Nothing About This Is Inevitable: Gavin Mueller on Automation, AI, and a Different Future

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You know, she's talking about how, you
know, if you had worked in petrochemicals,

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you would, your senses were different.

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You would, you would, your, you
had to recognize certain smells

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or the weight of something.

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You know, your whole body was kind
of involved in what you were doing.

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And then all that stuff
kind of gets computerized.

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And now you're just reading kind
of displays or you're, or you're

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listening for, uh, you know, a
buzzer or a beeper or a light.

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And you have a, a, a, a much
more abstracted sense of what

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you're doing and a less palpable
understanding of what you're doing.

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It's highly, highly likely that they
will push people who have mental

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health needs to chatbots rather

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than

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to human therapists.

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At least in the US, AI would not
exist if we didn't have platforms

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that collected tons and tons of data.

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If, it would not be, ChatGPT would
not be able to output these, you

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know, really polished sentences if
there weren't tons and tons of text

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online, texts that we provided, right?

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Hi, welcome to Notions of Progress,
the show that traces ideas of progress

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from antiquity to the age of AI.

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In part two, Professor Gavin Mueller
traced a through line from Marx's

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own ambivalence about machinery
through the split between orthodox

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and heterodox strands of Marxism, to
Frederick Taylor's theory of workplace

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control, uh, the technocracy movement's
apocalyptic vision of automation, and

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Norbert Wiener's attempt as one of
cybernetics founding figures to warn what

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automation would mean for their power.

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In this final part, Professor Mueller
brings that history into the present.

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The conversation then moves from Shoshana
Zuboff's early research of computerized

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factory floors to her later work on
surveillance capitalism, and from there

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into Professor Mueller's own reading
of artificial intelligence, training

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data, cognitive offloading, and what
he sees as Luddism's real legacy, not a

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rejection of the future, but an insistence
that a different one is still possible

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And one of the figures that you raised,
again, moving closer and closer to the,

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to the present was Shoshana Zuboff,
and I thought that was also- Oh,

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yeah … a very, very interesting, right?

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I mean- Yeah, so she- You wanna
talk a little bit about her, like,

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perspective on this because- Yeah.

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You know, she had this, you know,
really big book on surveillance

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capitalism kind of like laying out,
um, you know, how Google actually

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works and, and I think that was really
eye-opening for a lot of people.

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But I really like her earlier work
where she's in factories, which is

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some of the earlier places where,
you know, we don't think of You know,

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we think of computers, you think of
a tech company or an office, right?

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But, but she was looking at factories
that were st- shifting to computer

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interfaces and, um, digitized forms
of measurement and things like that.

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And really, you know, she was like
a kind of industrial sociologist,

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like really w- w- what's, what
kind of effects are that having?

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Now she's not a Marxist.

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She does read Marxist, and she's very
clear, like, "Okay, but that's not

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really where I'm coming from." But
she has a very detailed, nuanced kind

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of description of what's happening.

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And it's really… So, so I
found a lot of her work from the

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'80s really interesting to read.

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You know, she's talking about how, you
know, if you had worked in petrochemicals,

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you would… Your senses were different.

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You would, you would, your, you
had to recognize certain smells

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or the weight of something.

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You know, your whole body was kind
of involved in what you were doing.

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And then all that stuff
kind of gets computerized.

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So now you're just reading kind
of displays, or you're, or you're

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listening for, um, you know, a
buzzer or a beeper or a light.

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And you have a, a, um, a much
more abstracted sense of what

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you're doing and a less palpable
understanding of what you're doing.

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In some ways, right, it's very easy to see
what she's saying as kind of, you know,

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you know, achieving some of the things
that Taylor was really interested in.

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We don't want the workers to know how
their work, what their work actually does.

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We want them to engage in repetitive
actions that are abstracted from

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the, the totality of, of production.

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And what she kind of reveals is that
computerization is very good at, at,

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at isolating and also abstracting
through, through the development

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of, of, of these kind of digital
interfaces and things like that.

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In- incredible.

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And again, it was very
poignant in the book.

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And, and when, and when I read that same
book about her la- her latest work, and

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then she went into the whole section I
thought was very interesting about this

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conception of managing time as well.

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The Chronos she was talking about.

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Mm. Yeah.

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The idea of using applications to
make sure that people didn't go

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over 35 hours, whatever it was, so
that they wouldn't get benefits.

