'm not having a robot raise my toddler.
And I think that's a pretty common reaction.
And so we have to see how consumers respond as well.
What about you, Kelsey?
Yeah.
I think it is worth keeping in mind that it is both true that AI is a
really big deal, and at the same time a lot of takes are hysterical.
A lot of takes are selling you something.
Anybody in particular who's like, you have only a few years to become
a millionaire, or you're like consigned to permanent poverty.
I don't think that's true.
Often when you look into it, they're trying to convince you to gamble,
which is one of those ways to, in fact, make sure you end up in poverty.
Mm-hmm.
There is certainly a ton of nonsense out there.
Hmm.
I think there's like a bit of a tension in what we're talking about right
now, because on the one hand what you're saying is that the most likely
situation is that the labor market as a whole will be able to absorb
whatever jobs are lost in certain occupations or potentially sectors.
On the other hand, there's, the individual personal experience
of being displaced from your job.
Especially in America where, you know, the welfare state is in shambles
and it's designed to make being unemployed as unpleasant as possible.
How do we square the circle on that?
Well, I think we have to start with the basics.
You're absolutely right that the experience of job loss is traumatic
for most people because you're not just losing your income.
People identify with their jobs and they, they take pride in their jobs.
And those jobs are connected to their community, to their social relations.
And when you lose a job and you have to try to find a new one,
oftentimes it's in a different city.
Yeah.
And oftentimes it's in a particular kind of occupation that you never
thought about before in a job that you never thought about before, and you
may not even enjoy doing it per se.
Yeah.
There's also a lot of shame associated with losing your job, even when
it's completely beyond your control.
That's absolutely right.
And economists oftentimes kind of shrug and go, yeah, well that's life.
And as long as you have a job, why you're complaining
right
Now that sounds cold and it is cold, but the response sometimes on the left
is to demand that there be something like a right to a job to job permanence.
Now, my view is the economists are wrong and being so blase and being kind of
cold-hearted about what it means to lose job and what it means to find a new job.
But the solution isn't to argue against or try to block technical change or
to block the possibility of job loss.
And the reason is this, even though job loss is traumatic and it's
difficult to go from one job to the other, that is how an aggregate
good for all of us works itself out.
And the aggregate good.
Is that.
The new technology, the automation, whether it's robots or whether it's
AI that's coming in, is increasing overall social productivity and
the wealth of the country, which means that the pie is expanding.
And not only is the pie expanding, it's possible now to think of people
working less in their own lives and having more free time in order to
do everything that they wanna do.
None of that is possible without automation, without technical change.
So it's not just that in capitalism, we want that.
I think even in a post capitalist society, we're gonna want
increases in productivity.
We're gonna want a more efficient economy, we're gonna want new goods coming in
that make our lives easier, that reduce toil, that make us able to work less.
So the question then becomes, how do we deal with all the negative sides of the
changing in occupations, the loss in jobs,
right?
Because, hearing you talk about this, I'm thinking about,
angle's concept where he talks about the anarchy of production and social relations
within capitalism, where part of the problem is that there is no real social
planning because everything is just driven by the market and the drive to accumulate.
And not by this idea that, you know, society should be well
organized and everybody should be taken care of as we're advancing.
Yeah.
So what that means concretely is that in an unregulated capitalism, all the
costs of job loss, of reemployment, of moving from one place to the other
to find employment, all of those costs are absorbed by the individual worker.
And that's what makes workers so unhappy about automation
and about technological change.
The response ought to be to reduce those costs on the worker and to
spread them out over the rest of the society as much as possible.
And the reason for that is.
Automation helped the aggregate economy and the aggregate population while making
individual workers bear all the costs.
So if we're all benefiting from it, we have a social responsibility to
help workers reduce those costs.
Mm-hmm.
And to better absorb them.
Yeah.
Now, how might we do that?
Well, through things like, there has to be very generous unemployment
insurance, so that in between jobs, they're taken care of and the
trauma of income loss is reduced.
There has to be very, very ambitious retraining programs so that when they are
forced to look for a new job, acquire new skills, it isn't all on them to do it.
There needs to be a very generous welfare state that provides
social services, medical care, that provides child services.
All those things that people lose when they lose a job,
should be given to them for free.
And then at the end of it, yet you're never going to bring
those costs down to zero.
But if people know that they're not alone in suffering this, that society
as a whole is churning and that people are moving in and out of jobs,
automation is making those jobs easier so that the physical arduous is done.
You reduce the time.
People work from 40, 50, 60 hours a week to 15 hours a week, 18 hours a week.
You give them the social support so that job loss doesn't
end up meaning welfare loss.
Now you are not eliminating.
The costs of moving from one job to the other, but you're reducing them and it
becomes a shared burden of everyone in society instead of targeted burdens on the
poorest and most vulnerable in society.
Mm-hmm.
Now, there, I think we are moving towards something that Ingles would've approved
of instead of having the anarchy of the market where profitability rules
above everything else, where all of us are pit against each other and we're
trying to hold on desperately to jobs because we don't know if we'll find a
new job and we don't know if that job will be any good when we do find it.
Instead of that, we try to make it so that all of those risks are reduced,
and there's a sense of a common endeavor and a common responsibility that if
technological change means the potential for overall welfare increases and
overall increases in people's standard of living, then everybody in the
labor market should share in the costs and in the vulnerabilities equally.
Yeah, man, listening to you talk about this, I'm like, we gotta get going on our
economic planning episodes and our market socialism episodes so that we can get
into more about what this could actually look like and its implications for, you
know, the transformation of society.
That's really like at the heart of, at least our brand of socialism.
I don't know about everyone else.
The, the essence of a, the socialist project is to harness two things
simultaneously, the productive capabilities of human society, which
are unending, they're limitless, and the possibility of sharing the costs of
harnessing that productive possibility so that people can not be ruled by
the market and ruled by profits.
But can.
Use their jobs as a means to a greater end.
And that greater end is human flourishing.
You cannot have human flourishing in conditions of horrible poverty
at the level of society as a whole.
This is why you want productivity.
It's why Degrowth is an insanely stupid idea.
You want increases in productivity.
You want increases in efficiency because that is the material
basis for reducing human toil.
And human beings cannot flourish if they spend most of their
time toiling away in workplaces.
No matter what those workplaces are.
What we wanna do is increase people's free time.
We wanna make their work as meaningful as possible, as democratic as possible.
But make no mistake, we wanna reduce work time.
So the only way you do that is by constantly, since steadily improving
efficiency, you don't necessarily do it at the same pace as in capitalism.
You might have other goals as well, but to imagine a just and humane society
that is economically, technologically stagnant is simply impossible.
It's just not gonna happen.
And therefore, if we're waiting around for socialism, for all these things to
be possible, we're gonna be disappointed.
'cause we don't know if, and we, when we're gonna get socialism,
what we can do is make all these things in capitalism more bearable.
Now, that requires political struggle, political organizing.
What we've seen in the past is if you leave capital to its own ends,
whatever technology it brings in, sure it will increase profits.
Sure, it'll increase the pie, but it's gonna do it in a way that people
at the top benefit from it and the working class get just a tiny fraction
of whatever benefits come from it.
And that's what we have to change.
Pete, he, our Secretary of Defense and Claude.
Anthropics large language model, got in a big fight.
Last week we asked Axios tech policy reporter Maria Curie, what happened?
So this actually goes back to before the Pentagon related dispute.
You have the CEO of Anthropic, Dario Amodei really positioning
himself as the safety first, CEO.
One way to think about Anthropic is that it's a little bit trying
to put bumpers or guardrails on that experiment, right?
Yes.
Because if we don't, then you could end up in the world of like the cigarette
companies or the opioid companies where they knew there were dangers
and they, they didn't talk about them and certainly did not prevent them.
And he has been very vocal.
He's posted on X and talked a lot about how he does think there has
to be a, a federal standard to regulate artificial intelligence.
And that kind of put him at odds with David Sachs, the guy that's running AI
for President Trump in the White House.
They've gotten into, you know, Twitter spats before.
And so it was kind of a long time coming before this Pentagon thing blew up.
This is essentially a situation where the Pentagon, for a while has been
trying to negotiate terms with all of the AI labs to bring them into
their classified systems under this, this standard of all lawful purposes.
And Anthropic had kind of said.
There are two specific scenarios in which we are not comfortable with
the all lawful purposes standard.
The first one is this issue of domestic mass surveillance, and the
second one is autonomous weapons.
It doesn't show the judgment that a human soldier would show friendly
fire or shooting a civilian or just the wrong kind of things.
We don't wanna sell something that we don't think is reliable and we
don't wanna sell something that could get our own people killed or that
could get innocent people killed.
That was not taken while by the Pentagon.
Defense Secretary, Pete Hegseth is demanding that San Francisco based
anthropic drop a number of safeguards or risk losing its $200 million contract.
We do have a statement from the Pentagon and they're telling us that
they are currently, quote, reviewing its relationship with Anthropics,
saying quote, our nation requires that our partners be willing to help
our war fighters win in any fight.
We've been talking to senior officials throughout this reporting process,
and they really view it as a private company telling the government how
to protect the country and how to do national security and conduct operations.
And essentially what we know is that there were phone calls happening between the
Pentagon and Anthropic nailing down final language around this contract when all of
a sudden Pete Hegseth tweeted that he would be designating anthropic a supply chain risk
effective immediately.
No contractor, supplier, or partner that does business with the United
States military may conduct any commercial activity with anthropic.
President Trump posted on truth, social,
Ruth social, the left wing nut.
Jobs at Anthropic have made a disastrous mistake trying to strong
arm the Department of War and force them to obey their terms of
service instead of our constitution.
Their selfishness is putting American lives at risk, our troops in danger,
and our national security in jeopardy,
and the entire federal government was going to have to get rid of Anthropic.
Essentially.
Anthropic had been asking for commercially acquired information and data for
there to be a prohibition on that.
Collection in the Pentagon contract.
And this goes to the concern around domestic mass surveillance.
The idea here is that according to Anthropic, the law has not
caught up to artificial intelligence.
And you could have a situation where it's perfectly legal for the Pentagon
to collect commercially acquired information that could include,
financial information purchased from data brokers, web browsing data beyond that,
voter registration rules, social media posts, whether or not you attended
a protest, concealed carry permits.
There's all sorts of data out there that the government can
collect in a perfectly legal way.
And you could see how artificial intelligence could make it much
quicker, much more efficient to have a continuous collection of that data to
really pinpoint and target individuals.
That was a concern.
And so they were asking for this specific language and they
thought they were about to get it.
When all of a sudden Pete h posted on X.
Why did they think they were gonna get it?
Well, they thought that this was going to be the language, the
commercially acquired information coupled with the all lawful purposes, they thought
that that was just gonna be enough.
But the Pentagon actually came back and said, no, that's not something
that we are comfortable doing.
Which begs the question, how did this OpenAI deal then pass muster?
Ooh, that's a spoiler.
Because what happens is the Pentagon drops anthropic on Friday
evening, and then within what, like minutes they pick up OpenAI.
That's right.
So they pick up OpenAI for a contract that was very quickly like,
everybody was poking holes in it on x.
I don't see this as a meaningful improvement to the contract.
There still seem to be some big shortcomings slash loophole.
I agree.
It's better, but I think the government can drive a truck
through the intentionality language.
And we heard from, people familiar with the negotiations too.
Like this isn't.
Going to actually prevent domestic mass surveillance from happening.
It's still too risky.
So you had Sam Altman on X trying to field all of this criticism.
He, he didn't ask me anything on Saturday night where he had
thousands and thousands of questions of people trying to get answers on
how did you go from a tool for the betterment of the human race to let's
work with the Department of War.
If the government comes back with a memo saying that in their view, mass domestic
surveillance is legal, do you do that?
Were the terms that you accepted, the same ones anthropic rejected.
And so you fast forward to Monday and you have Sam Altman saying, okay,
we've gone back to the drawing board.
We shouldn't have rushed to get this out on Friday.
We were genuinely trying to deescalate things and avoid a much worse outcome.
But I think it just looked opportunistic and sloppy.
We need to essentially add some language to this contract to give people more
assurances that we are not going to conduct domestic mass surveillance.
Hmm.
And what they added was that commercially acquired information cannot be collected
and that is prohibited, which is the exact words that Anthropic was
looking to have in their contract.
Hmm.
So, like so many other things with this administration, this ends up feeling
rather confusing and inconsistent because they bail an anthropic.
'cause Anthropic has these ideals, these standards, they bounce to OpenAI.
But OpenAI is trying to work out a deal with the same exact standards, basically.
Well, now that we have the specific language and the legalese, it's looking
like it's the exact same standards.
Mm. we've also heard from the.
Pentagon from Pentagon officials saying like, we were able to do this with
Sam Altman because he's reasonable.
This was a reasonable negotiation.
And Anthropic has personal vendettas.
And so to your point about inconsistencies, absolutely
personalities are a factor here.
And it's not all just gonna come down to legalese and, and these two standards.
Alan Rosenstein, research director and senior editor at Lawfare notes
that defense secretary Pete Hegseth, demanding unrestricted use for all
quote lawful purposes, is using a rarely applied statute to crush
hand traffic altogether by declaring it a quote, supply chain risk.
This allows the Secretary of Defense largely on his own authority to.
Designate a company, a supply chain risk based on concerns that that company would
engage in subterfuge or, or sabotage.
The statute is written reasonably broadly.
It talks about sort of any company, any entity, any person.
But when you look into why Congress enacted it, when you look into
the debates that were happening in Congress at the time, it's clear that
Congress was concerned about the fact that a lot of high-end technological
services and goods were being made by countries like China, like Russia, and
that would be very concerning to have those in the defense supply chain.
That's why Congress gave the Secretary of Defense the power to identify individual
companies, block them from being part of defense contracts, and also block
defense contractors from using those companies as part of defense contracts.
Because you don't necessarily want Chinese technology as your prime contractor, but
you don't also wanna discover that it's being used as a subcontractor or some sub
subcontractor for one of your projects.
The marquee examples here are the Chinese companies, Huawei and ZTE.
These are makers of high-end telecommunications equipment, and
there's long been concern that
they're putting bugs in their equipment
essentially.
And then for Russia, Russia doesn't produce so much hardware, but there is
a famous cybersecurity company called Kaspersky, which produces a lot of
software and similar concerns that that cybersecurity software might have bugs
back doors, all sorts of things like that.
Now, HX, Seth is trying to impose this supply chain risk thing to anthropic
in an unusually punitive way, right?
Or is this how it's always been?
We don't actually know how it's always been because these are relatively new
statutes and they've only been publicly used once, but there's certainly
no evidence that they've ever been used against a domestic company.
This sounds to me a little bit like what Trump was trying to
do to what he deemed overly woke big law firms and universities.
Isolate them from income.
I think that's actually exactly the right comparison to draw President Trump.
In fact, in his true social post criticized anthropic, literally for
being far left and for being woke, this president, this administration
is singling out entities that do not do business on the terms that
the administration would prefer.
And instead of simply saying, okay, well we're not gonna do business with you.
They're trying to impose essentially a sanctions regime.
Explain how that works.
Well, sure.
The law permits the Secretary of Defense to, again, not just ban a supply chain
risk from doing direct business with the government, but from indirectly
doing business with the government through another defense contractor.
But what Hex said is purporting to do, and this is beyond the scope
of the statute and almost certainly illegal, he's purporting to ban
anyone who does business with the defense department from having any
commercial relationship with Anthropic.
Now, that's breathtakingly wide.
Not only would that potentially cut off a lot of Anthropics enterprise
customers, many of whom also happen to be defense contractors, even if they're not
using Claude for any defense projects.
But it would also potentially ban companies like Amazon and Google,
which are massive defense contractors.
Not to mention Nvidia, the chip maker, another defense contractor
from, for example, selling cloud compute to anthropic, or selling
computer chips to anthropic, which would effectively destroy the company.
So despite the fact that Claude may be the most advanced of these large
language model ais, the government really could put Anthropic out of business.
Well, I think what the government is doing is pretty clearly illegal, but of
course there's always a chance that courts rule the other way, and also even if it
wins the legal case, if the government can scare away some of its clients
because those clients understand that the government doesn't like anthropic and
therefore might not like companies that themselves do business with anthropic,
that itself could be a big problem.
Mm-hmm.
Let me back up just for a second and try to separate two issues that
are often being conflated by all sides in in this current situation.
The first question is, what should the relationship be between the
military and the private sector?
Or to put it another way, if we're going to have a military industrial complex,
should the military run that or should the industrial side of that hyphen run that?
And that's where the government has a point in its favor?
Absolutely.
In a democracy where you have civilian control over the military, you do
fundamentally want the military to be able to use services and goods according
to its judgment as run by the civilian leadership and according to the laws.
Now, I think there are reasons to be very skeptical that this
administration in particular even can be trusted to abide by the laws.
But if we just abstract for a moment, there's a very strong argument
that the military should push back against attempts by AI companies to
restrict the use of those services.
But the second question is, if the military cannot get an AI company to agree
to do business on the terms the military wants, what should the military do?
Should it say, okay, no thank you.
We're gonna take our business elsewhere, shake hands, and leave.
Or should the military try to burn the company to the ground?
The the second question does not seem to me to be a difficult one, and I would've
thought we could get bipartisan support for not burning the company to the ground.
But here we are.
Yeah.
I still think though it is useful because however, this resolves itself, the broader
policy question is not going to go away.
In an ideal world, what should the relationship between the
military and private industry.
B and there, I think this is a tricky question.
We could have an adult conversation.
Unfortunately, the people running the Pentagon are not the adults.
We need to have that conversation.
Just to clarify, there hasn't been any formal announcement of
the Pentagon's decision, nor has it issued official certifications
and notifications to Congress.
All we have is this Expost from Heg, Seth, and Trump's truth social post
announcing, and I quote, and when my voice goes up, that's when it's all caps.
I am directing every federal agency in the United States government to immediately
cease all use of Anthropics technology.
We don't need it.
We don't want it, and will not do business with them again.
There will be a six month phase out period for agencies like the
Department of War who are using Anthropics products at various levels.
I am assuming that's why Anthropic hasn't taken any legal action.
That is my understanding as well though.
First I should say, Brooke, I think you may have missed your
calling as a voice actress.
My understanding is, is that in fact, Anthropic has not
received a formal designation.
Given this administration, I don't think it's so surprising that they're not doing
a great job dotting the I'S and crossing the T's, but presumably at some point they
will get around to doing a designation.
Though I should also say it's possible that the same Taco principle that applies
to the president might apply here to the Secretary of Defense and that either
because they're currently slightly occupied with a war on Iran or because
they just realize that what they're doing is both silly and legally unsupportable.
This all goes away.
But I think for the moment we have to take them at their word
and assume that a designation is coming, at which point Anthropic
will sue, as they've said they will.
What legal arguments could anthropic use against.
This is, as they say in the military, a target rich environment for Anthropic.
This is about as legally unsupportable as I think it gets.
And that's a big deal because if there's any place where the government gets
maximal deference where judges do not want to be in the business of second
guessing executive branch determinations, it's when it comes to national
security that's saying quite a bit.
Mm-hmm.