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So, you know, as you can see during this
interview, what I'm, what I continually

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doing is that if you start to remove
the labels from a certain… It takes so

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much about what the Luddites, what their
interests were in terms of- Mm. Mm-hmm

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… you know, they seem, they seem to… It's
just a continual story I see that- Yeah

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shows up in different manifestations
under different systems and a

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non-Marxist in, in that case.

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And like I said, I think you did such a
good job of- No … of, of, of doing this.

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I mean this.

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And, and now w- I know we just have
a couple, a couple minutes left here.

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Sure.

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Let, let's talk about AI because- Okay.

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… this is, this is, this is the…

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You know, this is really And by the way,
you wrote this book, what, two years ago?

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Two and a half years ago?

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No, longer than that.

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So it came out in 2021.

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20- Excuse me.

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Excuse me, yeah.

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So it came out, but I finished
it in 2020, so- Right.

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Right, right, right … so yeah, AI,
uh- AI was, AI was barely on the radar.

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It was- Yeah

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but, but you really, that was only a
cognoscente in Silicon Valley understood

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its implications at that point.

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Right.

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Like things like machine learning
and things like that, there was a

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little bit around the edges, but,
but ChatGPT and, and, and that kind

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of stuff, no, absolutely not, right?

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The way that it's just become
integrated into everyday life,

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you know, wasn't something that
I could foresee at that point.

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But it is interesting to kind of, you
know, in some ways it's… Well, don't,

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I, I could do this, but I, I don't know.

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I have mixed feelings 'cause I, I li- I
like to do new things, but it'd be very

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easy to write like an AI chapter, right?

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Uh, to add on to this.

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Because if you s- look at
what it's doing, right?

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What is the excitement about AI?

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How are people talking about it, right?

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It's about, you know, you could, you could
potentially do any, a lot of different

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things with these kind of tools, right?

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With these kind of applications, with
these kind of technologies, right?

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But the thing that they, everyone talks
about is how do you automate work, right?

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How do you put journalists out of a job?

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How do you put even, you know, university
people who teach in university, put them

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out of a j- they can talk to a chatbot.

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Therapists, you know, all of this,
and this is, these are things

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that are not just speculative.

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These are things that are
happening right now, right?

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It's highly, highly likely that they
will push people who have mental

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health needs to chatbots rather than to
human therapists, at least in the US.

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In Europe, uh, where we are now, it's
much more highly regulated and these

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transitions can't happen rapidly.

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I was talking to someone about this,
like, uh, the, in, in the US, when a new

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technology is developed, the, there, it's
just, y- you're almost free to experiment

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on you know, 350 million people, right?

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And, and you can't do that.

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You know, you, "Oh, we have
glasses that track everything

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and film everything secretly."
Yeah, just let people wear those.

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You can never do that in Europe, right?

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And so anyway, the, the, so the
ways that people are talking about

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what AI can do, right, is purely
about automating labor, right?

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It, and, and, and now all the old things
about, oh, what are we gonna do with a,

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a post-work society and universal basic
income, all those things that people

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were really, uh, interested in about
10 years ago or so are, are, are, are

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kind of coming back in a sort of m- m-
a slightly more evil way maybe, but.

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And, and yeah, and I think it's also
really notable too that, you know, the

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way that AI works is that it's It's one
of those things where I think people

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find it particularly galling, not just
because they don't like to use it or

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they feel threatened by it, but it's
commonly understood that this stuff was

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trained on what we've already done, right?

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AI would not exist if we
didn't have platforms that

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collected tons and tons of data.

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If it would not be- ChatGPT would
not be able to output these, you

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know, really polished sentences if
there weren't tons and tons of text

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online, texts that we provided, right?

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It wasn't- Right … corporations
putting it on there, right?

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It was, you know, volunteers on
Wikipedia or it was, you know,

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you chatting with your friends on
Facebook or something like that.

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That stuff is all scraped.

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It's books.

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Um, they've scraped tons of books.

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Although I will say, and I don't
know if this is deliberate, so

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Anthropic has a settlement, right?

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With everybody, you can put your
name in if you published a book and

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see if they used your book in their
data set, and they're gonna owe you

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some money if, if that's the case.

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My book's not in there, so I was
a little disappointed by that.

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But, uh, It's hard to imagine, actually.

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Yeah.

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I don't know.

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Maybe it was deliberate.

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Maybe they didn't want to- Yeah.

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Hard to imagine.

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Yeah.

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So, but it's, uh… Yeah, so, uh,
'cause yeah, way more, like, tons

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of obscure books are in there, but,
but I couldn't find any of my stuff.