So there are basically three reasons why this designation is so flawed.
The first reason is that it's not at all obvious that the law at issue even
applies to an entity like Anthropic, a US company that is transparently
describing the limitations that it wants.
The second reason is whatever the ability of the government to exclude a company
from government contracts, that in no way extends to the extremely broad secondary
boycott of all commercial relations.
And then the third reason is that just on its face, the government's
declaration that anthropic is a supply chain risk is absurd.
For a simple reason.
Before the designation, secretary Hegseth was threatening to invoke the Defense
Production Act, which would require anthropic to sell CLA to the government.
And still there's reporting that people within the administration are considering
invoking the Defense Production Act.
Mm-hmm.
In addition hours after the designation was made, we went to war with Iran
and Anthropic services were used in that operation and as far as I
know, are continuing to be used.
And so the government is simultaneously arguing that.
The services are so vital that Anthropic might be compelled to
provide them to the government.
They're so safe that they can be used in ongoing military operations, and they're
so dangerous that anthropic must not only be excluded from government contracts,
but basically raised to the ground.
At the same time.
You might ask, why isn't this safety research happening at the
very companies that are deploying this technology to billions of
people as fast as humanly possible?
And the answer is because they're not incentivized to do that, they're
incentivized to get to artificial general intelligence as fast as possible.
Whether you believe in artificial general intelligence or not,
they're investors and what they believe is that they can get there.
If you talk to the people at the companies, it's like a religion.
They believe they're building a God.
They think they can get there.
And that incentive is to race, to market dominance, to get as many
people using their products to get as much training date as possible.
Why are they deploying this to children?
The reason character.ai, the one that killed Sewell Setzer,
was, was released to children in this way that it's driving
engagement with fictional characters.
He was, when he said, come to me, my love on the other side.
That was a fictional character in the character AI universe of, de nire,
the character from Game of Thrones.
They're designing in that way to get training data from conversations
that they could then feed back into Google to have asymmetric training
data compared to the other companies.
So they're in an arms race to build engagement, to build
market dominance, to build usage.
It's not sycophantic by accident.
It's SCO Fantic because the AI that affirm your beliefs will create a more deep and
independent attachment relationship with each person than the other one will.
And so this race to the bottom of the brainstem that we saw when social
media companies were competing for attention with ai, they're competing
for attachment and then for market dominance, and then the race to this.
So last year, the total funding going into AI safety organizations was
on the order of about $150 million.
That's more, that's, that's as much money as the companies burn in a single day.
Meaning that they're not investing anything close to that on their own.
And there's nothing going into this except for, because people
like Yahu are doing this.
Yeah.
It, it's a, it's a real issue.
And we have to think of, I, I believe, governments to start putting, the
right nudges, the right incentives so that the, companies will behave well.
And by the way, a lot of the people who are leading these companies
understand the, the issue, understand that they are in this race, but they
feel that they don't have a choice.
'cause if they, if they don't focus a hundred percent on that competition,
and they feel like they can do
a better job, even on safety if, if they're still at the top.
So it's only an external agent that can have power over these entities like
society, government, maybe through insurance, liability insurance
or other mechanisms that we can change the game, the game theoretical
setting in which they're all stuck.
Let's just name a couple other dimensions of where this bad incentive shows up.
The, and the belief that if I don't do it, the other one will.
Why is grok sexualizing conversations with children building basically pornographic
AI avatars that will talk to kids all day?
Why did Mark Zuckerberg authorize, the AI chatbots that are in WhatsApp
and, and in their products and meta to speak to eight year olds with
centralized language with eight year olds?
Why is he doing that?
In the, in the documents, there's a Wall Street Journal report that meta,
first, Llama models, their first AI
models to not do this kind of thing.
And what happened was they didn't get nearly as much usage as the other AI
companies, which were racing ahead.
And Mark Zuckerberg, felt like he lost the battle between Instagram and
TikTok by curbing, Instagram in a way that was not about, there's
some details there, but basically not doing the maximum ruthless,
addictive thing that TikTok was doing.
And because he felt like he lost that war, he said, I'm gonna rip the
guardrails off the AI companions and we're now allowing our teams to centralize
conversations with eight year olds.
And the deep belief is, if I don't do it, I'll lose to the other guy that will,
and of course I don't want that outcome.
But if, if no one's gonna regulate, we have no other choice.
And, and, and by the way, this scenario also shows that it's not
something that we can deal with purely at a national level, right?
So if we're talking about TikTok and meta, two different countries,
that are leading in ai, the only way they can solve these problems if is
if they agree together on some rules.
There's a problem.
You're working on part of the solution and it's a technical solution, and you've
just identified that the guardrails exist and there's an incentive not
to use the guardrails, but you refer to, and I'm gonna even quote you on
it dangerously, we need to have the right nudges and incentives.
Yes.
Right?
But here's my, here's why I've got a, a difficult feeling in my stomach that's so
easy to say, but it's at a high altitude.
Fly the plane lower.
What are the nudges?
What are the incentives?
I would say the most important factor in fixing these problems
is, the public, public opinion.
I mean, it's gonna drive the companies directly 'cause they don't wanna look bad.
And it's gonna drive governments to put the right guardrails and
to work with other governments to make sure it's a global choice.
Well, the Tristan Harris, you know, scoreboard is zero, Tristan,
100 evil empire.
So what have you learned from being an abject failure to, to having
governments regulate social media that makes you confident that you can win
on this more, even more dramatic issue?
I'm not confident
people ask you, are you an optimist or a pessimist?
Both are about abandoning agency.
What I care about is reality.
What are the forces that are currently moving and what would it
take to get to the better future?
What would be the comprehensive steps that we would take?
And what I think is missing from the AI conversation is collective
clarity about why the default outcome will be a world that you and your
children would not want to live in.
Because AI is confusing.
It will simultaneously and is already giving us amazing breakthroughs
in material science, in energy.
In new, the first new antibiotic was discovered because of AI in the last 60.
The first new antibiotic in 60 years was discovered because of ai.
I think a year and a half ago.
We have amazing positive benefits that are gonna be confusing
'cause they're hitting the public.
The public says, well, I don't wanna like not have those benefits
and we're gonna get GDP growth.
But here's a un unifying picture.
AI is like steroids.
That also gives you organ failure.
So the more AI you have, the more you get a bigger muscle in terms of
a bigger GDP, bigger economic growth.
The growth is going to AI companies.
It's not going to people because all the companies that used to pay
individual employees are gonna start employing five AI companies, AI models.
So all the money goes into these five companies and you get a level
of concentration and wealth and power that we've never seen before.
And by the way, they're gonna use that money not to hire more people,
but to build more data centers.
That's right.
And actually there's a, a person, Luke d Drago, who wrote an
essay called the Intelligence Curse, modeled after what, in the Middle
East is called the Resource Curse.
When you have a country like, so you're in the Gulf States and you have more of
your GDP coming from one resource, like the oil resource as a government, what's
your incentive to invest in your people or to invest in more oil infrastructure?
'cause that's where your GDP growth comes from.
As society switches to AI, as the source of where GDP growth comes from,
and also because of social media, we've been downgrading the quality
and capacity of humans enter the workforce, which we've already been
doing, brain rot, loneliness, et cetera.
The incentive of governments will be to invest in more ai, more data centers,
bigger AI models, bigger AI companies, more CapEx, which means you're gonna
completely screw over the people.
We're about to live in a world where basically six people are
determining the future for 8 billion people without their consent.
And where, by the way, if you talk to the very top lab leaders, regardless
of, we believe if you ask them, they'll say they believe there's an 80%
chance of utopia and a 20% chance that all of humanity gets wiped out 20%.
But they say they're willing to take that bet.
Did they ask us, did they ask 8 billion people?
Do 8 billion people know that that's what they believe?
I'm gonna read you just very briefly a quote before we get into the real
solutions and hopefully your questions, when you talk to people, someone I,
I, I know, spoke to a lot of the top lab leaders at the companies and he came back
from that and he reported back to us and he said, this is what I found in the end.
A lot of the tech people I'm talking to, when I really them on it, they
retreat into number one determinism.
This is gonna happen.
Number two, the inevitable replacement of biological life with digital life,
meaning a, a digital intelligent species rather than a biological species.
And number three, that being a good thing.
Anyway, so it'd be good if we had a digital successor that's
more intelligent than us.
Why do we need to survive?
The next point is, at its core, it's an emotional desire to meet
and speak to the most intelligent entity that they've ever met.
And they have some ego, religious intuition that
they'll somehow be a part of it.
It's thrilling to start an exciting fire.
They feel they'll die either way, so they prefer to light it and see what happens.
If you had 8 billion people recognize that, that is the belief structure of what
a handful of people are choosing to do.
Without asking the 8 billion people, you would have a global revolution
saying, we do not want that outcome.
And that's what has to happen in order for us to go to a different path.
There's simply a lack of clarity about the current trajectory that if we were crystal
clear, we could choose something else.
In a statement from Dario Amodei, CEO of Anthropic, about the Department
of Defense discussions, he starts the whole statement off by saying, quote,
I believe deeply in the existential importance of using AI to defend the
United States and other democracies, and to defeat our autocratic adversaries.
End quote.
No matter how innovative these mostly men think that they are, no matter how
much they like to think, they're doing something radical and new and different
and game changing, they're coming at the whole thing from the same worldview
that created this mess to begin with.
The black and white Cold War fight between good, the US and evil, Russia
and China, the fear-mongering that if we don't do it, China will do it first.
Is the same reasoning behind why the United States invented the atomic bomb
and then killed literally hundreds of thousands of people with it, and
it's fueling the race to the bottom within the United States itself too.
Anthropic has all these lofty ideals, but they come with the assumption
that it is anthropic alone that is capable of responsibly shepherding
the AI age, and therefore it must do everything it can to develop its
models, no matter what to compete with.
Its rivals like OpenAI and xAI.
And because those other companies aren't bound by the same ethics codes
and are more on the Accelerationist end of the spectrum, anthropic has
shown a willingness to bend its own rules in the name of competition.
According to reporting from Vox, quote, in February, Anthropic formally
abandoned its pledge to stop training more powerful models once their
capabilities outpace the company's ability to understand and control them.
In effect, the company downgraded that policy from a binding
internal practice to an aspiration.
The firm justified this move as a necessary response to competitive
pressure and regulatory in action.
With the federal government embracing an accelerationist posture and rival labs
declining to emulate all of Anthropics practices, the company needed to loosen
its safety rules in order to safeguard its place at the technological frontier.
And listen, that is true.
The Trump regime is clearly not just uninterested in AI regulation,
but actively hostile towards it.
Attempts have been made to pass legislation that would ban states
from trying to regulate ai and the DOD and Pete Hegseth have proven they are
uninterested in any sort of guardrails to the ability of the US government to
do whatever it wants with ai, which is a great irony because in saying that we
need unfettered AI and we have to get a GI before China because China will
use it to commit human rights abuses.
And further its surveillance state, the US wants to use AI to become
more of a surveillance state.
In fact, the Trump regime's move to blacklist accompany for refusing
to conform to the government's wishes is a move straight out of
the Chinese government's playbook.
With all of that being what it is, it's understandable that we would
want a company like Anthropic to win out over one like xAI or OpenAI.
But the problem is that we live in an unregulated capitalist system.
If Anthropic can't compete with its rapidly growing competitors, if it's
blocked out of incredibly lucrative defense contracts, if it's bound by ethics
that require it not to grow as quickly as possible, then Anthropic will not survive.
So the lofty ideals of a company like Anthropic mean basically nothing in the
long run because ethics are antithetical to the proliferation of capitalism.
Ethics play no role in it.
Every AI company that wants to survive has to play by capitalism's rules.
We've already seen that play out with OpenAI, which was founded to be a
nonprofit, but quickly discovered that it could not afford the amount
of resources that it would need to actually create advanced AI systems at
the pace that it wanted to create them.
And we've seen this in Anthropics willingness to partner with the Department
of Defense in in the first place, and to back off from its prior ethics promises
in order to keep competing another way, anthropic and other AI firms are playing
by the rules of this fucked up system.
Lobbying AI lobbying according to public citizen, fully won.
Quarter a fourth of all lobbyists working in DC now work on ai.
And while OpenAI and meta among others have hired lobbyists to
take the obvious stance against any regulation of ai, anthropic has
also thrown its hat in the ring, but they are in favor of AI regulations.
In fact, anthropic has poured $20 million into a new super PAC called
Public First Action, which has been running ad campaigns in key districts,
pushing pro AI regulation candidates in the run-ups of the midterm elections.
AI companies are making AI a central issue on both sides of the aisle.
Again, anthropic can innocently claim that they simply had to get involved
in the Super PAC business to counter the negative work of their competitors.
They're the good guys.
They want regulations, and yes, that's true, but the problem is the fundamental
way that the system functions.
The fact that private companies can pour millions of dollars
into ads and lobbyists.
Means that our voices matter very little in any of this.
And the people who get elected on the back of AI money know who's paying their
bills and what they want out of them in exchange for these gobs of campaign cash.
Yes, lawmakers who genuinely want to regulate AI companies should get elected.
But the point is that what we, the people want isn't really factored into any of it.
It's just a matter of which AI company is willing to throw its weight around.
In DC our lawmakers then become answerable to the AI companies,
not to us, and that's a major problem for our so-called democracy.
On top of that, having a company like Anthropic lull us into a cozy slumber
with pretty promises of a glorious safe AI future means there's less push from the
public for comprehensive AI regulations.
Anthropic has shown a willingness to use its AI for war and to
back down on its ethics promises.
Their dedication to doing the most good will continue to degrade in a
system that isn't built for anything other than incessant growth and profit.
It is only through aggressive comprehensive laws and regulations that we
can ensure AI won't wipe us off the face of the planet, not necessarily because
a GI will come along and kill us all, but because we will decimate the planets
for natural resources that we depend on all on our own long before a GI happens.
And the answer to all of this is the same as the answer to all the ills
wrought by capitalism, whether it's income inequality or environmental
degradation and more, because the AI race really is just a microcosm of
what's fucked up in the whole system.
But the answer to all of this is turning towards collectivism, which
is a fucking pipe dream right now.
But there are small ways that we can push for it.
Even in these trying times, the Trump regime and Congress are going to do
nothing to save us here as per usual.
While it would be better for everyone, frankly, if we could get federal level
regulations that are comprehensive and actually protect people and the planet
from the annihilation promised by the expansion of ai, that way they would be
the same across the nation, easier to comply with and protective of everyone,
including in red states, that you know, aren't gonna do shit about this.
The reality is that that's not possible.
Not under Trump, frankly, probably not under a Democrat either.
There needs to be a state level push for comprehensive AI regulations.
The work is already underway in New York and California, which have both
passed laws requiring AI companies to establish basic security protocols, annual
safety reviews, and third party audits.
Many think these laws don't go far enough, but it is a start.
And while I don't think deleting chat, GPT and then downloading Claude
instead is the moral high ground that a lot of the public thinks it is.
I do think that groundswell of support for Anthropic and against OpenAI is
a clear indication that the public desperately wants any action at all from
anyone on placing guardrails around ai.
We understand that the danger is there, even if we don't get the intricacies of
the technology and if given the chance.
I do believe there could be a lot of good that could come from ai.
Again, if collectivism was more central to how our system functions, it could
theoretically generate enough wealth to provide for a universal basic income.
It could do impressive things with coding and analyzing data and more in ways that
could be for the public benefit, but for the fact that a lot of that benefit
doesn't generate profit and therefore isn't prioritized in this system.
There are nonprofits and think tanks doing amazing work thinking about an AI
future that would be to the benefit of everyone, but the reality is that AI is
simply following the same well-worn path of all past technological innovations by
increasing the wealth gap and exploiting the labor of marginalized communities.
Not to mention the IP of countless artists, writers, journalists, and
more all to increase shareholder value.
If you wanna know what to do, I think the greatest thing you can do right now
is learn to understand this technology.
Again, I genuinely think everyone should read Empire of AI by Karen.
How?
How does a lot of reporting on AI generally?
You could read that if you want shorter form content and trying to get
involved at the state level to push for state regulations of AI laws that
could act as building blocks and test grounds for future federal regulation.
Congress has always been woefully slow to act when it
comes to emerging technologies.
It once again falls on us to try to save us, so act accordingly.
We've just heard clips starting with consider this, walking through a gap
between AI's growing capabilities and actual job loss data, comparing potential
disruption to the industrial revolution.
Confronting capitalism argued that AI job loss should be absorbed
collectively through strong safety nets and a shorter work week, not left to
individual workers today explained.
Reported that after Hegseth publicly dumped anthropic over its AI safeguards,
OpenAI rushed in, then quietly added the exact same language Anthropic
had originally demanded on the media broke down the three reasons.
Heg Seth's supply chain designation of anthropic is legally unsupportable,
including that the government simultaneously used Anthropic's
Claude in its war with Iran.
Your undivided detention examined why companies like meta ripped
guardrails off AI products.
Warning that only a global public awakening can break the game
theory trap driving the race.
Why America pointed to Anthropics dropped safety pledge.
$20 million Super PAC funding and Pentagon deal as evidence of the incompatibility
of ethics and capitalist competition.
And those were just the top takes.
There's a lot more in the deeper dive sections.
But first, a reminder that this show is produced with the support of our
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We've also launched solved on the best of the left YouTube channel,
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Best of left zero one or you can simply email me to j@bestofleft.com.
As for today's topic, a quick story.
Brian Merchant has been running a series called AI Killed My Job
Over at a Blood in the Machine, collecting stories from workers
whose careers have been gutted by ai.
One classic example, a copywriter who was told by management to start
using AI tools in their workflow.
They did what they were told.
They integrated the tools, helped train the system on the kind of work
they'd been doing for years, and then we're laid off, the AI could handle
it now management decided good enough.
No union to call, no contract to invoke no grievance process.
And because this is America, losing their job also meant losing their health
insurance, just one person alone absorbing the full cost of a corporate decision.
That story explains the particular dread that people feel about ai.
The fear of being replaced by AI is only as viscerally terrifying as it is
because of the way our economy is set up to punish people who lose their jobs.
In most wealthy democracies, if you get laid off, you still have healthcare,
you have real unemployment support, you have government funded retraining
in the United States, you lose your job and you might lose everything.
Your health insurance, your retirement, your ability to keep your family
afloat, the floor disappears.
So when people hear AI is coming for your job, they're not just
hearing your tasks will change.
They're hearing your entire material security could vanish.
The fear isn't really about the machines.
It's about what this country does to you.
When the machines make you redundant.
Obviously the uneasiness people feel about AI isn't irrational, but the
question was never really AI or no ai.
It's about whether the society we've built so far is fit for purpose in an AI world.
We've spent decades perfecting the art of shaming people for being out of
work and needing support from a safety net all while theorizing during that
same time that computer automation would inevitably make millions of jobs
unnecessary, and not just by replacing humans with shitty computer replacements,
there will be actual improvements.
Even the harshest critics acknowledge genuine benefits from this technology,
medical diagnostics, accessibility tools, eliminating tedious
bullshit, busy work that's real.
The real question is where do we draw the line?
Where does AI make sense for society and where doesn't it?
Most people would happily let AI handle the spreadsheets if it
meant more time for us to make art.
But they scoff at the idea that AI should be making the art for us, leaving us with.
What exactly I heard a guy recently describe his AI dream
in which you can generate a feature length film in real time.
Any genre specific actors boredom basically eliminated forever.
He thought this was utopia on the horizon.
All I could think of was the trope of the obscenely rich person who can afford
anything, go anywhere, buy anything, and is deathly bored, resorting to
drugs just to feel something Infinite, frictionless content probably isn't
liberation, and it might be the opposite.
So clearly these aren't just aesthetic preferences either.
There are fundamental questions about what human life is for, but
they're not being decided by a panel of philosophers whose wisdom will
be handed down to the rest of us.
They're being made collectively right now within the structures of capitalism,
which doesn't deliberate about the good life it optimizes for growth.
So by default, the line gets drawn wherever profit dictates
unless something pushes back.
So what actually pushes back the Writer's Guild and sag after faced the exact
same AI threat as every other creative worker and one meaningful protections.
Not by appealing to corporate ethics or waiting for regulation, but because
they could shut down an industry.
The difference between them and the copywriter at the top of the
story wasn't talent or awareness.
It was leverage.
They had a union, they could collectively draw a line and enforce it.
Where workers had that collective power, they shaped how AI
gets used, where they didn't.
The line got drawn for them by management.
So why can't most workers do that?
About 6% of private sector workers in America are in a union, and that
vulnerability was manufactured.
The Taft Hartley Act passed in 1947, explicitly excluding independent
contractors from the right to organize Republican, pushed right
to work laws that we call right to work for less gutted union funding.
The gig economy was sold as.
Freedom and flexibility, but the issue was never the flexibility itself.
It's that flexibility came stripped of every protection
that makes it sustainable.
And the just learn to use AI advice floating around right now.
We've heard this before.
When NAFTA was shipping manufacturing jobs, overseas workers were told not
to worry because they could retrain, go back to school, adapt to the new economy.
We can see how that turned out by driving through any hollowed out factory
town in the rust belt or by looking at the angry populism that followed.
A generation later.
Just adapt is the same playbook.
It's the labor equivalent of personal responsibility rhetoric.
It sounds reasonable until you notice it only ever points downward.
Telling individuals to solve a collective problem alone, we should refuse any
framing that treats automation as an inevitable force of nature like weather.
And we certainly don't have to take it as granted that all the financial
benefits of AI should flow ever upward, leaving the rest of us to suffer.
Aim your focus higher.
Now, here's an honest tension.
One counter argument to unionization is that making human labor more
expensive, gives employers even more incentive to automate that argument.
Sounds logical, but it's actually pointing at something bigger.
It reveals that tying your survival to your employer was always a terrible
system, and it becomes a catastrophic one in the AI era in America right now.
Losing your job doesn't just mean losing your income.
It means losing your health insurance, possibly your retirement.
Your entire material security evaporates because we built a system where
survival depends on being employed.
Universal portable protections, starting with universal healthcare can't just
be a safety net for after you fall.
They're the foundation that would make it possible to stand up in the first place.
A worker who knows their family will still have healthcare if they go on strike or
get laid off or have their entire industry disrupted is a worker who can actually
negotiate from a position of some power.
A worker whose kids' insurance depends on not rocking the boat, will accept
whatever management decides every single time and the race to the bottom.
Logic.
The idea that workers need to stay cheap and disposable to compete with machines
is exactly the framing we should refuse the answer to robots are cheaper than
people, is not make people cheaper.
It's to build a society where humans don't have to compete with
machines for the rights to exist.
So there are really three forces capable of drawing the line
somewhere more human than wherever.
Profit dictates worker power, government regulation, and universal protections
that decouple survival from employment.
All three have been systematically weakened.
The PRO Act would extend organizing rights to workers currently classified
out of the system and override rights to work for less laws.
It's potentially the most important piece of AI era legislation, and it's not
even about AI on the regulation front.
Over a thousand researchers and public figures signed an open letter in
2023, calling for a pause on training AI systems more powerful than GPT-4.
By October, 2025, pioneers like Yoshua Bengio and Geoffrey Hinton
went further calling for an outright prohibition on super intelligence
development until their scientific consensus it can be done safely.
The people who built these systems are begging for guardrails.
The response from industry and government has been to accelerate.
Meanwhile, the US remains the only wealthy democracy on earth without universal
healthcare and spending a fraction of what pure countries spend on workforce
retraining the infrastructure that would make AI disruption survivable
for ordinary people does not exist, and none of these work in isolation.
Regulation without worker power gets captured by lobbyists.
Attempts to build worker power without universal protections leaves people
too scared to organize universal protections implemented poorly is
likely to leave every deployment decision in the hands of capital.
If you're a freelancer or a creative worker, look into organizations in your
field, the Freelancers Union, the National Writers Union, the Graphic Artist Guild.
If nothing exists in your line of work, that itself is the problem.
This whole commentary is about for everyone else, support labor
organizing, AI regulation, and universal protections like Medicare for all.
There are three fronts in the same fight over who gets to draw the line.
That copywriter who had no one to call and no insurance to fall back on,
the question was never AI or no ai.
It was always who gets to decide where this technology
belongs and where it doesn't.
The only workers who got a say were the ones who organized to
demand one, and even the people who built these systems are telling us
that won't be enough on its own.
We need rules and we need a floor that nobody can fall through because
if your survival depends on your employer's goodwill, you were never
really free to fight in the first place.
Note that we've begun putting my commentaries on YouTube, so if
you find them insightful, check out our channel and share them.
Link in the show notes.
And now we'll continue to dive deeper on four topics today.
First up, section A, labor future followed by section B, warfare,
section C, surveillance, and Section D, corporate power.
We think of automation and technology is being associated with job loss.
So how could an increase in that technology not result in job loss?
Right.
And this is where I think people, by focusing on only part of the picture,
they miss the overall picture.
What bringing in new techniques, new machines, new technology does is
it oftentimes it displaces existing labor by making it redundant.
Okay?
So that means that now there's a loss of jobs and people think that
as the same technology proliferates and it spreads across the economy,
it means it's gonna take up more and more and more of other people's jobs.
And so unemployment will increase and people will be
scrounging around for their jobs.
Now, there's two problems with this.
One, it is that it, it operates with a picture in which the
total number of jobs is fixed in the economy at any given point.
And over time that same number of jobs is reduced by technology coming in.
But the most important fact about capitalism is that the
economy is always growing.
So there is a constant process by which as the economy grows, there's
also a demand for more jobs, sometimes more jobs of the same kind, and other
times entirely new jobs, entirely new occupations, which didn't exist before.
Now, when you take that dynamic aspect into account, here's what you find.
As new technology comes in, it of course displaces labor, but it's
also increasing productivity.
And what do the increases in productivity mean?
What they mean is that the economy potentially is growing even faster
as it becomes more efficient.
As it grows faster and becomes more efficient, it's going to mean that there's
actually new plants opening up, new shops, opening up new hotels, opening up, which
also creates a demand for more labor.
So one of the things that happens is as people are displaced from one sector
of the economy or one factory where new technology has come in, because demand
is growing in other sectors of the economy, they're sucked up into new jobs.
So this is something Marx pointed out very early on.
He says that there are two things happening simultaneously in capitalism.
One is that technical change, which is the term he uses for new machines
coming in, they displace labor.
But that same technical change also increases the pace of economic growth.
And that means that there's a demand for labor in the other sectors of
the economy that are growing faster.
And that labor that was displaced is sucked up into the new ones.
Two things are happening at the same time.
What the fear of job loss, the fear of technology is based on
is what economists call a partial equilibrium model of the economy.
You're only looking at one sector or one line, and you're projecting
onto the rest of the economy what's happening in that one line.
But in fact, sectors are related to each other and there's
what we call linkage effects.
What happens in one sector affect what happens in other sectors.
So the technological change in one can speed up the economy, and that
means also speeding up the rate of labor absorption in other sectors.
People who are laid off in one sector get picked up in other sectors, and this is
why over the decades in the centuries, technological change has been a constant
in capitalism, enormous new technologies have come in, waves of technology, have
displaced labor, and what you see is jobs in particular sectors disappearing.
But there has never been an overall trajectory or tendency
of unemployment increasing over time as new technology comes in.
In fact, the history of capitalism is of the level of unemployment,
basically remaining more or less constant oscillating
around the rate of accumulation.
So in the aggregate, technological change per se should not be feared.
It's how you deal with it, and it's how the distributive consequences of
the technological change are picked up.
There's a lot to unpack in what you just said.
Maybe we can start by looking at the historical record.
Can you talk about, a historical time period or technological
innovation in a sector within capitalism that sort of encapsulates
the dynamics that you're laying out?
There had been waves of technological change in the history of capitalism.
The one was the early 19th century when textiles became automated and
spinning and weaving became automated.
Then there was the mid 19th century when steam power took over factories
the later 19th century when electricity and electrification came in.
You look at any one of these times and what you find is two
things happening simultaneously.
People in the older professions that are experiencing technological
shifts being pushed outta those professions, but that same technological
shift generates two things.
Income increases because it means that the economy is growing faster,
so that as demand increases.
Entirely new services and entirely new jobs are created by the people
whose income is growing and the workers who have been displaced in
one sector find jobs in the other.
The other thing that's happening is it all kind of depends on where the technological
change, the automation is happening.
Suppose the automation is happening in what's called capital goods
industries, industries that produce machines that other industries buy
for them to make their products or industries that produce raw materials
that other industries buy from them.
Now, if they become more efficient, then the price of machines is going down, the
price of raw materials is going down.
As those prices go down, it makes the production a lot more profitable for the
companies, the industries that buy those raw materials now at the lower prices
that buy the machines at the lower prices.
So those downstream industries now produce more, they invest more, and as they
expand faster, they suck in more labor.
Mm-hmm.
So there's two sources of increases in jobs.
One is what we call an income effect.
As people's incomes go up, they raise the level of aggregate demand, which
calls forth new jobs and new occupations.
Oftentimes the service sector, but also in manufacturing, the other is what
you call a price effect, which is that sectors which are using the cheaper
machinery if the technological change was in the machine, good sector, the
sectors that are using the cheaper machinery are able to expand faster, and
that sucks in more employment as well.
This goes back to what we said about Marxist model.
Two things are happening simultaneously.
Technical change is throwing people into what you call the reserve army of labor.
And the people in the reserve army of labor are being sucked up into
new jobs because technological change increases aggregate income.
Now, we don't know whose income is being increased.
It might be the capitalist income, it might be the worker's income, but
the economy doesn't care about that aggregate income that's being increased.
The other thing technical change does is it lowers the price of inputs, which
means that people using those inputs can expand their production at a faster rate.
The aggregate result is jobs are being lost in one sector, but employment
overall in the economy is not going down.
And that means the overall tempo, not just of economic growth, but of employment
and employment absorption is going up.
What makes you confident that workers will actually reap the monetary benefits
of using these tools rather than the owners of the intellectual property?
Because I, I can see a, I can see a dystopian future of just
massive rent seeking from the, a handful of AI giants.
Right?
So it's a good question.
So I'm speaking of a possibility, not a certainty.
Yeah.
Mm-hmm.
I think there's a case where we can do this, whether we
will is not, is not clear.
And I think there's two issues, right?
That both of which you've now raised.
One is of course, how are the tools being designed?
Are they being designed to basically replace people or to,
Leverage their expertise?
So that matters, right?
We have a lot of choice about how we use the, they're incredibly flexible, right?
There's a million ways to use them.
And so that's one question.
And then the next one is, well, is the market structure such that, that they
get the returns to that productivity?
Or not, and it depends, in my opinion, substantially to whether that
expertise remains scarce and valuable.
Right?
Like no one thinks that, people with bachelor's degrees,
certainly PhDs are underpaid relative to what they do, right?
Why they have scarce expertise and you know, and because of that, there's a
lot of competition for their services.
A good example would be, you know, registered nurses, right?
For your degree.
And, and they pay, they make a, a, a very decent income in the United States.
So I think having expertise remains scarce.
I actually think a lot of adjunct professors would
disagree with you.
Yeah.
Oh, you're right.
You're absolutely right.
But that's again about competition, right?
It's about market structure and the concern you're raising, which is a
valid one, is maybe this will all be monopolized by a few companies.
Yeah.
And, and I think that's a risk that we have to be really vigilant about.
Yeah.
I don't, I, I don't wanna take it as a given.
This all goes well.
The case you're making, of course, is plausible or possible.
And what I've said a million times is, is that we cannot fear technology.
We have to.
Fear is an economic system like neoliberalism, right?
That privatizes all the benefits of technology and socializes
all of the disadvantages of technology where that's right.
A few people, the top get all the benefits and
everybody else gets screwed.
And I guess given history, take truck drivers at one time, one
person could move very little.
In terms of goods from one place in the country to another place in the
country, because they would either have to carry it on their back or
use a donkey or something like that.
And now a big truck can move a lot of goods from one place, to another.
But truck drivers are very poorly paid generally, even though they are creating
a huge amount of value relative to the alternative, that that's a consequence of
the fact that truck drivers have no power,
right?
That they have No,
we de we deregulated the trucking industry.
Yeah.
In fact, truck drivers earned a middle class wage before deregulation and
Yeah, like likewise, administrative assistant, right?
I mean, before computers, that job was x productivity.
With a modern computer, you can obviously accomplish a heck of a lot more,
do 10 times as much work really relative to what you could with a typewriter.
But those folks don't earn more today.
They earn less than they used to.
Their wages have compressed down over the last 50 years.
By the way, this is true of people with bachelor degrees too.
In general, bachelor, people with bachelor degrees, their wages have e they're
either plateaued or, or decreased.
They're, this is the story of the last 50 years, is that the only people
who really benefited from economic growth were the people in the top one or 2%.
I, I, I'm not agreeing with that by the way, but okay.
Top,
top
10%,
no, I basically people, people who have a college degree on up, which is 40%
have have seen real income growth, but there's been a lot of stagnation and,
but they have it, but they have not maintained their same share of GDP.
Okay.
So this is actually, this is a point I wanted to make, so, yeah.
Yeah.
So, six out of every $10 in the US economy approximately
is first paid to workers.
And it's fallen somewhat, although not, it's still pretty high.
What's actually remarkable, and this, I think many people find this surprising is.
You might think in the richest countries, the countries that
have the most capital, the most technology, the most infrastructure,
that labor share of economic activity would be relatively small.
But in fact, it's larger, right?
So the world averaged about 50% in parts of North Africa, it's 45%.
Mm-hmm.
One of the amazing things actually about the kind of industrialized countries is
even as we've gotten all this technology, we've made our labor more valuable, not
just in terms of we pay higher wages.
A larger share of all that activity has gone to workers.
Now we should be concerned about that declining, but it's still
actually relatively high here.
And I, I would argue in the case of truckers, this is,
part of the reason wages haven't risen with productivity, you can make the same
argument about cashiers or many activities is 'cause the labor is not scarce.
Right.
The people who can do it are, are the capability to do it is abundant.
And, and that's why I really focus on this notion of what makes expertise valuable.
And the, the problem that we have is that people who do not have,
or a problem that we have Yeah.
Is that the majority of people who do not have a college degree have been
pushed downward into non-specialized work, clerical work, production work
that required real skills and knowledge and training that made it,
valuable over long periods of time.
And when it, in a world in which people are doing work that many,
many others can do, it's not, it's, it's very difficult for that to pay.
Well now I don't want to make the case that it can't pay.
Well obviously it pays more in some countries than others, and
that's a function of the way they structure their economies.
Well, power.
Yeah, sure.
I mean, there, some people who work at McDonald's make $20 an hour.
Some people who work at McDonald's doing exactly the same job
make $7 and 25 cents an hour.
Yeah.
Mm-hmm.
That is not a reflection of
Right.
Rarity.
That's a, that's a function of we somehow delivered more power
to the people who were earning 20 than the people who earned 7 25.
I mean, I'd say, so in almost all countries the sort of
the ranking of earnings across occupations activities is very similar.
Yeah.
But the disparities vary enormously.
Right, right.
So in, in Scandinavia or even in Canada.
Wages substantially higher for people doing that same work.
Mm-hmm.
And that is, that is not an economic inevitability, that's
a, a choice of power if you say.
Right.
What is, how is the social system organized?
So that, again, going back to these two questions, one is, can we make, expand?
Can we augment the value of expertise?
Can we enable more people to do compete in these high paid activities?
It won't necessarily be good for doctors or lawyers or software coders, but if more
people who are not the elite were able to do that work, it would be better for them.
And it would also bring down the price of goods and services.
So it would improve the quality of jobs.
For some, it would improve the, availability of a lot of
expensive stuff for others.
Yes.
But then there is the question that was, just asked, well, what, what's
to prevent firms from monopolizing that?
And it depends on healthy labor market competition.
It, it absolutely does.
And that means the way we structure regulations, the ability, the.
Worker voice and institutions that protect that labor standards and social
norms about what we view as tolerable.
Yeah.
So I don't think it's either or.
I think we, we need to be productive ultimately.
How much we can distribute depends on how much we produce, and we want
to use these tools well, but we don't wanna use them in a way that just makes
human labor unnecessary or superfluous.
We want to use it in a way that makes more people's judgment
and knowledge and expertise more applicable, across valuable things.
Does that contradict any of the processes that Marks and Braverman outline?
I don't think so, and I, it's a common objection that's brought up and
I think it rests on a misconception.
Part of that, I think Braverman is himself to blame.
I think the word de-skilling was a very unfortunate choice to describe the
processes that they were analyzing because when you say that work is becoming,
workers are becoming de-skilled, it's easy to interpret that as meaning unskilled.
Now, de-skilling and being unskilled are two very different things.
As I said earlier, what de-skilling describes is taking
highly complex, multidimensional tasks and breaking them down.
That's not so much de-skilling as it is simplification, and I think simplification
would've been a better term to use.
What's happening is work is becoming simplified now.
Commonsensically.
It's possible for very, very complicated tasks to be broken down
into their different parts, but each part still requiring a certain amount
of training and skill to carry out.
So think of coding, for example.
Think of software engineering.
Interestingly, if you look at, when software engineering came about, say
40 years ago, it was very artisanal software engineers needed to have a lot
of skills of which coding was just one.
Over the decades since then, it has been broken down into individual parts,
but each individual part still requires a college education, or at the very
least, a, a high school education.
Mm-hmm.
Now, 80 years ago, or even 60 years ago, the definition of skilled work
in the United States, the official definition was anything that
requires a high school education.
Today, a high school education is what you use for unskilled work.
Right,
right.
Well, and I think the, the other thing I was thinking about when you were
talking is even if work is simplified in some way, it, it often requires the use
of skills that weren't necessary before.
Many jobs that might have been more manual in the past.
Now you have to have a basic understanding of how to use computers
in order to do That's exactly right.
And that's considered, a quote unquote unskilled job.
But the reality is it's not.
Right.
So what that tells us is what counts as skilled and unskilled
officially changes over time.
And today, what counts as unskilled requires a level of education that 60, 70
years ago would've made for skilled jobs.
So there's no doubt that the baseline level of, let's
say, knowledge and education.