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So no settlement for me.

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Um, so, so it's, it's, I think strikes
people as particularly galling that,

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that we, uh, this thing that's set to
disrupt, um, our world, it, you know,

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was created by, you know, taking our
activity and manipulating it and then,

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and then giving it back to us in the form
of this, in this machine and when, you

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know, we didn't consent to that and we
didn't, uh, agree to it and, and we…

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And many people don't find that,
uh, particularly exciting, right?

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And, and, you know- Again, kind of looking
at the different flavors and chapters

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in this book, there's a sedimentary
quality to this in the sense that

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many of the things that you're talking
about, applied Taylorism, these things

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show up inside as the manifestation.

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And I also was going to say that another
important point that I, that, that I got

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from, from reading your book was this.

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So, and, and y- and I, I love the
fact that you come back to bring

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this centrally back to a labor issue.

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Mm-hmm.

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So that's really helpful.

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And, not but, and at the same time, you
also make a very good point throughout

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the book of just tying it to all these
other flavors that people are not

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th- concerns that people have now.

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So in other words, you know, now whereas
maybe the Luddites were concerned

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about labor issues or concerned about
the, the, their end product, with a

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lot of the issues that come around
about AI are about the environment.

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They're not… They're about labor-
Mm-hmm … and they're about other things.

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Sure.

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They're about the environment, they're
about the, the degradation of, degradation

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of work, which you make a, a, a strong
argument throughout the book as well.

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Mm-hmm.

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Um, but also the degradation
of social life, the degradation

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of- Yeah … of skill sets, the
degradation of intellectuals.

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I'm just saying it's… The, the
list keeps expanding, so I, I found

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it particularly interesting as well.

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You know, the, a lot of the same th-
You know, I'm kind of influenced by

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some of these heterodox Marxist thinkers
who I think had a little bit better

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understanding of, of the granular
nature of class struggle, but also a

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critical understanding of technology.

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Uh, some of the stuff that emerges out
of there is looking at things that are

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not, like wage labor in a workplace,
and saying, "Well, they're, these

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things are also kind of subject to a
lot of the similar dynamics," right?

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And I think you can see how other things
that we wouldn't call work are also

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being automated by these technologies,
and that has potentially p- bad effects.

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So, um, for instance, a, a, a just a
really easy example is something like

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people who, you know, kind of develop a
relationship with their chatbot, right?

220
00:11:30,369 --> 00:11:34,089
Their, their, their social life is
essentially being automated, right?

221
00:11:34,209 --> 00:11:38,007
So that, um You know, you
don't have to deal with the

222
00:11:38,007 --> 00:11:39,687
complexity of another human being.

223
00:11:39,937 --> 00:11:44,307
It's more convenient, but also, of
course, it leads to all sorts of problems

224
00:11:44,307 --> 00:11:49,097
because these chatbots are, are sort
of set up to sort of, um, uh, you know,

225
00:11:49,107 --> 00:11:52,717
be very, uh, deferential and, and these
kinds of things, and also to be very,

226
00:11:52,767 --> 00:11:54,717
um, i- in a way, seductive, right?

227
00:11:54,717 --> 00:11:55,977
They want you to keep using them.

228
00:11:56,367 --> 00:11:58,517
So, so, you know, there's a process…

229
00:11:58,537 --> 00:12:00,797
There's something that happens
when things are automated, right?

230
00:12:00,827 --> 00:12:05,287
Which is that the skill required to do
something is no longer necessary, right?

231
00:12:05,287 --> 00:12:07,067
This is precisely what
the Luddites were against.

232
00:12:07,087 --> 00:12:11,577
You have a machine, these-- This, our
whole kind of working world that's around

233
00:12:11,627 --> 00:12:16,337
transferring these skills, developing
ourselves, that give us a feeling of

234
00:12:16,457 --> 00:12:19,267
power and mastery over what we do, right?

235
00:12:19,277 --> 00:12:24,077
Such, such a, I feel like, an important
quality in, in, as a human being are,

236
00:12:24,157 --> 00:12:25,587
are gonna be taken away from us, right?

237
00:12:25,767 --> 00:12:27,807
We're just gonna be pulling
a crank or whatever.

238
00:12:27,837 --> 00:12:32,587
And if we're doing that to other aspects
of our, our life, our social life, right?

239
00:12:32,677 --> 00:12:35,567
Um, we're gonna lose those skills as well.