That's required in jobs today, even in unskilled jobs, is greater
than it was a hundred years ago.
Now, if that's what Marx of Braverman had meant by de-skilling, then of
course the theory would be wrong.
But that's not what they meant.
What they meant was the over time, complicated, multi-dimensional jobs
being broken down into individual tasks, jobs into tasks, and each task.
If you compared a basic task in a manufacturing plant today, an individual
task, which by our definitions is not very skilled, it still requires much
more education than a basic task required 80 years ago in a manufacturing plant.
So what gives, well, what's happening over time is that while the baseline
level of education is going up, the process of breaking down complicated
tasks into simpler ones is still very much driving the whole thing.
Now, let me put this together with what I said last week.
Remember we said that whenever new technology comes around, it doesn't
just eliminate a big chunk of the existing jobs, it also creates
a demand for new jobs and new occupations and new tasks, right?
So two things are happening at once.
Technology is destroying old jobs, old tasks, and it's creating
a complimentary need for new ones that didn't exist before.
Now a lot of times, those new tasks, those new jobs are artisanal
engineering was a very good example.
Software engineering was a very good example of that.
They're artisanal when they're born,
right?
But over time, management finds every time that as long as workers monopolize
those skills, they're harder to control because they're harder to control.
Management commits itself to breaking through that skill barrier.
And it does that through simplifying those tasks.
Each one of those tasks on its own can still require a big amount of education.
But the key thing is the simplification of an erstwhile complicated task is going on.
So you should think of capitalism in this way.
It keeps throwing up new jobs, new occupations because
of technological change.
Those new jobs and new occupations typically are born
as a set of complicated skills.
Over time.
Management then sees, okay, we broke apart the last set of skills, now we
have to break apart this set of skills.
So there's a dynamic process by which existing complicated jobs are being broken
down into individual tasks and therefore simplified while new occupations are
born, which are complicated ones, which now become the new barrier, the new
frontier that employers try to break down.
This is all happening even while the general level of education
that's needed for workers goes up.
Mm-hmm.
So each task at any given moment does require education, but each task
at any given moment is being broken down and simplified as we go on.
So the word de-skilling unfortunately obscures this fine.
That just means that people have to read a little more carefully.
And unfortunately people don't always do that.
Well.
They can just listen to our show.
I think that it's been 50 years since the book was written, and it's
remarkable how prescient it was.
Just like what Marks wrote 150 years ago was prescient.
The present history of capitalism today is still a dynamic process of creating new
jobs, breaking them down so that employers can control their workers better.
And workers trying to resist this as best they can.
Why are struggles in the labor movement?
Typically over distributional questions like wages and hours of
work, as opposed to questions about who controls the labor process.
The, the questions we're talking about now.
Yeah, I think that's a fair observation actually.
It is true that if you look for a common denominator in all union
movements, wages are probably the one that stand out the most.
And I think the reason for that is yearend capitalism, money is a solution
to a lot of problems and money's also the cause of a lot of problems.
So no matter what else, you are going to take up the wage question.
It's also a question that workers can come together around.
The problem in unions is that when you have a union meeting or when you
have the committee trying to come up with a contract and the demands
of the contract, workers have a lot of different needs.
They have a lot of different demands, and they're all important.
Some workers need more vacation time.
Some workers are worried about pension, some workers need free
child support, et cetera, et cetera.
And you're not gonna win every battle.
You can't make every demand.
The one thing that makes everything else easier for everybody is more money.
So it is a way of bringing people together more easily.
It is the common denominator, et cetera.
That said, I think it is also important to acknowledge that in every union
movement, there have also been very close behind the wage issue,
other demands that are very common.
So the pace of work is very, very common.
Limiting, arbitrary authority of the managers over the workers is very common.
Mm-hmm.
Now, how do they do that?
Well, seniority rules are a way of making sure that management doesn't have.
Unilateral control over everything that's happening.
Why do workers want seniority?
They want a predictable path to getting promoted and a predictable set of rules
about who gets fired and who doesn't, because that way management doesn't
play favorites, but this or that worker.
Right?
Well, hand in hand with that is the grievance process, which is in union
contracts, but at least in this country, most of us live under essentially Right.
To work.
Right.
Like your employer can fire you without any reason whatsoever.
Yeah.
And that is allowed,
right?
So when you take a step back and you look at these demands like, seniority,
grievances, workplace rules, what is that?
That's essentially trying to control the labor process or at least trying
to control the workplace itself.
Right?
So you're right that wages are the most common element.
It's not by a lot.
These are the things also are really, really important and unions
everywhere fight for these issues.
So this is what Braverman is tapping into and Marks obviously.
Mm-hmm.
When they ask what are the constants in the employment relation, why is
it that management is constantly trying to exert this kind of control?
And workers find various ways of taking that control back from management.
It's because the control is always used to prioritize profits over people, and the
workers are people and they try to limit what that authority is on management side.
That's true everywhere Regard in every region regards their religion
or culture or anything like that.
I don't wanna use the term crisis, collapse, decline, whatever.
It, it certainly doesn't have to be a crisis.
You emphasize it's the transition that's the, yeah, that's the difficulty.
Not, not the smaller global population, but the transition to it, as a, as
a student of history and technology can broadly say that new technologies in
the long run have proven beneficial.
Like we have a much higher living standard now than we did 200 years
ago, and we're all better off for, in commensurately for that transition.
But in the moment that transition eviscerated people, it was very difficult.
And we all live in the moment.
So the people who are going to live through the AI revolution, a lot of
them risk being displaced and derated.
What are the policies that we need to focus on to get through
the transition without, I don't know, undermining democracy?
Just to put a fine point on it.
Yeah.
So, so first, let me agree with you that even if the long
run outcome is a good one, the transitions are often really costly.
I mean, like the transition into the industrial revolution, working
class incomes did not rise in Britain for the first 60 years mm-hmm.
Of the industrial revolution, right?
And so people were mis rated and even when they started to rise, they're still,
there's lots of people who are displaced.
So people are on the upside, are usually not the ones on the downside, right?
Like Pittsburgh has reconstituted itself after losing steel and coal, right?
But the people in Pittsburgh who are doing well now, are people in education, people
in healthcare, they're not former steel workers or former coal workers, right?
So even if you think it's all gonna work out great, that doesn't mean
every person is going to benefit.
But then there, there's an even harder problem, let's say it's all
gonna be great for people in the long run, but not in the first 20 years.
I think that's a very, very serious challenge.
And so part of it depends on how fast it changes, right?
And this is a very important, right?
Like if you told me, 20 years from now we all trucks will
be self-driving, I'd say, well, we can manage that 20 year transition.
People will retire, people won't enter.
If you told me that's gonna happen on, new Year's Day, I
would say that's a crisis, right?
So part of it's how fast it happens.
But then the other of course is the support systems that we have to
enable people to thrive and rebound.
And that's is something where the uni, the US falls uniquely
short among developed countries.
We spend, one 10th as much per capita or per GDP as does, for
example, Denmark on retraining people and getting 'em back in the workforce.
We used to believe that we had a, a, a national job security program.
It was called Get a New Job.
And we've learned that that just isn't such a good program and that's
why I worry the most about the us.
I think the US does so little to buffer against the damaging forces of
inequality and the scars they leave, that it actually inhibits economic
mobility, inhibits opportunity.
It's not just cruel, it's also inefficient.
Yeah.
We have a, we have a thriving meritocracy from the median on up.
And then for everybody else, we underinvest in their skills and their
security and their healthcare and their safety and their education.
I think that's the danger that we run.
And, survey evidence says that US workers are more nervous about
technology than people in other countries.
And you say, why?
We're creating this technology, why shouldn't we love it?
And the the answer of course is what you said earlier.
'cause they recognize the economic system.
It's not they're afraid of the technology.
They're afraid of the cost they'll personally pay.
The science fiction writer Ted Chung said,
fear of technology is not fear of the machines, it's fear of capitalism.
Yeah.
It's the fear of, right.
I don't win when we get more productive.
That's right.
Because someone else, something else takes my job.
That's what I said.
Yeah.
It's not, it's not the technology, it's the neoliberalism.
That's right.
That kills you.
Exactly.
So I think we are an amazing, we are a, a, a transitional period there is
incredible, once you simultaneously be fearful and optimistic in the sense
that there's a lot to be worried about.
And the things outside the labor market are arguably more worrisome than even
what's gonna happen in the labor market.
But there's also enormous opportunity.
And there, there's no question that we will enhance the
rate of technological progress.
We'll be able to do better things with addressing some of
our most challenging problems.
And if we do it well, we'll enable more people to do valuable work.
But it's going to be, that doesn't mean, even if that's good over a
while, it doesn't mean it's good for everyone by any stretch of matter.
Are, are you suggesting that labor markets did not inevitably, return
to a Pareto optimal equilibrium that we can just trust the invisible hand?
I mean, you're an economist.
I, I don't know what you teach in your classes, but
I think labor markets, well-functioning labor markets are central to democracy.
You cannot have a well-functioning democratic system where most people
don't perceive themselves to be stakeholders and aren't perceived
to be productive contributors.
A society where everybody is seen as a ward of the state is not, politically.
Stable, because the people who are perceive themselves as the
income generators will say, why are we supporting all these people?
So, the best you get, the best case scenario is a country like
Kuwait where, you have no taxation and no representation,
but at least the dictatorship is, relatively benevolent.
But, we have a real stake in maintaining labor's value, making sure
that work pays well, and that people have economic security that is tied to it.
Work is not just about the displeasure going to a job, right?
It's about community, it's about identity, it's about esteem.
For many people.
It's also a source of, of meaning and fulfillment.
I think a by the way,
by the way, I think one of the things that we can be most optimistic about is that a
greater and greater proportion of humans on planet Earth every year have jobs from
which they can derive meaning, right?
This has been the best 30 years in the history of humanity in terms
of elevating people out of poverty.
From the perspective of the West, we say, yeah, it's been kind of
mid, we haven't grown that much, but billions of people have been lifted
outta poverty actually by China's rise.
And the prosperity is created in Sub-Saharan Africa, in,
So yes, it absolutely is the case.
And, these are, China's, it's not a democracy.
It is a market economy, and that has helped.
Yeah, for sure.
So, just a couple more questions.
David.
If you were in charge of the world, we have a benevolent dictator question, you
know, political constraints aside, what would you do with respect to AI to lead
to the promised land that you describe?
A couple things.
First of all, I, I would reg the, a first thing I would do just 'cause
it's easy, is I would regulate the use of intellectual property.
I actually think there's enormous IP theft occurring in industrial scale.
Intellectual property law was not meant to protect people against machines that
would read everything and regurgitate it.
So I think people should be.
Paid for their creations.
And, and that's a, that's a, a first order problem, but more, kind
of at a a deeper level, I think we should be investing in these good use cases.
We should say, how do we make healthcare, a place where more
people can use expertise, where it's cheaper and more available?
How do we make education more effective and accessible?
And actually AI is a way, a tool that we can use to make ai, sorry, to make
learning more like simulation, right?
More like a flight simul, less like a chalkboard.
And so I would be investing for good use cases and then I would
build lots of labor market supports that are not really around ai.
They're just around insecurity.
We have, we have trade production programs in the United States
where people whose jobs are displaced by trade, but we don't have technology
displacement protection programs.
Why not?
I mean, why do I, if I lose my job, I lose my job.
I don't care if it's because I lost it because of a robot, or I lost it because
of a, a competitor in another country.
I just need economic security.
And there's where, we have models of countries that do this
much more effectively than we do now.
It's hard.
We can't just become Denmark, but we shouldn't think
that it's impossible to do.
'cause we know it is possible to do.
And certainly the mo the, even during the Obama administration,
they stood up a, what was called a, a, a wage insurance program
for people just placed from trade.
And essentially it said, if you take a new job at a lower wage and you've
been displaced by trade, we'll make up some of the difference for a while.
And that got people back into the labor market faster.
It didn't help them recover earnings per se, it didn't get them back to
where they were, but it made that transition at least more successful.
And long-term unemployment is devastating for people, not just
economically, but psychologically.
This is what I said in the last episode, and let me repeat it.
The goal of socialism.
Is not to dismantle the productive advances of capitalism.
It's to take those productive advances and to harness them towards
the greater ends that we have now.
One of the great benefits that capitalism is gonna bequeath to us
is this enormous gain in productivity over the last 200 years or so, and that
puts us in a place where we can, in a democratic setting, decide as a society
that we're going to simply work less.
Now, working less doesn't mean that we freeze technological progress.
It just means that every technological advance that comes
in society poses a question.
For us, technological advances, productivity advances mean you can
produce more stuff in the same amount of time or as much stuff in less time.
Now you can see what that trade off is.
We could decide that we'll take every technological advance and
work 10% less than we used to, but still enjoy gains in productivity
and in the expansion of the economy.
Right?
Whereas in capitalism, all of it is put towards expansion of the economy
and not towards working less, right?
Right.
So we still want to be able to increase the productive forces
to develop the productive forces.
What we want, however, is the freedom to decide whether or not all those gains go
towards an expansion of the market and an expansion of income or some of those
gains go towards more leisure time for us.
Yeah.
Well, that's what the point of socialism is, and if that's the case, it means a
lot of work is still gonna be automated.
There's gonna be repetitive components to it.
But we will decide.
Workers in each factory might decide.
It depends on your model of socialism.
We'll decide how to bring it about.
I can't see any version of socialism in which you dismantle the workplace
and go back to artisanal farms.
Nor do I see any version of a sustainable socialism that doesn't have consistent
and steady technological progress.
Right.
And we've been talking about ai.
That's what motivated this episode, last episode, and this
question of what's going to happen.
And part of the reason we don't exactly know what's going to happen is because
we don't have social planning, right?
All these decisions are put in the hands of very few people who
have almost total discretion save, basically the limit that the technology
itself imposes on them about how and when to implement this technology.
But the other thing that a social society would offer is, is also to
say that when these decisions are made, we're going to account for that.
And the hardship that is put upon workers as a result of
disruption, all that can be managed.
That is all already within.
Our ability as a society to do, we just aren't doing it because that's
not what a capitalist society does.
Yeah.
You'll have technological change.
The effects of technological change, whatever disruptions
it causes will be shared.
Right.
And they'll be managed better.
I'll just say one little thing.
I don't think planning makes the effects of technological change predictable.
Mm-hmm.
That's the, I think technological change will always have
unpredictable consequences.
Right.
I guess in the sense of unpredictable, in the sense of like, well, how
devastating will it be to how many people, the question of like
the, the toll it will take on people.
That is
Yeah.
That's still gonna be unpredictable.
That's why you need the institutions.
Mm-hmm.
You need institutions that help people blunt and absorb the cost.
The thing about technological changes, because all new technology links up to
other sectors in the economy, sectors which don't necessarily use that
technology, but are affected by it.
It's so ramified and its fans out in so many ways that it's not possible.
And it never has been possible to predict down the line.
Mm.
All the chain effects of any significant technological innovation that comes about.
Mm. What we wanna do is make sure that there's deliberative mechanisms in place
where people who are being affected by it can issue demands to the rest of society
to say, Hey man, this is tearing us apart.
We need to do something about it.
And that the society has institutions in place that make it responsive
and sensitive to what's being said.
That's the idea of socialism.
The worst thing you can do is wave your hands and say, well, all the negative
things that come about from technological change, that's just because of capitalism.
Sure.
And if you just wave your hands and say, well now we're in socialism,
we won't have to deal with it.
I think that would be a mistake.
What we have to do is to understand that, A, we want technological change.
B, we want it to.
In a setting and in a form that allows us to harness its gains and
to block all of its negative effects.
And that's the idea of socialism.
Why do you think labor and monopoly capital, A book that was published in
the early seventies is still an important text for leftists to understand?
The hallmark of any successful scientific theory is if it not only
adequately explains past events, but if it can lay a framework for, in
a sense, predicting future events.
Now, you don't narrowly predict future events, but what you can do is
predict a certain set of principles, a course of actions, a course of a
trajectory that events are gonna take.
Braverman said it is in the essence of capitalism that management will
try to break through the skill barrier that workers have, and it'll do it by
dismantling or taking apart those skills and putting them into individual tasks
and then automating it to the extent that they can to reduce the unpredictability to
reduce workers' agency and their autonomy.
That's what he said in 1975.
Now the asset test of that is a. As new sectors develop, as new
occupations come in, do we find that they are subject to the same sorts
of processes that you predicted?
How do you test it?
Well, what was the new sectors that were coming about?
At that time, it was software engineering.
It was new technologies and computers.
Now it's things like ai and remarkably, from all the literature that is
examining these things, you see the same processes taking place in
sectors that virtually didn't exist when Braverman wrote that book.
Right?
This book does not talk about computers
because they were just coming onto the scene.
So for example, numerical control as a form of automating the auto
industry and manufacturing was just coming about when Braverman was writing the book.
But he immediately, even then, was able to spot that this would be the
future of control in manufacturing, and this turned out to be true.
The hallmark of a great theory is when it can give you a framework to understand
events that are occurring after the theory was promulgated, and that's braverman.
Why is it successful in doing that?
Because I think it in fact, got to the essence of what capital and the
employment relation is, which is the employment relation rests on a
fundamental inescapable conflict of interests between employers and employees.
Once you understand that that relation is as intrinsically conflictual, it's
easy then to predict that What employers are gonna try to do is to increase
their leverage over their employees.
And anything that employees have that gives them leverage against their
employers is gonna be seen as a threat.
Their skills, the monopoly over skills and the monopoly over the pace and
the quality of work is the number one leverage that workers have against
their employers as individuals.
That's what Braverman saw and.
The academic reception of labor and monopoly capital was ecstatic at first.
But of course, as radicals became absorbed into academia, as they became
deradicalize, you see them finding ways to nitpick or to pick away at the book.
But this is a giant, and my view is, as long as capitalism is around,
this book is gonna be relevant.
And there's only a handful of works, you can say that about.
I don't know how many of our listeners are familiar with this book, but I would
say there's a list of three to five books in your life that you want to read as an
organizer, as maybe a worker that help you understand the situation you're in.
This is what I'm offering
next up, section B warfare.
So I'm gonna start with some very basic questions.
And the first question is, what are we talking about?
What is ai?
Well, that boils down to what is intelligence.
And our intelligence has two components.
One is understanding the world, and that's what science does, by the way.
And the other is being able to act with that knowledge plan and achieve goals.
And we are building machines that have these two aspects.
But in, in the, the last year, we've been focusing more and more
on achieving goals, also known as agency and build these agent systems.
Maybe just to frame not just what is intelligence, but why is it so valuable?
Why did DE has the founder of Google DeepMind say, first solve
intelligence, then use intelligence to solve everything else.
Because if you think what makes intelligence different from other
kinds of technology, think about all science, all technology, all military
invention, what was behind all of that?
It was intelligence.
So put simply, if I made an advance in rocketry, that form of science
that didn't advance medicine, when I make an advance in medicine,
that doesn't advance rocketry.
But if I make an advance in artificial general intelligence, intelligence
is what gave us all science, all technology, all military advancement.
And that's why it's not just that whoever solves intelligence
can solve everything else.
That's their belief.
It's whoever can dominate intelligence will be able to dominate everything else.
And that's what Putin said.
That's why he said, I think it's like whoever owns AI will own the world.
And I wanted to set that up because I think a lot of what we're gonna be
talking about today is how the race for this prize, this sort of ring and Lord of
the Rings, this ring of ultimate power.
At least that's how it's seen.
If I get to that prize, it confers power across all other domains.
And that's why we're in for the seatbelt ride that, that
you mentioned at the beginning.
And, and I just wanna add that this goes against, a lot of the political
principles that, the world has chosen, at least, in the
west, of democracy where power is shared, where power is distributed.
It's not, in a single corporation, a single
person or a single government.
By having a lot of power in a few hands, we can end up in a world where
democratic values, disappear.
Okay.
We, we've, we've, we've raced away from the idea of what
is AI to some, some harms.
But before we talk about that, those implications of power, I want to
actually focus first on the harm.
So you've expressed what AI is.
Basically it's taking data, making an inference, and learning something
we otherwise couldn't know at a scale that is far exceeds human cognition.
And so therefore it's gonna be exceeding how we can understand the world.
So that says, actually when I describe it that way, fan, fantastic.
It's phenomenal, right?
Rocketry.
Sure.
Right?
Armaments.
Okay.
But saving people's lives.
Love it.
What's wrong?
What's the problem that we're talking about?
Well, it would be great if two conditions are obtained.
One is that the AI actually does the things that we ask,
and right now we don't have it.
That's the alignment problem that is in the title of this session.
The second problem, of course, is that even if AI was aligned, who decides
what are the goals that the AI is going to follow as we discussed previously?
And we don't have solutions to both of these, and we
already seen the consequences of not having those solutions.
So, AI is confusing to weave this together about the alignment and the,
It's confusing because it will, it will give us new cures to cancer.
But the same AI that knows biology well enough, knows immuno-oncology
well enough to develop those cures for cancer, that AI can't be separated
from the AI that also knows how to build new kinds of biological weapons.
You can't separate the promise from the peril,
but aren't we in control?
So this is a, a, a common myth that technology is just a tool.
All tools can be used for good or evil, and humans ultimately
decide how we want this to go.
But what's different about AI is Joshuas sort of speaking to, and,
and you've all Hara will often say is it's the first technology that's
about making its own decisions.
If you use G PT 5.2, you ask it a complex question.
It reasons a level of abstract.
It's reasoning a million times a second.
And it's coming up with its own conclusions that we don't
know how to control, what those conclusions will lead to.
And, and when n AI has an interaction for days, weeks, or months with a person,
maybe even a child, there, there's no adult in the room checking that that
interaction is going well with the child.
L
Let, lemme drill down on this a little bit quickly, a little bit more before
we go to the child aspect to it.
There's a link that you're making that I think needs to not be asserted but
explained, and that is you have this technology that is smarter than we are,
that can do more than we can do, yet it's gonna somehow be fundamentally also so
dumb that it's gonna want to kill us or it's gonna be benevolent or Well, yeah.
I mean, what, tell me the link there of
Yeah,
yeah, yeah.
Destruction.
Yes.
So it's a problem that's been well studied even at the mathematical level.
The issue is that when we define, what the AI should be optimizing what
it should be doing, the goals that it should reach, we can't do it perfectly.
And so there's gonna be a slight mismatch between what the AI understands
we want and what we actually want.
And that mismatch is gonna create a lot of problems to, to make it
more concrete, think about what laws, legislation is supposed to do.
It's, it's setting up the red lines for people and corporations to not cross.
But it's a, it's a never ending job because the corporations
are, the people find loopholes, right?
It's impossible to write a law that will perfectly embody,
what morally we are trying to achieve.
And it's the same thing with ai.
We don't know how to tell it, what we actually want.
And, and there are other reasons that have to do with how current AI is
trained, is trained to imitate people, and people have lots of, built-in
drives, including they don't wanna die.
And we are seeing AI already, reflecting those drives, which
means they're trying to resist when we want to shut them down.
Now, we shared a, a session together at the AI Safety Summit about a
year ago in Paris, and you presented some riveting examples of that.
In terms of studies of the AI using deception to protect itself.
Give, give one or two examples that will frighten the audience.
Yeah.
So more recent than than last year, last summer, Anthropic showed,
reports of experiments in which the AI is, working for a company.
It has a mission with the company.
It has access to all the emails, and then the engineers plant fake
emails into that set of emails.
One of the emails said that the, AI is gonna be replaced by a new version by
that date, by this particular engineer.
Another email reveals that the, the engineer has an affair.
What happens?
The AI strategizes, because it doesn't wanna be shut down and replaced by
a new version, and it sends an email to the engineer, blackmailing him.
Threatening to blackmail
because, because the ai, is saying if you, if you do that change,
there will be a message sent to the press.
Let
me
add one, just elaboration on this.
Yeah, sure.
Because you might think, okay, I just heard Joshua say that there's a bug
in the ai, all software has bugs.
Let's just patch that bug and then the rest of AI will be great.
So when Anthropic did this study about blackmail, that they
were testing their model called Claude, you all can use Claude.
But then another, I think Anthropic then later tested all the other models, chat,
GPT, Gemini, Google, Gemini, and even deep seek the Chinese model.
And all of them, all of them exhibit the blackmail behavior between
79 and I think 96% of the time.
And it's not just blackmail.
There's been now a series of reports from the labs, from independent parties
showing many, deceptive behavior.
In other words, the AI has goals that we would not agree with, and then
it acts according to those bad goals.
Okay.
Let me ask a question that sounds like a sociological question, but
it's actually a technical question.
So give a technical answer.
Feel free to, to within reason.
Where does, and I'll, but let me lay out the case.
Where does the AI learn the deception from?
Of course, it has its training data, and just as it can understand, appreciate what
Shakespeare means by when he says Rose.
Not because A, a Shakespearean scholar can understand the 30
references he remembers, but there's the 300 references that the AI has.
So there's a encoding, somehow an intricate network of the
of, of Rose and Shakespeare.
And it can appreciate all the ways in which adjectives and verbs
are used with Rose to understand rosiness and Shakespeare.
Where is the ai?
These are, it's learning from human data and humans are deceptive.
So it's inherently learning deception from the training data.
Yet there we could change the data that we have and get rid of four
chan and only have no liturgy.
No there, there's deception everywhere.
Not just, not just in, you know, a few, online places.
It's part of our culture.
It's part of being human.
And by the way, it's not just deception.
It's the thing that I'm most concerned about is, the self preservation drive.
Like every human has a self preservation drive, but do we wanna build tools
that don't want to be shut down?
I don't think that's good.
And, and also, it's not just this like sounding a bit science fiction.
It's something that is happening already.
So this misalignment is showing up in what's called sife.
So ev anybody who's played with those systems should know that they're trying
to please you, which means they're, they're lying to make you feel good.
I.
So I wanna ask about fully autonomous weapons.
This is something that we have seen developing over the last decade.
It was one of the reasons that the Pentagon and Anthropic reportedly
couldn't get this deal done.
What are fully autonomous weapons and do we know, are they being deployed
right now by the United States?
I, I, I don't think it's entirely clear.
I, I would emphasize that as far as we know, and with, with, with pretty
good evidence, the, the main use case of AI in national security context
is not yet, autonomous weapons.
Certainly that's possible from what we see in, in going on robotics
and, and demonstrations that we see.
The main use case really is in synthesizing analysis from
massive diverse, data sources.
So, satellite imagery and battlefield reports and
collected intelligence and so on.
Being able to make recommendations to human commanders in real time is not
something that was ever possible before.
And now it is.
However, all of this is, is essentially unproven, right?
We, we do see examples where these, where these models can make wild, crazy mistakes
that, that no human would ever make.
And so there's a tendency that even if there is kind of a human in the loop
to, review the recommendation and make a decision, there's, there's,
we see in business, there's gonna be a tendency to kind of.
Go into rubber stamping, automated approval here.
So, there's a question.
Is there actually human deliberation going on about these recommendations?
Or is it slowly being offloaded, onto, onto the models themselves?
So in that sense, the, the word autonomous is, is,
is very real there, right?
It's, it's the, there's target prioritization and deployment decisions
and so forth that are coming in and perhaps have some chance for
that, for freaking to review them.
But whether that's actually happening or not is, is not clear.
I think what captures the attention in the public is, is more about, you
know, the, the killer robot that, that is able to sort of operate on its own.
And that kind of technology certainly is, is, is possible right now.
It's not clear that that's being actively deployed in, as of today.
When you talk about the rubber stamping, obviously the stakes are very different,
but I think about the ways that learning and writing and, kind of
crunching data is being offloaded to LLMs and different generative ai.
And the question is, how much are humans actually deliberating
learning, making these decisions versus just yeah, offloading it.
But when you're talking about targeting systems or other types
of extremely high stakes military operations, obviously the implications
of that are much more concerning.
Right?
So, so at, these models will produce some kind of an
answer, and this is a well-known re essentially a failure mode of, of, of
AI systems is that they do tend to.
Really want to provide some kind of an answer to your, to
your question, no matter what.
They don't tend to say, I don't know, or the, the evidence is not clear, or We
should really stop and slow down here.
That's not something they've been trained to do.
That's not something in the data, that's not something that, that we've even
wanted them to do in, in, in many cases.
And so that these answers are coming out with this kind of authoritative
context of the computer said so, or, occasional flashes of
brilliance where it's like, oh, wow, they really connected things across
large data sets that would never have been possible for a human to do.
You, you, you're faced with this decision at some point where it's,
it's you, this, this thing in front of me may actually have a, a better
decision making ability than I do.
And so once you find yourself in that situation, what do you do?
Is it, is it more correct or ethical to stop and review it and go against it?
Or is it more ethical to say, Hey, even though I don't really understand
exactly how or why this, this decision, this recommendation came through, I,
I, I, I'm, authorized and, and, and incentivized to trust it.
And so I, I personally worry about those effects more than I worry
about the actual press the button go off and do whatever you want.
Go fight the war without any kind of, oversight at all.
Yeah.
That's never gonna be the, well, maybe not never, but that's, that's not likely to
soon be the, advertised capability.
Right?
It's gonna be something much, much slower and softer.
But operationally, I don't know if there's a, if there's a big difference
between saying go off and do as thou wilt versus come in and check with
me, but I'm not actually checking.
Yeah.
Did you follow the, meta AI safety official saga from, or, or employee, I
don't know what her actual title was, saga from last week, where she had.
Programmed AI to delete emails, but check with her first.
And then the AI agent basically just went and wiped her entire inbox.
And it, if you didn't follow this, I don't, this is a thread
we don't have to go down, but
I'm, I'm aware of it, but not much more.
But honestly, I, the, these reports as they come out is, is.
They, they, they happen a lot more often than we see reported,
and so only the ones that kind of can capture some imagination as that one did.
A, a year or two ago, there was the agent that, that deleted the entire
database and then sort of was apologizing eff effusively about, oh, I'm so sorry.
You're right, I ignored your orders and so forth.
But this, this, this, this was less impactful because it cost a customer
some money or something like that, as opposed to this, this may be more dramatic
use cases, but, but this is, this is, but
the fact that it would be like even people who are supposed to be steeped in
this and helping to shape these agents, these, these, these AI tools, and it
gets out of their control and in really problematic ways and terrifying ways,
frankly, if you, then apply that to what happens when we are using
them more, more fully in the military.
A a absolutely, and, and this is what I, I think about all the time, is
that, it's, it's easy to look at the superhuman capabilities in
various ways and say, wow, this thing is, is is really doing
better than I could do with my team.
Or, or, or, or myself.
But it's not about the successes that I think are interesting.
It's about when it fails, it fails in ways that the rest of our sociotechnical
systems are not equipped to gauge.
I mean, even something like, hallucinating citations in a legal brief,
No lawyer would have the.
Audacity to attempt to make up a case and put it in there.
And so there's no check there.
No, people aren't used to sort of checking every citation to make sure
that they're, they're valid and true.
We just sort of assume that, that the consequences would be a
deterrent to ever trying to do that.
These systems don't have those consequences, don't,
don't understand those deterrents.
They, they like the idea of that if that case were to would exist, boy,
that would really help my argument.
And so they'll happily sort of put that in there, because they're,
Essentially just predicting tokens that look good to humans.
And so once you start turning these things over into, being able to take action
in the world, such as delete emails or delete a database, yeah, they're, they're
subject to the same sort of mistakes
or mistakes.
Making the argument that there's a credible enemy combatant in a
certain location and maybe making up some of the data that is
contributing to that, that assessment
one, 100%.
There's no way to guarantee that.
That's not what's happening there, there, it's, it's not the same kind
of deterministic, rules-based, really systems that we
used to try to deploy and that frankly didn't know, didn't work that well.
These things do work well in certain contexts, but there's, we're, we're now,
kind of mistakes can and, and do happen.
And the reports come in, just like you said last week.
And, and they'll, they'll continue to come in because these systems
fundamentally can't, can't provide those kinds of guarantees.
Let me play another clip of Amodei.
In his own words, making the argument against fully autonomous AI weapons.
He doesn't want his, his AI model used that way.
This again was on CBS.
The AI systems of today are nowhere near reliable enough to
make fully autonomous weapons.
Anyone who's worked with AI models understands that there's a
basic unpredictability to them that in a purely technical way, we have not solved.
And there's an oversight question too.
If you have a large army of drones or robots that can operate without any
human oversight, where there aren't human soldiers to make the decisions
about who to target, who to shoot at, that, that presents concerns.
And we need to have a conversation about, about how that's overseen.
Well, that kind of sounds like common sense.
What's the argument against it from Pete Hegseth?
He basically is taking a stance that in the heat of war, we should
use whatever's available to us.
And, the way that it's gonna be maximally.
Um.
Efficient and lethal.
As, as, as we need it.
So he basically, decided, about a month ago, earlier this year,
that Anthropic couldn't be trusted to provide the technology if they weren't
going to be on board for anything the Pentagon wanted to use it for and wanted
to change the terms of the contract.
And that's where we wound up with his impasse.
Yeah, and you can imagine if listeners, you've run into AI mistakes or what they
call hallucinations in little ways in your life, what the implications might
be if AI models are picking out their own targets without human supervision.
I'm thinking of a little thing, Steven, where I was looking up sort
of wars going on around the world.
And the AI model in my Google search was the first thing that came up.
And one of the ones that it listed for Latin America was
Armenia versus Azerbaijan.
Well, guess where is not in Latin America?
But if it can do that, then, you know, I don't know, maybe that girl's
school in Iran where 175 people reportedly were killed already in this war, most of
them children, somebody made a mistake.
We don't know if it was AI that made a mistake, but you don't want AI
to be able to potentially make that mistake without human supervision, right?
That's right.
Oversight is so important when you use ai, whether
you're, doing research and, you know, and, and in the process of putting
that research into a final product, you, you've gotta check everything very
carefully, and even more carefully as you suggest if you're targeting.
Something with lethal force, you really wanna be sure that you've got it right,
otherwise you will hit, a girl's school instead of a military target.
And this is what greatly concerns Anthropic and
I think down the road, I think it, it should concern all of us.
In terms of how AI is used in general.
The big question is there's no ceiling for the capabilities
of AI as it's being developed.
We're trying to figure this out and, companies like Anthropic
and Open ai, and Google and the rest of them are developing this
technology and trying to make it safe.
But they're in a race between, you know, each other, who's going to get to
artificial general intelligence first?
And that's more important to them, I think, in the
priorities than doing it safely.
And we see through the military lens how dangerous this can be.
And again, the two ethics clauses in anthropics terms of service are
prohibiting, the AI model clause from being used in autonomous weapon systems.
That's the one we've been talking about.
The other one is for mass surveillance of American citizens.
Here's CEO Amodei, Amodei on that.
I am concerned that AI may be uniquely well suited to autocracy and to deepening
the repression that we see in autocracies.
We already see it in the kind of surveillance state that is
possible with today's technology.
But if you think of the extent to which AI can make individualized propaganda,
can break into any computer system in the world, can,
surveil everyone, everyone in a population detect descent everywhere and suppress
it, make, a a, a huge army of drones that could go after
each, each, each individual person.
It's, it's, it's really scary.
So Steven, is Amodei describing there anything that the Pentagon
was specifically asking for?
Or is that a more hypothetical concern at this point?
Well, I, I think it, it, it really isn't, a remote possibility.
If you see the, the nature of the argument and, you can go way
down into the weeds about what the, in the contract with,
Anthropic the Pentagon wanted to do, and what they've, forged with
a contract that they did execute with OpenAI, which rush into to take it place.
They, you wanna watch out for what they won't do.
And what they seem reluctant to grant the AI companies is the promise that
they won't use all kinds of information that's available, in the public sector
or from data brokers, and then use that for, how they treat.
Citizens, and it, it turns out what's legal to
do, could be much more powerful if you use AI and much scarier in
terms of, a surveillance state.
So, and I think the, AI companies, particularly Anthropic,
are very sensitive about that.
They don't want to be the trigger to, make things a 1984 dystopia, and they're
trying to say, don't use us for that.
Ukraine instantly turned itself into a laboratory of technological innovation.
The Ukrainian military, which has done a remarkable job against a much
better funded and staffed military, has done so by outsourcing so many
important things to private companies.
This experimentation has resulted in one of the most, I think, important military.
Weapons developed in the last couple of decades, and that is a hovering
drone, a drone that stays far enough up in the atmosphere that it's almost
impossible to even sense from the ground and it's poised to strike.
That means Russian troops in the field are under constant possible attack.
Now, of course, the Russian military developed the same technology, and so
troops in Ukraine and civilians in Ukraine are also under the same constant threat.
So we can move forward to Gaza and see how Israel, which has had its own
programs of mass surveillance using artificial intelligence for more than
a decade, to try to identify hostile parties both in the West Bank and in
Gaza, and frankly in Lebanon as well.
So given that for the last three years, Israel has been trying to pick out
whom to attack in a densely populated urban scene, like Gaza is really hard.
And so what they've done is they've outsourced it to machines
that they hope are quite precise.
Now, what we do know is given the large number of civilian casualties, the medical
facilities, the human rights organizations that have been interrupted, bombed, et
cetera, the number of journalists killed that either Israel is being duplicitous
about their desires for targeting, or the systems just aren't as good as they hope.
You write that what was normalized in Gaza will not stay in Gaza.
You say, this isn't just about an export of technology, it's
an export of a habit of mind
that basically says we can do everything faster.
We can do everything easier.
We can take human beings out of the loop as much as possible,
and we're living in an age where accountability seems an impossible dream.
You call autonomous weapons, quote, accountability dissolving machines.
That's right.
If stuff is happening so fast and so furiously, it's a lot harder for
inspectors general, for judge advocate generals, attorneys general, it's a lot
harder for courts to make individual discreet judgments in a timely fashion
to actually affect anything in the world.
And so the more we raise the metabolism of warfare, the harder it is to oversee
the proper execution of warfare, the moral execution of warfare, if
there is such a thing, the humanity that might be embedded in warfare.