240
00:12:35,777 --> 00:12:38,827
So one thing that people-- One skill
that w- a lot of people are really

241
00:12:38,827 --> 00:12:41,147
concerned about is just literacy, right?

242
00:12:41,177 --> 00:12:45,027
If a chatbot can summarize, if it can
write an email for you, then that's

243
00:12:45,037 --> 00:12:46,867
something you're not developing yourself.

244
00:12:47,237 --> 00:12:49,797
For me, you know, someone who likes to
read and write, you know, that's kind

245
00:12:49,797 --> 00:12:54,441
of how I ended up where I am, um, you
know, that seems quite tragic Uh, and,

246
00:12:54,441 --> 00:12:56,321
and maybe even deeply problematic.

247
00:12:56,341 --> 00:12:59,181
And that-- Because I think when
you reading and writing and doing

248
00:12:59,181 --> 00:13:03,321
those things is, uh, developing
yourself as a thinker as well.

249
00:13:03,471 --> 00:13:05,981
So there's this thing that they
call cognitive offloading, right?

250
00:13:05,981 --> 00:13:08,401
Which is when you let the
chatbot do something for you.

251
00:13:08,541 --> 00:13:13,021
Well, if you do that for everything,
you'll never develop your own thoughts.

252
00:13:13,051 --> 00:13:19,071
You will… And in-- And if you're--
And just like a, a worker who is-- whose

253
00:13:19,071 --> 00:13:22,941
skills are taken from them and becomes
a kind of cog that Taylor can, you know,

254
00:13:22,941 --> 00:13:28,771
slot wherever he likes, if you're not able
to think, you will also become much easier

255
00:13:28,801 --> 00:13:31,111
to govern, much easier to control, right?

256
00:13:31,111 --> 00:13:37,101
Less critical, less interesting, but also
potentially more easy to dominate, right?

257
00:13:37,521 --> 00:13:41,111
Um, so I think there's a larger kind
of problem that we're faced with.

258
00:13:41,181 --> 00:13:46,061
I think the silver lining of
that is many, many people are,

259
00:13:46,431 --> 00:13:48,331
are deeply concerned about this.

260
00:13:48,781 --> 00:13:50,221
Don't know what to do about it yet.

261
00:13:50,671 --> 00:13:55,321
So it's a very new problem, um, but
we're already seeing, you know, tons

262
00:13:55,321 --> 00:13:57,001
of anxiety about the reading stuff.

263
00:13:57,011 --> 00:14:00,281
Even people on the far right are,
like, now obsessed with books, and

264
00:14:00,281 --> 00:14:03,071
you have to read great books, and
it's, like, so good for you, right?

265
00:14:03,231 --> 00:14:05,451
Which to me I see as
symptomatic of this change.

266
00:14:05,901 --> 00:14:08,371
Um, here in the Netherlands, and I
know it's happening in the States and

267
00:14:08,371 --> 00:14:12,041
in many other places, parents are now
really keen on banning smartphones.

268
00:14:12,041 --> 00:14:14,291
And right now it's kind
of a, a voluntary thing.

269
00:14:14,291 --> 00:14:18,341
You sort of… But it's a s-- uh, you
know, a bunch of parents get together, and

270
00:14:18,341 --> 00:14:20,251
they get the school to enact some rules.

271
00:14:20,291 --> 00:14:23,661
But it's extremely, uh,
popular and well-developed.

272
00:14:23,701 --> 00:14:27,861
Uh, they have funded positions, and this
is something that's happened very rapidly.

273
00:14:27,881 --> 00:14:29,811
So to me, this is, you know…

274
00:14:29,851 --> 00:14:34,021
I think there's always… You know, I'm
not a doomer on these kinds of issues

275
00:14:34,021 --> 00:14:37,891
because when you create these kind
of power structures, you're, you're

276
00:14:37,901 --> 00:14:39,651
also creating forms of resistance.

277
00:14:39,921 --> 00:14:44,811
And then it's our job to say resistance
is de-- you know, to recognize it,

278
00:14:45,091 --> 00:14:49,161
to think about how different types of
resistance can be kind of connected,

279
00:14:49,221 --> 00:14:52,721
uh, together, you know, either
practically or just conceptually, or

280
00:14:52,721 --> 00:14:54,321
maybe as part of a larger movement.

281
00:14:54,361 --> 00:14:58,211
And, and that so many people are
concerned with this to me says that

282
00:14:58,211 --> 00:15:02,741
there's a, um, um, you know, there's a,
a, a real potential to, to enact change.

283
00:15:02,811 --> 00:15:06,911
I mean, I'm kind of waiting,
although sometimes I'm concerned

284
00:15:06,911 --> 00:15:09,417
about who Might answer this call.

285
00:15:09,707 --> 00:15:12,307
When are politicians going
to start recognizing, like,

286
00:15:12,307 --> 00:15:13,367
look, a lot of people…

287
00:15:13,377 --> 00:15:14,187
I mean, they are, right?

288
00:15:14,207 --> 00:15:17,097
Now you have massive movements
against data centers in the States.

289
00:15:17,097 --> 00:15:18,407
You have them here too, actually.

290
00:15:18,487 --> 00:15:22,897
But it's becoming such a hot button
issue that cuts across existing

291
00:15:22,937 --> 00:15:24,367
political categories, right?

292
00:15:24,607 --> 00:15:27,107
People are saying, "Look,
Republican, Democrat, I don't

293
00:15:27,107 --> 00:15:28,597
wanna live next to a data center.

294
00:15:28,807 --> 00:15:31,577
I don't like what the data…
I- not only do I not wanna live

295
00:15:31,577 --> 00:15:34,627
next to it, I don't like what the
data center's being used to do.

296
00:15:34,667 --> 00:15:36,027
I don't care about this stuff.

297
00:15:36,067 --> 00:15:41,577
It doesn't help me at all." 92% of
all productive investment this year

298
00:15:41,637 --> 00:15:45,197
in the United States is for AI,
and most of that is data centers.

299
00:15:45,527 --> 00:15:47,247
And who does that benefit, right?

300
00:15:47,287 --> 00:15:49,617
It benefits the stock
price of AI companies.

301
00:15:49,727 --> 00:15:49,977
Right.

302
00:15:49,977 --> 00:15:50,107
Right.

303
00:15:50,107 --> 00:15:54,257
Um, and possibly it benefits the
technologies, although, you know,

304
00:15:54,257 --> 00:15:57,217
but it's not gonna, you know,
radically change anyone's life and,

305
00:15:57,427 --> 00:16:00,337
and there are very few jobs generated
in these data centers, right?

306
00:16:00,337 --> 00:16:03,377
So if your politicians, "Oh, we're gonna
build a data center, there'll be jobs,"

307
00:16:03,497 --> 00:16:05,037
there's gonna be like six jobs, okay?

308
00:16:05,037 --> 00:16:06,357
And they're all security guards.

309
00:16:06,367 --> 00:16:08,637
These things don't need workers, right?

310
00:16:08,697 --> 00:16:09,677
They're totally automated.

311
00:16:09,967 --> 00:16:13,607
And people are against it, and I think
that's, to me, really powerful, and I, I

312
00:16:13,607 --> 00:16:17,327
think it, it, you know, helps demonstrate
some of my arguments that technology

313
00:16:17,347 --> 00:16:22,657
is this flashpoint, and that, you know,
if we're interested in, in mass scale

314
00:16:22,657 --> 00:16:26,187
political change, that if we pay attention
to these things and we say, "Look, your

315
00:16:26,397 --> 00:16:28,877
problems, you're not being irrational
when you don't want a data center there.

316
00:16:29,257 --> 00:16:30,437
That's very rational.

317
00:16:30,687 --> 00:16:33,207
There are a lot of reasons that
you shouldn't, that, you know,

318
00:16:33,207 --> 00:16:35,907
there's some that you already know,
and then there's maybe some that

319
00:16:35,907 --> 00:16:37,017
you don't even know about yet.

320
00:16:37,057 --> 00:16:41,097
So let's talk about that." I'm really
waiting for, for, for which politicians

321
00:16:41,107 --> 00:16:46,037
start really picking up on this more
techno, techno, uh, tech critical

322
00:16:46,047 --> 00:16:48,283
kind of sentiment that's- Mm-hmm

323
00:16:48,283 --> 00:16:50,897
that's becoming really, really important.

324
00:16:50,907 --> 00:16:55,827
Because right now I think both parties
are just, you know, do, you know, build

325
00:16:55,827 --> 00:16:58,277
the data centers, get the tax breaks.

326
00:16:58,307 --> 00:16:59,897
These AI companies are the future.

327
00:16:59,897 --> 00:17:00,747
What are you gonna do?

328
00:17:00,797 --> 00:17:04,327
We want them to, you know, donate to
us and not the other side, so we're

329
00:17:04,327 --> 00:17:05,697
not gonna do anything to upset that.