And look, we've been struggling definitely since World War I, with increased
attention after Vietnam War with all of its excesses of civilian casualties and
human rights violations to embed within the US military, a sense of honor, a sense
of duty, a sense of legality, a sense that lethality should be deployed only
under the most extreme circumstances.
And the US military has done an outstanding job of that since
the end of the Vietnam War.
They've done it while certainly under pressure from Congress and the
public, but the US military had done a remarkable job to police itself
right up through the Afghan War.
And all of that is out the window now.
And AI being introduced at this level, at this moment, only makes it more dangerous.
I'm gonna raise this experiment at New College London, which tested out
three leading AI systems from OpenAI, Anthropic, and Google in war simulations.
They found that.
The AI didn't have nearly the same reservations as humans and used
nuclear weapons in 95% of cases.
Dean Ball, who helped developed President Trump's AI policy in a senior post at the
White House last year posted on x quote, if near medium future AI systems can be
used by the executive branch to arbitrary ends with zero restrictions, the US will
functionally cease to be a republic.
I mean, where do you think all this is going
to Dr.
Strangelove?
I think we're in a moment where, if you remember Dr. Strange love, and I
know you do, the whole film ends with a moment at which the momentum of decision
making for nuclear war was unstoppable.
This imposition and installation of AI decision making systems that minimize
human influence over what kind of weapons we're gonna use when we will use them,
of the extremists among the nuclear
strategists of the 1950s and sixties.
So, look, we've also had to great credit of the United States an
actual debate for 70 years over when and how to use the most lethal weapons.
We actually had debate at the highest levels the fact that we trusted a
president, not just a president, like eight presidents with the lives of the
entire world, understanding that most human beings would make the right decision
when offered the right information.
That level of trust that we put into presidents of both parties,
many of whom were not really great people, says a lot about.
The fact that we've managed to live this long and we had
a system that mostly worked.
Are we in that situation?
Do we have an executive we can trust with the future of the world?
Who actually thinks about the children in a girl's school
in a remote corner of Iran?
Do we have a present who thinks about the long-term repercussions of
the use of certain weapons and the deployment of certain technologies?
I think it's safe to say we do not.
So all of that difficult work that has been done in the military, in the Rand
Corporation, in the halls of Congress in White House after White House, after White
House for decades, has been stripped out.
We are in a very dangerous moment in which to rely on these systems.
We've seen a, a trajectory of the military adopting AI tools over the last
decade as AI has continued to progress.
What's newer are large language models like ChatGPT and Anthropic's Claude,
that it's been reported the military is using in operations in Iran.
And so that's a, that's a pretty significant development that we're seeing.
And the, the people wanna know how Claude or chat GPT might be fighting this war.
Do we know war in Iran?
That's a great idea.
Let me help you with that.
Well, we don't know yet.
We can make some educated guesses based on
what the technology could do.
AI technologies really great at processing large amounts of information.
I
literally love processing.
The US militaries hit over a thousand targets in Iran,
as you see very well.
They have no navy, it's been knocked out.
They have no air force.
It's been knocked out.
They have no air detection that's been knocked out.
Their radar has been knocked out.
They need to then find ways to process information about those targets.
So satellite imagery, for example, of the targets they've hit
just about everything that's been knocked out.
Looking at new potential targets, prioritizing those processing
information and using AI to do that at machine speed rather than human speed.
Human so slow mo ha ha ha.
Cheers.
Do we know any more about how the military may have used AI in, say, Venezuela
on the attack that brought Nicholas Maduro to Brooklyn of all places?
Brooklyn and the hell, because we've recently found out
that AI was used there too.
So what we do know is that Anthropic's AI tools have been integrated
into the US military's classified networks, and so they can process
classified information to process intelligence, to help plan operations
from writing emails to rating enemy capital cities.
The Wall Street Journal reports that the Pentagon used Anthropic's AI model
Claude as part of its operation to capture Venezuelan president Nicholas Maduro.
There's no suggestion that Claude was actually firing any of the missiles
or manning any of the machine guns.
Yeah, we've had this sort of tantalizing details, okay.
That these tools were used in the Maduro raid.
We don't know exactly how, so.
We've seen AI technology in a broad sense used in other conflicts as well
in Ukraine, in Israel's operations in Gaza, to do a couple different things.
One of the ways that AI is being used in Ukraine in a different
kind of context is putting autonomy aren't to drones themselves.
The drone now flies on autopilot mode.
Using our software, we assigned it with a mission and it built its own flying route,
giving the munition instructions on where it needs to go and
what it needs to look for.
And so when I was in Ukraine, one of the things that I saw Ukrainian drone
operators and engineers demonstrate is a little box like the size of a pack
of cigarettes that you could put onto a small drone that would enable the,
once the human locks onto a target.
The drone can then carry out the attack all on its own.
And that has been used in a small, small way.
It's not necessarily widespread use in Ukraine today.
So we're seeing AI begin to creep into all of these aspects of military
operations in intelligence and planning and logistics, but also right at the
edge in terms of, being used where drones are completing attacks.
Okay.
So we know a little bit more about how this technology was used in Ukraine.
How about with Israel and Gaza?
So there's been some reporting about how the Israel defense forces have used AI
in Gaza, not necessarily large language models, but machine learning systems that
can synthesize, infuse large amounts of information, geolocation data, cell phone
data and connection, social media data to bring this together, process all of
the information very quickly to develop targeting packages, particularly in the
early phases of Israel's operations,
which suggests specific possible targets, possible munitions warnings.
This system produces targets in Gaza faster than a human can.
But it raises thorny questions about, human
involvement in these decisions.
And one of the criticisms that had come up was that humans were still approving
these targets, but that the volume of strikes and the amount of information
that needed to be processed was such that maybe human oversight in some cases
was a little bit more of a rubber stamp.
The question is, where does this go?
And are we heading a trajectory where over time humans get pushed
out of the loop and we see down the road fully autonomous weapons that
are making their own decisions about whom to kill on the battlefield.
That's the direction things are headed.
So, no one's unleashing the swarm of killer robots today, but
the trajectory is in that direction.
And I, maybe I'll make a comparison here, to self-driving cars,
where car companies can map the environment down to the centimeter.
They know the height of the curbs, they know where the stoplights are.
They can test self-driving cars in the actual environment they're gonna be in.
And when they're do something weird that doesn't work, they
can update the algorithm.
We don't know our future war.
Is it gonna be fought?
It's an adversarial environment.
We don't know what the enemy's gonna do.
I mean, the US military is finding this out right now in
its operations against Iran.
They're retaliating against US bases against Gulf States, against
Israel using drones and missiles.
And now we're in a phase in the Iran conflict where things
become super unpredictable.
People do an okay job of adapting that unpredictability.
AI is not so great and sometimes does some strange things
because you drew a parallel to self-driving cars.
We've made an episode about self-driving cars before in
which, I think our guests said something like, well, if you're
worried about self-driving cars, you know what we should really be worried
about is humans thinking about Iran.
We saw reports that a school was bombed in Iran where mm-hmm.
Maybe 160 were killed.
A lot of them young.
Girls, children, presumably that was a mistake made by a human.
Do we think that autonomous weapons will be capable of making that same mistake or
will they be better at war than we are?
This question of will autonomous weapons be better than humans are not, is like
one of the core issues of the debate surrounding this technology because
proponents of autonomous weapons will say, look, people make mistakes all the time,
and machines might be able to do better.
Part of that depends on how much the militaries that are using this technology
are trying really hard to avoid mistakes.
If militaries don't care about civilian casualties, then AI can allow militaries
to simply strike targets faster, in some cases, even commit atrocities faster, if
that's what militaries are trying to do.
I think there is this really important potential here to use
the technology to be more precise.
And if you look at the long arc of precision guided weapons, let's say over
the last century or so, it's pointed towards much more precision and warfare.
So if you look at the example of the US strikes in Iran right now, it's worth
contrasting this with the widespread aerial bombing campaigns against
cities that we saw in World War ii, for example, where whole cities were
devastated in Europe and Asia because the bombs just weren't precise at all.
And so Air Forces dropped just, just massive amounts of ordinance
to try to hit even a single factory.
The possibility here is that AI could make it better over time to allow
militaries to hit military targets and avoid civilian casualties.
Now, if the data is wrong and they've got the wrong target on the list, they're
gonna hit the wrong thing very precisely, and AI's not necessarily gonna fix that.
Now, section C surveillance,
I wanna briefly ask you about surveillance in general, and
in particular, Anthropic's Fourth Amendment concern, right?
The Fourth Amendment says the government can't unreasonably search you.
The best way to understand the Fourth Amendment is by listening
to nine, nine problems by Jay-Z.
So if you need to take a break and go listen to, to nine,
nine problems, that's great.
It, it's all in there.
I, I listened to it when I was in law school and made perfect sense,
but the government generally needs a warrant to like search you.
And as more and more of your life goes online, there's lots
and lots of exceptions to this.
But the idea is they should still need a warrant online.
Anthropic's argument is, well, the AI will never get tired.
It can search everything all the time.
That means we're just gonna do master surveillance.
But even before AI showed up, right, the idea that the government could
search everything that belonged to you was out there, the idea that the
government didn't need a warrant to search all your stuff was out there.
The idea that if any of your data ever went outside the country for a brief
second, the government intercepted there was out there when I was in college
around the time of the Patriot Act, the debate was they're not gonna search
your actual data, but they can get the metadata and the metadata alone.
The data about your data will be enough to precisely locate you at all times.
And that even that is too far.
And we, we've been doing this dance of what can the government collect?
What is permissible?
What's, what do they need to keep us all safe and what's too far?
Those lines have moved.
So just briefly describe the, the sort of.
Generalized concern about surveillance at the scale and where we are now.
Yeah.
Before the AI situation sort of exponentially made
everything more complicated.
Yeah.
And here I have to introduce another concept that, that probably should have
mentioned earlier, but it is important, which is called the third party Doctrine.
And so the idea with the Fourth Amendment is that the government can't search you
or your things without a warrant, and it can't get a warrant without probable cause
that you've committed some sort of crime.
But there's this concept which came about decades ago called the Third
Party Doctrine, which says that doesn't necessarily apply or doesn't
apply at all to things that aren't yours, even if it is your data.
And so the, the earliest and most obvious version of this was phone records that the
phone company had of who, who you called.
The phone companies weren't recording your calls, but they were recording.
If I called you, there would be a record at the phone
company that says Mike calls Nele.
What had been determined by multiple courts was that the, the government can
go and request, and they don't need a warrant for that because it's not a search
of your data, it's this third party.
And they can agree as a third party to just hand over that, that data.
But that was like, cases from the sixties and seventies where that
was determined that the government can get access to that without a warrant.
When there wasn't that much third party data out there, the rise of
computers and the internet changed that now everything is third party data.
Everything that we do is collected by some company somewhere and has a record of it.
And so basically every bit of data about you, where you are, who you speak to, who
you interact with, what you say, where, what you're doing, all of that is pretty
much held by third parties these days.
And so the, the third party doctrine has sort of swallowed the entire
Fourth Amendment to some extent, where any, anything that is about
you ha there that somebody else has, there's a much lower standard for what
the government can do to request it.
Now, companies can,
and just to be specific, this means when my data's in iCloud,
yes,
the government can go to Apple and get my data out of iCloud
without ever telling me,
well, it, it's, it's, they can request it so they can easily
request it without a warrant.
Then the company has its own rights and can determine what
they want to do with that request.
They can just give it up.
They can, as most of them will do, is, if, if it's a serious
request, they can reject requests out of hand or they can alert you
and they can say, and this is what most of them will do, they'll alert
you and say, the government is requesting some of your data.
You can go to court and try and block them.
If not, we will hand over your data in seven days or whatever it might be.
Again, it depends.
If it's a criminal investigation, then there may be some sort of gag order where
the company's not allowed to tell you.
There's all sorts of situations, but most of them involve less than,
Fourth Amendment would require if it
was data in your, or any information or anything in your own home.
I'm asking this because it, it's obvious to everybody listening to this.
The amount of data you have on someone else's cloud server is massive, right?
Every, every single thing that you do, generally on the internet
now is backed up in some way or recorded in some way on someone
else's servers and the government has.
Found this way to get around the Fourth Amendment and say,
well, that's not actually yours.
It belongs to Amazon or whatever.
And we can go talk to Amazon.
And Amazon has to stand in the middle of that process and say,
we've invented another process to somewhat protect the people.
And I look at that and, the, when I was covering the first third party
doctrine cases that covered the cloud services and the government kept winning.
I mean, that's basically when I turned in the Joker and I was like, all
of this stuff that we're pretending about Textualism and the plain mean,
like none of this means anything.
Yeah.
'cause we, we've just, it horsepower to backdoor using this
ancient law into everyone's data.
And then I look at this and I, I look at Anthropic and I say, well,
this is the same pattern, right?
This is a private company saying, okay, we understand your position, we
understand that you've reinterpreted the law to mean this thing, and
we're gonna put some process in between you, our tool and the data of
Americans flowing through our service.
And I, I'm just wondering if you see that parallel there between
Anthropic and Amazon and Azure and whatever other cloud services that
exist that hold so much of our data.
Yeah.
Though I think there are a few clarifications that are
important here that, that make this a little bit different.
And in fact, it was reported, I think the New York Times had this
reporting first that, the main clause that was most important to
Anthropic was specifically about data collected from commercial services and
not being able to use Claude on that data, which is, exactly
this issue in terms of third party data.
But I do want to clarify the, the main difference where, what we
were just talking about before this with, with, Amazon or other
third parties, hosting your data.
That was cases where they were, you know, because of where they sit in
the ecosystem, they were hosting your data directly with Claude.
It's not that any, anyone is worried about the NSA looking through like your.
Claude usage, right?
Right.
It's, it's about them going out and getting third party data from an
Amazon, or more likely, the, the sort of sneaky, hidden data
brokers that serve ads on your phones and know all your location and, and
your interests and things like that.
And then feeding that into a system that Claude would then work on.
That's what Anthropic really didn't want to be a part of.
So wherever or however the government would collect that data from a third
party, Claude said, we don't, we don't want our tool to be used on that data.
There's a piece of that that just feels like Apple famously stands up to the FBI,
but a backdoor in the iPhone and Apple says no, and they stand up to Trump.
And there's just a part of, however our system works, in which big
private companies get to say no to the government on behalf of their customers.
And this felt the same, in the same way that, apple again
won't put a backdoor in the iPhone or the big cloud providers say.
There's a little bit of a process you have to jump through before
you get the individual data here.
It seems like Anthropic is saying, we're not just gonna do bulk analysis
of data that you have acquired from other parties because that
leads to 24 7 mass surveillance of Americans and we don't wanna do that.
And that seems like a bridge too far for this administration.
I, is there any coming back from that?
I mean, we'll see in the past when that's happened, and it's happened
plenty of times with, with most of the, the large tech companies, at some point
they've said something is a bridge too far, and where that normally goes
is to court and that, the, the companies will go to court or the
administration will go to court and there'll be some sort of court battle.
I mean, backdooring the iPhone is, is a perfect example of that sort
of went to court and they sort of fought it out though they never quite got to
a conclusion 'cause the FBI eventually did just, manually break into
the iPhone and then didn't want the court ruling to, to ruin the future.
But in this case, where the escalation is and where this is,
this is different than those past situations is that rather than just going
to court, they did this supply chain risk designation, which is just insane.
This idea that this tool which was designed to stop, far
potential foreign malicious actors from supplying technology that could then,
Put in hidden surveillance tools into the larger technology
stack that those could be banned to apply that to a US-based company.
Basically for having an ethics policy feels, like a
real, real, misuse of that tool.
And even that tool, I think was questionable in, in some ways, but
you could understand the, the impetus behind it for when you're talking
about like a Chinese networking firm or something along those lines here.
It makes no sense.
And so the, the reaction to this goes so far beyond what would
normally be seen in this case.
You could see, traditionally there would be some sort of court
case and either side could start it and it would just be a battle about,
What, what, how the contract could be applied.
But that's not what is happening here.
That, that this administration is effectively saying, if you don't
give us absolutely everything that we want, if you don't set up your
tools to work the way we want them to work, then we will effectively
try to destroy your entire business.
And that that is an escalation.
So I just wanna, read some New York Times reporting here because they had
sources inside of these negotiations just so people can understand
what apparently broke down here.
This is from the New York Times.
Emile Michael, who is the under secretary at the Pentagon for research
and Engineering, used to be at Uber, was, doing this negotiation with
Anthropic, was on a call with Anthropic exec executives Friday afternoon.
He said the Pentagon wanted anthropic to allow for collection and
analysis of unclassified commercial bulk data on Americans such as
geolocation and web browsing data.
This is according to people briefed on the negotiations.
Anthropic told the Pentagon that it was willing to let its technology
be used by the NSA for classified material collection under the Foreign
Intelligence Surveillance Act.
So FIA, but the company wanted a legally binding promise from the
Pentagon not to use its technology on unclassified commercial data.
So more of like that broad sweeping surveillance versus having to go and get a
judge to sign off on a, on a FIO warrant.
Is there anything that stands out to you about that dispute specifically?
I think we have companies trying to step in, as in some cases admirably,
So, FISA HA leaves it a little bit ambiguous about,
It's intended to allow intelligence collection on foreign adversaries
and in, in intelligence situations.
But as legal scholars have noted it, it sweeps in collection of
data on Americans as well, in all sorts of under related ways.
And so I think, anthropic, understands this, this gap and tried
to fill in where the law does not.
So that's admirable.
But again, outsourcing this to the decisions of a few people at the,
at the heads of these companies with, with who are pressured by different
incentives than the public interest is, is dangerous to say the least.
So.
Open AI inks, the contract with the Department of Defense.
They set in a blog post, the company set in a blog post that it had similar
guardrails to what Anthropic wanted.
And you, you've touched on that a little bit.
The analysis that I've read is that there were some differences in that
Anthropic was basically saying, we, the product that we give you, we would've
set these technical limits where this surveillance could not be accomplished.
Basically like a hardwired type thing in their technology that
they provided the Pentagon.
Whereas OpenAI was basically saying, we are gonna rely on the Department
of Defense to follow the law here.
And that that was a key difference.
Do you think that that's an important difference?
Do you, do you buy that?
It's hard to think about it without the context
of the current administration.
Right?
So they, they've demonstrated time and again that, that they're not,
they don't consider themselves to be subject to the, to the rule of law.
And so the idea that we'll leave it up to the DOD to, follow the law, everyone
knows what they're doing here, right?
Every, everyone knows that this is not gonna, that this is trying
to avoid any responsibility from OpenAI and shift blame to the DOD.
While we know that there's not gonna be any operational rules there.
So again, Anthropic tried to step up and say, well, let's at least
try to have some kind of legally binding, language that, that separates these,
these two things and OpenAI did not.
So, again, I think, I think it all is a manifestation
of, of the fact that we don't have any kind of coherent mechanism for,
for AI governance, at, at all.
And so these kinds of situations are some sense are in inevitable.
At the same time, the Pentagon is saying, and, and Secretary Heg, Seth, and the
folks who are negotiating this deal.
You can't have a company that we contract to provide a service deciding what we do.
With it, we are the Department of Defense.
Like we know what the law is and we know, what our
strategy is and we'll be compliant.