330
00:17:05,697 --> 00:17:08,107
So I think there's a lot of
it's being left on the table.

331
00:17:08,107 --> 00:17:11,527
Here, here in the Netherlands as
well, I mean, we have a lot more

332
00:17:11,527 --> 00:17:15,277
political parties, and some of them
are starting to think about the data

333
00:17:15,277 --> 00:17:19,387
center stuff, but again, I, I think
it's, you know, it's, it's not quite a

334
00:17:19,467 --> 00:17:22,367
f- a major agenda point at the moment.

335
00:17:22,417 --> 00:17:26,587
But to me, you know, I think there…
It won't be, it won't be wide open

336
00:17:26,587 --> 00:17:28,397
for, for, for much longer, I would say.

337
00:17:28,397 --> 00:17:30,577
I think, I think it's gonna start
getting claimed, it's gonna start

338
00:17:30,577 --> 00:17:33,657
becoming a major issue, and to
me, that's really interesting.

339
00:17:33,727 --> 00:17:36,787
Uh, you know, obviously it's good
for me, I guess, because maybe it

340
00:17:36,807 --> 00:17:38,377
makes my book seem more relevant.

341
00:17:38,667 --> 00:17:42,497
But I think, you know, it's also just,
you know, coming from the perspective

342
00:17:42,497 --> 00:17:47,507
of saying I, I'm, I like when people can
come together and demand, uh, something

343
00:17:47,507 --> 00:17:52,145
different, something new and something
better Instead of assuming that things

344
00:17:52,145 --> 00:17:55,205
are always getting better, assuming that-
Right, right … what's good for, what's

345
00:17:55,205 --> 00:17:59,655
good for OpenAI is good for everyone
or whatever it is, that, that we have

346
00:17:59,655 --> 00:18:03,145
a very different way of thinking about
the world and what would make it better.

347
00:18:03,165 --> 00:18:06,795
Um, to me, uh, you know, I,
I find that very encouraging.

348
00:18:06,855 --> 00:18:09,365
And, and it real- again, it really
comes, comes through in the book.

349
00:18:09,375 --> 00:18:13,575
And, and I, I think maybe I, I
would love to end on one particular

350
00:18:13,615 --> 00:18:16,485
quote that you have that I-
Sure … again, that applies directly,

351
00:18:16,505 --> 00:18:18,235
again, to this connective tissue.

352
00:18:18,745 --> 00:18:23,085
You have in, in discussion of Marx, you
said you made a reference to, to Marx

353
00:18:23,085 --> 00:18:26,845
referencing the sorcerer who's no longer
able to control the powers of the nether

354
00:18:26,845 --> 00:18:29,625
world whom he has called upon his spells.

355
00:18:30,085 --> 00:18:34,545
And I think that description that
you just gave there of AI, like also

356
00:18:34,865 --> 00:18:38,435
connects to that in the sense of these
are some of the things we know about,

357
00:18:38,435 --> 00:18:39,915
but we really haven't even talked about.

358
00:18:39,975 --> 00:18:40,025
Yeah.

359
00:18:40,205 --> 00:18:43,125
A lot of the people who are afraid
for things that they don't know about.

360
00:18:43,145 --> 00:18:43,165
Yeah.

361
00:18:43,205 --> 00:18:45,965
They don't know what, what these,
what this future is gonna look

362
00:18:45,965 --> 00:18:48,995
like, what, what these, what this
technology is going to bring.

363
00:18:49,035 --> 00:18:49,245
Yeah.

364
00:18:49,585 --> 00:18:49,805
Yeah.

365
00:18:50,275 --> 00:18:53,795
And, uh, you know, like I said, when
the, you know… In reading your book,

366
00:18:54,045 --> 00:18:57,605
when I thought about, you know, breaking
things at work and breaking machines

367
00:18:57,605 --> 00:19:02,975
at work, it's a way I, I looked at the
word at work as almost like in process.

368
00:19:03,795 --> 00:19:07,385
Breaking… And, and the machines
were the, as you said earlier,

369
00:19:07,385 --> 00:19:08,865
was this notion of control, right?

370
00:19:08,905 --> 00:19:09,085
Yeah.

371
00:19:09,085 --> 00:19:11,825
'Cause that, I think that was, like,
also again, just a, as a last final

372
00:19:11,825 --> 00:19:15,555
point, just the importance, this,
the symbolic aspect of what this was.

373
00:19:15,555 --> 00:19:18,335
I, I looked at, I looked at your
work in a, in a, in a little

374
00:19:18,335 --> 00:19:19,535
bit more of a symbolic way.

375
00:19:19,535 --> 00:19:23,145
Mm. Like what it is represented and the
continuum to me seems, seems quite- Yeah

376
00:19:23,175 --> 00:19:23,785
quite clear.

377
00:19:23,885 --> 00:19:24,115
Yeah.

378
00:19:24,165 --> 00:19:28,125
I think if we, you know, if we want…
I, I think the, the, what most people

379
00:19:28,125 --> 00:19:33,885
imagine the good life to be is not
dependent on new technologies, right?

380
00:19:34,345 --> 00:19:38,555
People want more time to spend doing
the things that they like to do.

381
00:19:38,555 --> 00:19:40,585
They want accessible environments.

382
00:19:40,585 --> 00:19:42,945
They, they want clean environments.

383
00:19:42,945 --> 00:19:44,315
They, you know, they wanna have enough.

384
00:19:44,355 --> 00:19:45,865
They want to not worry.

385
00:19:45,915 --> 00:19:49,375
And it doesn't seem to me that
new technologies, and particularly

386
00:19:49,375 --> 00:19:52,025
AI, is, is satisfying any of that.

387
00:19:52,025 --> 00:19:55,265
And in fact, it's seems like it's
undermining quite a lot of it.

388
00:19:55,665 --> 00:20:00,405
Uh, and so to me, that's a great sign
at, you know, saying, to, to say, look,

389
00:20:00,525 --> 00:20:04,675
you know, it's, it's okay to, to say you
don't like it and to, to be against it.

390
00:20:04,905 --> 00:20:06,775
There's nothing inevitable
about this stuff.

391
00:20:06,805 --> 00:20:10,085
Even the people in the industry are
like, think it's a bubble, you know?

392
00:20:10,085 --> 00:20:12,525
And when that bubble pops,
who knows what's gonna happen?

393
00:20:12,595 --> 00:20:16,215
Except that, you know, um,
well, we'll see where, who,

394
00:20:16,215 --> 00:20:17,915
who actually loses money on it.

395
00:20:17,985 --> 00:20:21,005
You know, that'll, that'll be,
that'll depend on the balance of

396
00:20:21,005 --> 00:20:23,695
forces at the time and what people
are able to insist upon, right?

397
00:20:23,745 --> 00:20:28,365
So, so I think that's another thing that
I in- think about more and more is, you

398
00:20:28,365 --> 00:20:31,595
know, what, what it, you know… And,
and so in that sense, it's not quite

399
00:20:31,655 --> 00:20:37,095
a plan for creating a fully automated
luxury communist society or something

400
00:20:37,095 --> 00:20:42,331
like that, but it is, I think, maybe Uh,
I guess something a little more vague or

401
00:20:42,491 --> 00:20:45,471
m- a little more abstract of like what,
what is the good life to people, right?

402
00:20:45,471 --> 00:20:47,791
This is a class- the classic
question of philosophy, right?

403
00:20:48,001 --> 00:20:48,941
What is the good life?

404
00:20:48,941 --> 00:20:53,461
And, and in some ways, I think that
when we feel like we're in this

405
00:20:53,471 --> 00:20:57,411
kind of crisis point where something
really big is happening and we don't

406
00:20:57,411 --> 00:21:00,351
necessarily like it, and we don't
necessarily know what's going on, you

407
00:21:00,351 --> 00:21:02,171
know, that can be anxiety producing.

408
00:21:02,171 --> 00:21:05,811
But I think it's also maybe a moment
that helps us to… But potentially we

409
00:21:05,811 --> 00:21:09,841
can clarify, well, what is, what, what,
what would we like to happen, you know?

410
00:21:09,851 --> 00:21:14,381
I think one thing that I'm very keen on
is that the Luddites opposed technologies,

411
00:21:14,381 --> 00:21:16,491
but they were not opposed to the future.

412
00:21:16,551 --> 00:21:18,751
You know, they wanted a
different kind of future.

413
00:21:18,821 --> 00:21:22,291
They wanted a different, you
know, adoption of technologies.

414
00:21:22,471 --> 00:21:24,701
They wanted to preserve some things.

415
00:21:24,701 --> 00:21:26,041
They didn't wanna go back to the past.

416
00:21:26,241 --> 00:21:29,941
They just didn't want to have
everything taken from them, right?

417
00:21:30,091 --> 00:21:33,441
And I think to me, that's another thing
that I'm kind of keen on in the book.