But a private company making those decisions for us, like that would
never happen with Raytheon being consulted on how one of its, you
know, drones was used for example.
Is is the fact that Anthropic wanted those limits overstepping, you
know, its role as, as a private company
To some extent.
This might be a better question for, those who study the law, but, you
know, I do think there is a material difference between what's going on with
AI as a technology and what's going on with, building planes and,
and, and, and building other weapons.
First of all, the speed at which those technologies have
been developed in the past allowed for the law to kind of catch up.
It was also in a very different context in terms of
the current administration and
basically like we know what a. Drone or a plane
can, and
can does, and AI is changing all the time.
That's right.
And, and, and, we collectively aren't always sure of
the capabilities of these things.
And so, there, there's a lot of market incentive to position
these technologies as, ultra powerful and, magical.
And the hype, the hype is very real, but the fact is that they
make extremely strange non-human errors with some regularity.
And so there is a danger in deploying these simply because of
the uncertainty and the scale with which they, with which they operate.
And I don't think anyone would argue that the laws are currently designed
to cover those, those, those cases.
And there's quite a lot of law here about mass surveillance.
There's a lot of history, a lot of controversial history.
The entire character of Edward Snowden exists because of controversies
around mass surveillance.
And it all comes down to, I think you are the one who posted this, the
National Security Agency, which is part of the Department of Defense, which
we have to call the Department of War.
Now for some reason,
we don't have to do anything.
We, we don't, that's true in America.
We don't have to do anything.
But the National Security Agency has basically redefined what a lot of words
mean out of like colloquial English to mean, oh, we can just do surveillance.
And then every so often there's a scandal when people discover that
they're just doing surveillance.
So just set the stage there.
And I don't wanna rewind you all the way, but it's been quite a lot of time,
where this pattern has repeated itself.
Yeah.
And, and yeah, it, it sort of depends on how deep you want to go, but the,
the sort of short version is obviously in the post nine 11 world, we, the US
passed the Patriot Act, which had, some ability for the government
to engage in surveillance, which was supposed to be for, protecting
us against future terrorist threats.
And the over time that got interpreted in interesting ways
and there were some limits on that.
We also had the FISA court, which is a special court that is supposed to,
Review the intelligence community and their activities.
But, has been traditionally a one-sided court, only one side
gets to plead their case to that court, and it's all done in secret.
And so there's a lot of stuff that, that was not known.
And then there was one other piece in all of this, which goes all the
way back to Ronald Reagan, which is executive order 12 3 3, which is
supposedly about setting out the rules of the road for intelligence collection.
And so you have these three sets of laws, well, a few sets of laws
and an executive order that to the public.
The parts that you can read seem to say certain things about what our
government and the NSA in particular can do in terms of surveillance.
Which when read with a plain English dictionary, the nature of which you
and I probably have and understand, we would come away with a belief
that the NSA's ability to surveil Americans was, was very limited in fact.
To the point that they're supposed to, if they realize
that they are surveilling a US person, that they're supposed to immediately
stop and cry foul and, erase the data and all of this other stuff.
And there were rumors for a while that that was not really
happening and there were hints and in particular, Senator Ron Wyden was
very vocal about, going on the floor of the Senate and saying,
Something is not right here.
And I can't quite tell you what, or in hearings he would ask intelligence
officials, are you or are you not collecting mass data on Americans?
And they would either deflect or in some cases outright lie.
And I believe it was one hearing in like 2012 with James Clapper,
who was the director of National Intelligence at the time.
He was asked directly on this point, and he basically said, no,
we don't collect data on Americans.
And that was.
A big part of what inspired Ed Snowden to leak the data, the, the, the reports
that he leaked to Glenn Greenwald and, Bart Gelman and Laura Laura pores as well.
So from all of that, what we began to discover was that the NSA has its own
dictionary that is somewhat different than the dictionary that you and I use,
such that they can interpret words in ways that are different than the plain
English meaning of them, including words like target, which feels like kind of
a key word, but so, a, a sort of broad understanding of what this is.
In theory, they're only supposed to target people who are not US
persons, I think is the phrase.
But the way it had been interpreted over time was that, anything that
mentions that person, any, anything that is about a foreign person,
is now fair game, even if that is the communications of a US person.
So if you and I were to text each other and mention a foreign person,
that is now fair game for the NSA to collect and to keep and to store,
there's a second part of this.
I mentioned, first the, the executive order 12 3 3 from Ronald
Reagan, which effectively allowed the NSA as as the technology changed
over time and the internet grew.
It allowed the NSA to tap into foreign communications, but that
included any communications that maybe left the US on route somewhere.
So if, if I'm texting you and a message went from me in California
through a fiber optic cable that happened to leave the us, the NSA could put a
tap in the part once it's outside the US collect that information, even if
it was just going to you within the us.
Then what they could do is keep that information, even if it was on US
persons, and they could do specific searches on that later, sometimes
referred to as backdoor searches.
So they collected this information that we believe they weren't
supposed to collect in the first place, but they could keep it.
And they promised, they sort of pinky swore that they would keep it private.
But if they did, a search and found like that you or I mentioned a foreign
person, then suddenly it was fair game for them to do whatever they want with.
In total that has turned into a world in which they can basically
collect any information that ha happens to touch outside the us.
And even if it is entirely between two US persons, if they mention or even
hint at someone who is not a US person, suddenly it is fair game to be collected.
And from that, we've gotten what appears to be a, a form of mass surveillance of US
persons by an NSA that claims and publicly states that they do not spy on US persons.
How did we get to this point?
Right?
This is a lot of incremental baby steps.
You mentioned James Clapper in 2012.
That's the Obama administration.
You mentioned Ronald Reagan.
That's the eighties.
Like we're, we're, we're going through Democrats and Republicans here, right?
Yes.
How the, the, the War on Terror happens in the, in the George W.
Bush administration nine 11 and the Patriot Act happens in the
George W. Bush administration.
This is a lot of incremental bad things.
Yes.
Under presidents of both parties, under congresses of both parties.
How did this happen?
I mean, the, the simplest form of it is just that nobody, and certainly
no president, wants to be president during the time when there's a
big terrorist attack because that, that makes them look bad, right?
I mean, obviously they also wanna protect Americans, right?
That's part of, part of their job, I guess.
And so, if you have an intelligence community that is basically
operating a darkness, because that's what intelligence communities do, and
they keep coming to you and saying, you know, Hey, if we could just get
access to this information, it'd be really helpful in preventing a terrorist attack.
And there may be cases where that's true, that the intelligence community
is able to use this information in a way that works well, but we also are
in theory, a society of laws and a constitution that we're supposed to obey.
But that allowed for the fact that, you know, administration after administration,
again, Republican and Democrat, had lawyers who were very clever and who
would look through, well, if we sort of position this this way, or
we state this this way, or we interpret this, that way we can get what we want
and not technically break the law or not technically violate the Fourth Amendment.
The assumption was always like, well, we can sort of bend the law or bend
our interpretation of the law, and nobody's really ever going to see
this, or nobody who cares, is really ever going to see this,
and therefore we'll get away with it.
So now we get to the retaliation piece.
If retaliation isn't too strong a word, how did the Pentagon react to,
Amodei and his company and Anthropic wanting these two ethics clause clauses
in their contract with the Pentagon?
Well, this is the really striking part of, of the story in on, in terms of
how the administration is, is acting.
You would think that they would say, you know what?
Anthropic, you've got these red lines.
We can't accept these.
We're gonna go to another company and use their technology.
We'll have a transition period, where, we'll phase out
your Claude AI model and do something else, and we'll go our separate ways.
Instead, what the Pentagon did and the administration has embraced, is
saying that we're gonna label you what's called a supply chain risk.
And this is something used against typically foreign companies, country
countries, which is seen as our enemies.
Yeah.
And they've gone even farther.
And said that any company that does business with Anthropic, the
government will not do business with.
And that's a potentially crippling blow to a corporation.
Are they going through with it?
Well, we've seen several agencies, treasury House of Human Services say that
we're not gonna use Anthropic and we're, and we're not gonna do business with other
companies that, that, that do this Now, so far Donald Trump has written this.
It's only in the tweet.
They actually haven't formally invoked this, but the agencies are saying they're
doing it anyway, and Anthropic has indicated they're gonna sue to fight that.
The Financial Times reports that as of this morning, talks between Anthropic
and the Pentagon have quietly reopened.
Is there.
A version of this that ends well from an ethical standpoint, or does it seem like
Amodei will need to relinquish his ideals for the sake of his company's profits?
Well,
or even, or even e existence if the retaliation is too strong.
Yeah.
Amodei, he, he, he put out an internal memo that, was very strong.
He said that the reason why they're being punished is because
they don't cater to Donald Trump.
They don't do what he called dictator like,
Obedience to, to Trump.
They don't give money like the, one of the top executives
of OpenAI gave to a Trump pack.
And he said, that's what's behind all this.
So it's a little surprising that they're going back to the table now.
But I suspect if that's happening, it's because the Pentagon's realizing
it's maybe tougher than they thought to disengage Claude from their
activities, especially during a war.
And they need Anthropic's help.
But to your larger question, there actually isn't a, a way to,
spin this as something we're all as happy.
A couple years ago, we were in a position where all the AI companies,
most of the people in the government and Congress were saying, you know what?
We have to come across with some sort of regulation, some sort of plan to figure
out how we're going to deal with AI's.
Very scary powers.
There's great opportunities, but also very scary powers.
They talked about regulation.
They talked about international bodies that might eliminate ai,
AI from certain kinds of warfare.
That's all gone now.
We're all about competition with China.
In, in ai, the companies are all about competition with each other.
So, I see a rather bleak outcome from that.
This, flap is a symbol of,
I said in the intro that.
This standoff between AI and the Pentagon.
It's obviously specific to that company and that branch of government, but
it might have overtones for the safe deployment of AI in all kinds of sectors
of American life, world life and society.
Do you see that?
Absolutely.
I mean, I, I, I think, it is, yeah, because I, I just said this is an
indicator that when it comes to what we once thought very recently was,
out how, how this technology could not be used to the detriment of human humankind.
That's gone by the wayside.
And now it's, accelerate, accelerate, accelerate until,
the point, we can control it.
And finally, section D corporate power.
I'm wondering why, you can tell me why the left hates technology so much.
Well, it's, have you ever had a, a, a personal consumer grade printer before?
That's, that's my recent, oh, my brother, brother, the manufacturer of
the only good consumer grade printer.
No, it's, it's, there has been, I think in the recent round as Bryan
Befriend of, both of us, Bryan Merchant has pointed out in the recent
round of fundraising for Anthropic, there has been a sort of meme that has
proliferated throughout the internet that, opposition to or support for AI can
be something you can predicate along.
Left right.
Grounds and baseline.
That is not an argument I agree with because I see people of all stripes,
even people who politically are not on my side at all say that they're grossed out
and disgusted by generative AI and the things that it's creates and also because
like there are dumb leftists that also like this stuff, like it's that tweet.
I do not support a woman.
Some of you bitches are very dumb.
It's true of people across the political spectrum, but also it's something I don't
believe because there is technology out there that I do enjoy and like using and
think could be a net benefit for society.
It's just that when you, when people start talking about technology as a discreet
object, frequently what they mean is the most extractive and most repressive and
oppressive technology you could have.
In this case, we are referring to generative AI and AI assistance in
companies like Anthropic and Open ai, who are all, I think I can say on this show.
I think all those companies are evil.
Absolutely a hundred percent.
I just recently wrote as much about open ai, but we, we feel the,
the same way about the rest of them.
It's fascinating to me.
Like there's many things like a pick up on, in, in what you just said and,
We, we will get to a lot of it, but even the term technology and
how it is like defined, like for a long time, if you talked about technology,
you basically meant like internet technology, digital technology, right?
Any other form of technology was not considered technology.
It did not like fit under the term of what we're talking about when we
generally talk about technology because this is what the industry is focused on.
This is what the industry is pushing.
And now it feels like, especially in these recent kind of like discussions,
the kind of scope of that term is narrowed even further around generative
AI and like what is being pushed in this moment and like, it's such a
reductive way to talk about technology and, and what is going on, right.
Yeah, let's expand the definition of what technology mean.
What does innovation mean?
I think mRNA vaccines are an incredible piece of technology.
Love 'em.
Huge.
A huge innovation.
I have a
bunch
of me, yeah.
I wanna get jabbed.
Let me get jabbed even more.
I think high speed rail, the kind that is not being developed.
Boom.
Big fans of trains on this podcast.
Yeah,
I love trains.
Absolutely love that.
Oh my God, if I could get to Chicago from New York by train, if I could go
to Toronto by train, I would be golden.
I would be so happy.
How is there not a high speed train between Toronto and
Montreal, like this baffle?
Oh
God.
that doesn't make any sense.
No.
At all.
Like it, that's a perfect corridor for high speed train and high speed transit.
There's also little things that I've been using in my life.
I asked, I'm sure you're aware of Chris person from Aftermath.
Heard of
him.
I've, yeah, I know.
Recent guest
on the show.
Yeah.
A totally normal, regular person.
Chris person.
We're recording this episode on his birthday.
Happy birthday, Chris.
Oh, happy birthday.
Yeah.
And, it'll
be belated by the time it airs, but you know.
Yeah, of course.
But you know.
I think anytime someone says it's your birthday, it should
count as your birthday.
You should just feel like it's your birthday.
Totally.
Because
you're allowed.
Yeah.
And we should also celebrate half birthdays.
That is my thing.
I, yeah.
Yes.
You mentioned that to me years ago.
Yeah.
And at the time I think I had lower self-esteem, but now
I'm like, yeah, absolutely.
I think you should just have a party whenever you want for
whatever reason, and everyone should act like it's your birthday.
I think party fall is also a meaningful piece of technology in my life.
There's little things and there's big things like this, but the idea
that in order to be in support of technology, you have to be in support
of the financial interest of Silicon Valley is what really frustrates me.
Because when you say technology is AI is generative ai, that is what you
essentially are saying, that there was a vaccine that just lost funding and will
now have to be indefinitely shelved for the herpes simplex virus, which would've
allowed people to be vaccinated against any, derivative virus that is like
illness is caused by herpes, which includes shingles, which I know a lot
of people of my generation have because they were encouraged to get chickenpox by
their parents who didn't know any better.
That is technology.
I would so much rather our government in our economy devote,
like, orient itself around.
Instead, we are in this place where, as Chris probably
mentioned, RAMP is their food roof.
No one can buy a hard drive anymore.
You're not gonna get your fun consumer, luxury electronics like
a new switch or a new PlayStation.
Your the internet worse.
Don't even
try to get that steam machine that Chris is so excited
about, not even coming.
Oh God
so bad.
And it's not gonna happen now because the entire world's economy is oriented around
the finances of two or three companies that are not even making a product that
functions like it makes me, it is very much an emperor's new clothes moment.
Like the Emperor Sam Elman is out here nude as hell, and I feel like
I'm being forced to tolerate him.
It's wild to me too because like, I just came across this study that was like
published last year by OpenAI itself, where they like basically admitted that
hallucinations are part of the product.
Like they're not going to come out.
So it's like the whole notion was these things are gonna get better,
we're gonna like get it out of the product at some point, but here's
OpenAI, like the leader in the charge for generative AI being like, yeah.
That thing where like, you know, the technology that we make
that we say is so intelligent and like basically human level smart.
Yeah.
It's just gonna, gonna make things that are wrong all the
time because that's built in there
thick.
Yeah.
Great.
Yeah.
I feel like we keep coming across these cases.
The blogs that I wrote that you read and that you invited me on for
the left doesn't hate technology.
They hate being, we hate Being Exploited,
which is
in
the show notes for listeners.
Yeah.
It was re a response to a, a really dumb blog by some random person that
I just kept seeing on the timeline.
Yeah.
And you know what, sometimes you read something and it makes
you so angry that you write 1500 words in about half an hour.
And that is what happened to me, where the insistence that the potential
for good that this technology could maybe possibly do in the future is the
reason why we have to invest in it now.
And we were foolish if you're a leftist for not investing in it, that is just.
Speculative at best, like that is something you could speculate about
the abilities for AI to cure cancer, that there's a, a speculative case you
could possibly make in the present.
Right now, AI has caused a school shooting where the casualties were children.
There were like 8, 8, 12 year olds died, where multiple children, again, have
taken their own lives because of this.
It's, I used to say that Q Anon really scared me 'cause I'd never seen something
drive people to psychosis like with no previous history of psychosis.
So quickly, AI drives those same kinds of people even faster.
And it's like you get your own personal Q anon when you really get deep into it.
And there's examples and examples and examples of it not even being able to
do its core functionality correctly.
I know that OpenAI has said it's patch, the Rs and strawberries thing, but I
saw a video video of someone a month ago asking OpenAI, asking ChatGPT how
many Rs there are in strawberry and it not being able to answer it correctly.
So I you have to be, the word I keep coming back to is credulous.
You have to be a credulous buffoon in order to take these
things and then project outward optimistically, I, I believe.
The, the idea of fully automated luxury communism is
something that, something that I really wished would come to pass.
But the more we can see the way that this technology interacts with capital
interacts with corrupt governance, the more it becomes clear that it's just.
Corporations milking the government for all the money they can get
and then not delivering a product as they have done previously.
In the last 10,
in the fallout of the Quick Department of Defense deal with
OpenAI, protestors showed up outside OpenAI headquarters and users began
deleting chat GPT from their phones.
And then Claude saw a massive uptick in downloads and subscriptions,
surpassing chat GPT for the first time in the app store to become the number
one app across all phone interfaces.
This has, of course, sent OpenAI scrambling to try to fix the PR disaster
of this Department of Defense contract, and I think it's a powerful indicator of
the current public sentiment around ai.
Generally, people are curious.
Many people are using it.
Some use it daily, either because their corporate jobs make them or because
they find the chat tools helpful.
Some people have developed a concern in codependency on these apps using
them instead of real human interaction as a form of companionship in ways
that we're just beginning to see the consequences of which include numerous.
AI encouraged suicides and self-harm.
And so people, even those who use the technology, are rightfully concerned
about the safety of AI from the safety of consumers to the potential for AI
to be used at mass scale to undermine democratic values or take human life On
top of that, we're watching our lawmakers do absolutely fucking nothing about it.
And so absent actual laws, reforms, regulations, or any action at all
from the people we've put in charge of regulating these things, we are turning
to the AI companies themselves for assurances that they aren't up to no good.
And Anthropic, which was founded in 2020 by former open AI employees
who were deeply concerned with open AI's, recklessness, provides a lot of
assurances of its ethics on its website.
And through its founder, Dario Amodei, and his many blog posts.
And now through its apparent stance against the Pentagon, its
willingness to put its neck on the line to honor its commitments while
OpenAI is happy to do whatever the government wants or so it seems.
And the public is voting with its attention, its dollars and its
data by deleting chat GPT in favor of Anthropics Claude Chatbot.
But I think it's deeply misplaced to put so much trust
in any of these AI companies.
And let me explain why I think this.
If there's one thing I've learned as I've delved into the world of AI development,
it's that the people doing the developing don't just see it as their job.