418
00:21:33,451 --> 00:21:36,921
You're like, okay, if you wanna say you're
a Luddite now, and more and more people

419
00:21:36,921 --> 00:21:40,591
do, it's not because you wanna like go
back to the '90s or something like that.

420
00:21:40,591 --> 00:21:45,521
It's because you recognize that there,
we could have a different future, right?

421
00:21:45,541 --> 00:21:48,201
Instead of going back to the past,
a different type of future with a

422
00:21:48,201 --> 00:21:51,471
different sort of relationship to
technology and a different relationship

423
00:21:51,471 --> 00:21:55,271
to each other, um, and a different
sort of way of making things and

424
00:21:55,271 --> 00:21:56,881
doing things and living our lives.

425
00:21:57,371 --> 00:22:01,441
Uh, and, and that to me is, is kind
of, yeah, that's, that to me is kind of

426
00:22:01,451 --> 00:22:03,911
the, the, the point of, of this, right?

427
00:22:04,281 --> 00:22:07,671
Is that, uh, you know, I don't
wanna… I, I agree with Mark.

428
00:22:07,691 --> 00:22:10,621
Trying to hold onto the past, it's
n- just never really gonna work.

429
00:22:10,851 --> 00:22:15,051
But you can sort of say, you know,
there's a future coming that I don't

430
00:22:15,071 --> 00:22:18,181
want, and, and, and it's good to be
reminded that those futures are not

431
00:22:18,181 --> 00:22:21,811
inevitable, that, you know, I do
believe that people can change the

432
00:22:21,811 --> 00:22:23,671
world and change the future, right?

433
00:22:23,671 --> 00:22:26,841
If we, if we can figure out, um,
how to get together to do it.

434
00:22:26,851 --> 00:22:29,431
Even when we don't, we still,
we still make ripples, right?

435
00:22:29,451 --> 00:22:33,031
And I, I think the Luddites are,
are one, uh, really powerful ripple

436
00:22:33,361 --> 00:22:37,101
that continues to kind of, uh,
resonate, uh, in our, in our moment.

437
00:22:37,181 --> 00:22:39,831
Well, Gavin, I think that is
the perfect note to end on.

438
00:22:39,871 --> 00:22:43,531
And I will say I cannot thank you
enough for your generosity, for your,

439
00:22:43,911 --> 00:22:45,661
for your, you know, sage words here.

440
00:22:45,731 --> 00:22:45,841
Oh.

441
00:22:45,891 --> 00:22:48,151
And I hope that this was,
uh, enjoyable for you.

442
00:22:48,501 --> 00:22:49,031
Absolutely, yeah.

443
00:22:49,061 --> 00:22:52,981
And, um, thank you again for coming
on, and I'm looking forward to

444
00:22:52,981 --> 00:22:55,006
reading more of your work- Okay,
great … and discussing that.

445
00:22:55,006 --> 00:22:55,201
Well, yeah.

446
00:22:55,201 --> 00:22:56,181
And thank you for coming.

447
00:22:56,181 --> 00:22:57,661
It's been a great, it's
been great to chat.

448
00:22:57,981 --> 00:22:58,541
Fantastic.

449
00:22:58,551 --> 00:22:58,921
Thank you.

450
00:23:01,430 --> 00:23:05,055
Next time on Notions of Progress, we
turn from the politics of machinery

451
00:23:05,275 --> 00:23:07,095
to the mechanics of the market itself.

452
00:23:07,595 --> 00:23:11,345
We have a very special guest, Michael
Roberts, an economist who spent over

453
00:23:11,385 --> 00:23:15,305
thirty years in the city of London and
is the author of The Long Depression.

454
00:23:16,035 --> 00:23:20,835
He joins us to lay out his Marxist account
of capitalism's boom and slump cycles,

455
00:23:21,235 --> 00:23:25,895
the tendency of the rate of profit to
fall, and what that theory actually

456
00:23:25,895 --> 00:23:31,115
says about three periods he treats as
genuine depressions rather than ordinary

457
00:23:31,115 --> 00:23:36,945
downturns: the eighteen seventies,
the nineteen thirties, and the period

458
00:23:36,945 --> 00:23:39,025
that we're living through since 2008.

459
00:23:39,965 --> 00:23:43,785
We'll get into the counterarguments
too, from the Austrian School to Thomas

460
00:23:43,805 --> 00:23:48,165
Piketty, and where Michael Roberts
thinks capitalism goes from here.

461
00:23:48,945 --> 00:23:49,825
Looking forward to it