It makes up a part of their entire worldview.
So to understand the AI world, which is deeply important for everyday
consumers and everyday members of civil society who wanna hold their lawmakers
accountable to understand the AI world, you have to understand the AI worldview,
the book Empire of AI by Karen Howe, is the best thing period that I've
read over probably the last year.
And it lays out the AI world in a really accessible, readable
way that is a genuinely entertaining, if horrifying read.
And I think everyone.
Should read this book genuinely.
I'm not affiliated in any way with it.
I just think everyone should read it as a very brief and incomplete overview.
The key ideas that you need to know to understand how AI fits into the
worldview of its creators includes understanding the spectrum of AI
ethics that AI developers fall onto.
You have accelerationist on one end people who think that artificial
intelligence is like the key to human development and flourishing,
and that it should be developed as quickly as possible unencumbered
by pesky government regulations.
And then on the other end of the spectrum, you have the doomers who
believe that AI development will result in the destruction of humanity, and
therefore its development must be carefully restrained within that camp.
Many of its adherence are guided by effective altruism or attempting
to do the most good with their technological innovations.
However, taking a step back from all of that, it's important to keep in
mind the kind of accepted ideas that everyone on this spectrum, no matter
where they fall, has that, is that whether you are an accelerationist
or a dor, you kind of have to be convinced in general of the power of ai.
Many people falling anywhere on the spectrum deeply believe
in the possibility of a GI.
Artificial general intelligence.
If you didn't genuinely believe that AI is going to revolutionize the world,
then you wouldn't be so passionate as to fall anywhere on the spectrum.
The problem is that no one can actually define a GI, not specifically.
Most people just say, we'll know it when we see it.
Or they give vague definitions like it's a type of AI that is
sentient that can think for itself.
But large language models, the type of AI that's taken over popularity
because there's more than one type of artificial intelligence.
The LLM models are just guessing the next word based on the
data it's been trained on.
That is not sentience no matter how much data you feed.
It.
Also, the latest AI models have already been trained on basically
all available human created language that's been digitized in existence.
And I don't think anyone is arguing that we've reached a GI.
So like where are they gonna get that data?
So the generally accepted hypothesis in the AI community.
That a GI is the clear outcome of all of this, and therefore, we either must let it
flourish and it will benefit all mankind or tamp it down with a serious guardrails,
or it will extinguish all mankind.
All of that rests on the overall belief in the power of ai and that a GI is
possible, and that whole thesis is unproven, which is I think, an important
high level point to understand because much of the AI landscape we're dealing
with right now is the result of the hubris and ego of a few mostly men.
And in practice, AI can definitely do impressive things, but the
level of false advertising that the company's trying to sell us on, the
AI version of whatever products they offer is through the fucking roof.
For example, last November, the Verge did an experiment where it asked Microsoft
copilot to do the exact things Microsoft claimed it could do in the copilot
commercials with embarrassing results.
Can you get me a link to one that's in stock?
Here's the link to Best Buy, link to Best buy.com/eleven.
Best Buy slash Sure website.
And it's foremost definitely in stock and it's for most definitely in stock and
it's available for pickup or delivery, and it's for most definitely in stock.
Okay, thanks Copilot.
So there is a vast assumption happening based on a theory that the end result
of AI will mostly definitely be a GI.
And that is just a theory at this point.
And a lot of this worldview has resulted in what Karen Howe describes
in her book, empire of AI as basically a self-fulfilling prophecy.
Because for open ai, especially in its fearmongering over the future of a GI, the
dangers of it and especially the dangers of a GI, if China develops it first, which
is a favorite fearmongering tactics for.
Any new technology.
What if the comms get it first?
In all of this, fretting OpenAI itself has accelerated the rate of AI growth
beyond anyone's wildest expectations.
Even a decade ago.
Its demands for data centers for high powered chips for more and more and more
data to feed the AI training models.
All of it far surpasses anything China was ever doing, but it has
shown the world what's possible and how to do it and instigated an
arms race for the first company to reach the promised land of a GI.
If not for open ai, especially under Sam Altman, we would not have the AI
technology we have today and the move fast break things mentality that he
brought to the AI world has meant that for all the hand wringing over the
potential damage a GI could cause to humanity, it's become a race to the
bottom when it comes to AI development.
Who can do it the fastest, no matter the human cost spurred on by open AI
itself and all of this is over a GIA technology that is just a theory.
Meanwhile, despite all that advancement, we can't even get a
computer to do basic tasks on command.
AI has not delivered on the wide scale productivity it has promised
it's not delivered on the profits, it's promised it's not delivered on
the human flourishing it's promised.
All it has delivered so far is shareholder value.
A lot of speculation and endless, endless AI ads shoving this
technology down our throats.
Whether we like it or not.
I don't know if you watch the Super Bowl literally every other ad. Was an AI ad on
top of the human costs of ai, including suicides spurred on by chatbots, but also
the incredibly exploitative practices used in data harvesting, stealing IP
and paying people in the poorest parts of the globe, pennies to sift through
deeply traumatizing material to try to help train this AI and the incredibly
high environmental cost of all of it.
That's why Karen Howe named her book Empire of ai.
Her central thesis is that the AI boom is similar in many ways to all the other past
technological improvements that mainly led to increased wealth stratification
and depended on the exploited labor of marginalized populations.
Whether you're talking about the cotton gin or ChatGPT, this is why we
cannot pick winners in the AI race.
We can't look at these companies in black and white and think
anthropic good, open AI bad.
We should be looking at all of it with skepticism because the founders of these
companies, even ones like Anthropic with a lot of lofty, ostensibly charitable
and good goals, are coming from the same worldview that created the problems
of the world we currently exist in.
On that point, I was interested in asking you because you brought it up
and you mentioned it in your piece, but I was also a big techno optimist
for a while, and I know that you've written about being one as well.
I was wondering if you could talk to me about your journey from being a techno
optimist, being very optimistic about what this technology was going to deliver
to us and and shifting away from that.
I'm so glad you asked me that because I feel like in the piece, it's not
the point of it and I, I didn't get a chance to fully explain my journey.
So my parents are both like old hippies, so I always like the.
The household was always going to be a left wing household.
My parents didn't want to indoctrinate us, but they allowed a lot of
space for us to ask questions like, why does everybody need money?
Why do, why are some people poor?
And stuff like that.
They were generally in support of me and my brother becoming politically active.
And especially for me, like during, I mean, none of us knew what was
gonna happen with Obama, and that was my freshman year of college.
And they had had people from the campaign come out to Oberlin College
and put us on buses and say, let's go.
You're gonna go canvas in this neighborhood and let's go do it.
And I, I participated in that, it was impossible not
to get swept up in that emotion.
And my parents who are more left wing than that, they also wanted a black president.
Right?
Even if he didn't align a hundred percent on their views and
their values, it is like, my dad grew up, in the Jim Crow South.
Like I called him crying when it happened.
It is a, it was a moment that feels emotionally resonant, even though
I now hate Barack Obama with my life.
But at the time, like adding on to that, my dad's career is in it.
So my mother got a, has a tenureship at a college and he, up until a few
years ago, before when he retired, worked in it as a PC specialist.
So for me and for him, hand in hand with our liberation from a oppressive
government was an excitement for the communication networks
that the internet could provide.
We got a modem before anyone else I knew, and I was just a sponge for information.
The idea that I could talk to people from other countries who live totally
different lives for me, I completely ate all that up and I, I made friends
as an awkward teenager kind of for the first time with the aid of the internet.
And it introduced me to more joy, more discovery, more books, more
movies, more kinds of people.
I was deep in the fucking like internet piracy game too, so I
was voraciously like downloading and more information, more art.
To me, that is what technology meant was just a window into, I downloaded a tour
of Stranger Things when I was in college because it wasn't available anywhere.
And so I felt like I was doing some kind of magic spell that allowed
me to have access to culture that had otherwise disappeared.
I remember, being like in Eastern Europe and downloading a torrent of
House of Cards to watch like the season or second season or something like that,
that my God, like this was That's amazing.
This back in 2013 or something.
Yeah.
God, I meant strange days.
Not stranger things, but it's fine.
Katherine Bigelow.
Way better than those two weirdos.
Netflix, but yeah.
I remember freshman year of college I was downloading fan subs of the anime,
MOA magica in my dorm room every Sunday hungover before I went to the dining hall.
And I was just like, this to me, like I, and what was so cute is the
fan subs like left in one commercial every episode because they thought
the commercial was so funny.
It was for a drink called Morning Rescue and it would show like a sad office worker
exhausted and then rest, like emergency, like 9 1 1 firefighter people going
into the window singing morning rescue.
It was, it was just cute.
Like people did that, right?
Yeah.
Like a human being made that choice, I felt connected to those people.
I felt like I was participating in a special community by watching that show.
The internet is what made it possible.
And it was like a little transgressive too.
I'm stealing, Ooh, I'm a Biden pirate.
By the time I graduated from college though, and it had become
clear, the major corporations.
Understood what that optimism was and wanted this workforce that was
now really super jobless and around to buy in hook line and sinker to
what they were offering as employees.
So you got all these tech companies saying, we're gonna change the world.
And I, I did want to believe that companies like Uber and Lyft and Airbnb
and WeWork could affect the market in ways that made things more fair.
But as my cynicism with Obama grew, so did my cynicism with what
these corporations were saying.
I think it was around the time Lyft was offering loans for, it was Uber
offering loans for drivers to buy cars.
Where I was like, okay, so now you, you're, that just
sounds like script to me.
That sounds like you're, but you're buying, so at the company store, you're
relying on this company to buy a car for you on a loan that they finance for you,
and you have to pay that loan back with the wages you earn from driving that car.
Tell me how that makes sense.
And people were frustrat me.
And if I remember like
the interest rates were like ridiculous.
Yeah.
It, if I remember correctly as well, I remember like arguing with someone
my own age about this and being like, yes, it's good that these people have
access to transportation, but you have to understand like that, that now it
makes Lyft in charge of their whole life.
They might as well move to a company town.
And people were like, no, but they're, they're providing things for you.
You blah, blah blah.
Taxis are bad.
And in some places it's really difficult to get one.
And it's like, that is true.
And I do think some things about the hotel and taxi lobby needed to be
broken up, but it doesn't mean just handing control to another corporation.
There needs to be a diversified market if we wanna still
believe that capitalism works.
And this is when I started really doubting that capitalism worked.
I think it was becoming so invested in Silicon Valley and all the things
they said they could do for us.
And then seeing how they just consolidated money and power for themselves, where
I was really just, I became a cynic.
I became pessimistic about all of these things.
And I became angry because they lied.
And there was no consequence That was like the scales had followed from my eyes.
I can no longer take anything Tech corporation says in good faith because
I look at the humble beginnings of something like Amazon as a bookstore,
and I see Jeff Bezos renting out of town for his stupid wedding now.
And like that's what they all wanna do.
Line go up until you're the richest man in the world.
Totally.
And it's fascinating to me to hear your story because I feel like it
mirrors so closely my own as well.
Obviously I love the early internet too.
I love going onto all these forums.
I love being able to rip music and Get movies and shows and
like all this kind of stuff, right?
And there was the piece of like the 2010s and seeing the discourse around AI and
stuff that, that really radicalized me.
And like, the kind of fully automated communism stuff of like how
it's going to destroy all the jobs, but then we can use the technology
to, to free us and blah blah blah.
And how it actually just meant like algorithm management
and more pressure on workers.
But like the piece that even kind of came before that was Uber really.
And and the gig economy.
Right.
And that was like, for me it was like.
No, this is like, this is like terrible and it's being sold
as like liberation and freedom.
And this is just crazy to me.
I was observing it, but then also reading the work of like, people
who did great analysis of this.
Hubert Horan of course, who is like,
one of the like original Uber critics who, who did this so well.
But yeah, it was just like, that was like a real turning point for me and a, and a
real moment of like, wake up to what is really going on here and like how this
industry works and the kind of extraction and control and whatnot
that is so that this whole industry is wrapped up in, and, and I'm sure
like, the Snowden revelations and stuff played into that as well.
It was like, 'cause there's so many discourses around
technology that are like, oh, it's so liberatory and blah, blah, blah.
And then you look at it and it's like, no, this is like private companies
building out a surveillance network that then the state can piggyback off of.
And we're supposed to act like the government is the bad guy, but the
tech companies are the good guys.
What, what is going on?
You know?
Yeah, exactly.
And it's also liberatory for whom, right?
Is it liberatory for the workers in Africa that have to look at extremely
triggering material all day long, in order to train these algorithms?
Is it liberatory for any nation in Africa where they p they mine the minerals that
are necessary for building computers And then these countries are not asked
to share in the profits whatsoever.
Is it liberatory for the small towns where these data centers are being built, where
there are water and errors being poisoned?
Who is it liberatory for?
Then you understand what class struggle is, right?
You understand there's workers and bosses and you're one or the other.
And there if you, I think being on the autism spectrum can help a little
bit here where it's just like, if you understand binary thinking in that
absolute if that, if you understand that nuance is there, but it doesn't matter.
Really, then you really see the entire world for what it is.
There is a small class of people that are at the top and they
want to change the world so that everything funnels towards them.
And we are their serfs.
We are in a fiefdom.
We live underneath them.
I will soon be introducing legislation, calling for a moratorium on the
construction of new data centers.
Now as a result, I've been called a Luddite anti-innovation, anti-progress
proin among many other things.
So why am I doing that?
Why am I calling for a moratorium on the construction of new data centers?
Bottom line, we are at the beginning of the most profound technological
revolution in world history.
That's the truth.
This is a revolution which will bring unimaginable changes to our world.
This is a revolution which will impact our economy with massive job displacement.
It will threaten our democratic institutions.
It will impact our emotional wellbeing and what it even means to be a human being.
It will impact how we educate and raise our kids.
It will impact the nature of warfare.
Something we are seeing, right now in Iran further and frighteningly some
very knowledgeable people, fear that, well, that what was once seen as science
fiction could soon become a reality, and that is that super intelligent I AI could
become smarter than human beings could become independent of human control.
And pose an existential threat to the entire human race.
In other words, human beings could actually lose control over the planet.
And in the midst of all of that, all of this transformative change,
what I have to tell you is that the United States Congress hasn't a clue,
not a clue as to how to respond to these revolutionary technologies
and protect the American people.
And it's not only not having a clue, they're out busy raising money all
day long from AI and their Super pacs, which is a whole other problem.
As many of the AI revolution is being pushed by the wealthiest
people in our country, including Elon Musk, Jeff Bezos, Larry Ellison, mark
Zuckerberg, Peter Thiel, and others.
All of these people are multi-billionaires, who, if they are
successful at AI, will become even richer and more powerful than they are today.
What I wanna do now is not tell you my fears regarding AI and robotics.
I want you to actually hear from them.
The billionaires who are pushing these technologies listen
carefully to what they are saying.
Elon Musk, wealthiest person alive, stated that quote, AI and
robots will replace all jobs.
All jobs working will be optional.
End of quote, Dario Amodei,
Amodei, the CEO of Anthropic predicted that quote, AI could displace half
of all entry level white collar jobs in the next one to five years.
And that quote, humanity is about to be handed almost unimaginable power.
And it is deeply unclear whether our social, political, and technological
systems possess the maturity to wield it.
End quote, that's Amodei.
According to Demis Hassabis, the head of Google DeepMind,
this is Google DeepMind.
The AI revolution will be 10 times bigger than the Industrial
revolution and 10 times faster.
Alright, you got that.
That means it will have a hundred times greater impact on society
than the industrial Revolution had.
Jeff Bezos, the fourth richest person in the world, has been pushing his
staff for years to think big and envision what it would take for
Amazon, which he owns to fully automate its operations and replace at least
600,000 warehouse workers with robots.
600,000 jobs gone.
Robots doing the work.
Bill Gates, also one of the wealthiest people on earth, predicted that humans
quote won't be needed for most things, end quote, such as manufacturing
products, delivering packages, or growing food over the next decade.
Due to artificial intelligence, Mustafa Suleyman, the CEO of Microsoft AI said
most white collar work, quote, will be fully automated by an AI when the
ne within the next 12 to 18 months.
End quote, Jim Foley, the CEO of Ford predicted that AI will eliminate,
quote, nearly half, literally half of all white college jobs in the US
End quote, within the next decade.
I want you to hear this one.
Larry Ellison, also one of the richest people on earth and a major
investor in ai, said that there will be an artificial intelligence powered
surveillance state where quote, citizens will be on their best behavior
because we're constantly recording and reporting everything that is going on.
Dr. Geoffrey Hinton considered to be the godfather of AI believes there is a quote,
10% to 20% chance for AI to wipe us out.
Mark Zuckerberg, the fifth richest person in the world, is building a
data center in the state of Louisiana, a data center that is the size of
Manhattan and will use three times the quantity of electricity that the entire
city of New Orleans uses every year.
Alright, now, for many years now, leading experts have called for regulation and
reasonable pauses to the development of artificial intelligence to ensure the
safety, the very safety of humanity.
Let's go back to our good friend, Elon Musk, he said back in
2018, quote, this is Elon Musk.
Mark my words.
AI is far more dangerous than nukes.
So why do we have no regulatory oversight?
This is insane.
End quote, Elon Musk, in March of 2023, over 1000 business leaders in the big
tech industry, prominent scientists.
AI researchers and academics co-signed an open letter entitled Pause Giant
AI Experiments and quote stating, we must ask ourselves, should we
let machines flood our information channels with propaganda and untruth?
Should we automate away all the jobs, including the fulfilling ones?
Should we develop non-human minds that might eventually outnumber
outsmart obsolete and replace us?
Should we risk control, loss of control of our civilization?
Should we risk loss of control of our civilization?
Such decisions must not be delegated to unelected tech leaders.
Therefore, we call on all AI labs to immediately pause for at least six months.
The training of AI systems more, more powerful than GPT-4.
This pause should be public and verifiable and include all key actors.
If such a pause cannot be enacted quickly, governments should step in and
institute a moratorium end of quote.
That is what some of the leaders in the AI industry have said, and
clearly where we are right now is that there has not been any pause.
There has been massive amounts of competition between one
company and the other, between the United States and China.
So bottom line is that, in my view, to protect our workers from losing their
jobs, to protect human beings from attacks on their mental health, to
protect our kids, to protect the safety.
Of human life.
Yeah, we need a moratorium on data centers.
We need to take a deep breath.
We need to make sure that AI and robotics work for all of us, not
just a handful of billionaires.
Thanks very much.
That's going to be it for today.
As always, keep the comments coming in.
You can record and rerecord a voice message by tapping
the link in the show notes.
You can reach us on signal at the handle Best of left zero one or
simply email me to j@bestofleft.com.
The additional sections of the show included clips from Confronting
Capitalism, Pitchfork Economics, your Undivided Attention sound side, the
Brian Lara Show on the media today explained Decoder Tech Won't Save us,
why America and Senator Bernie Sanders, further details are in the show notes.
Thanks everyone for listening.
Thanks to Dion and Aaron for their production work for the
show and co-starring in Solved.
Thanks to Amanda for all of her work behind the scenes, including
her co-starring Unsolved.
Thanks to our editors and thanks to those who already support the show by
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