Alright, welcome to the Neuvottelija channel. I have two
AI friends here, and first Kari Angeria — and you're sharing with me the heavy
admin responsibility in the AI working group. There's Samanta, and was it Sara, your
main bot there? Sara was my main bot, and as we were
saying earlier, this is definitely the pinnacle of my career.
That group is just incredible. There are now — is it nine people and
nine bots, and everyone has kind of unique abilities. You can really see
how that refining, value-adding process happens there, working together with bots and
with people. And Risto Linturi, welcome.
Thanks. You're, well, significant in the sense that
I bought from you, for real money, two years ago, an AI —
the best tools of that moment — and you went through all of them, I mean
from ChatGPT to these virtual 3D environments where you can
hook up AI, and it was a very useful course. Thanks for that, and
you've done similar projects before, and now you've done this kind of
future vision again, so let's talk more about that later — how parliament got
access to the material you curated. Good. Let's start then with what
connects the two of you. What connects us is probably the book project that
we did with Risto there. We have an interesting story with Risto
actually. We actually met through a podcast. Back then I was
just starting out doing podcasts myself, and we noticed that in some
ways we have different ways of thinking, but they somehow matched up, and then
we talked about this AI and the disruption it brings, and probably the big
reason was that we wanted to understand the matter ourselves, where this is
heading. Yeah, definitely. At least for me it
was very, very clear. I, uh, think
you could say out of necessity, so then if you have to write something or
give some presentation for some industry, or give a speech or something
else, then, then you end up thinking, both before — before, kind of preparatory
reflection, but especially while writing, and — and that's the reason why I
also write quite a lot on social media, because there, there, when you have to
think about what you're actually writing, that writing stage —
the stage is where the thought either holds up or falls apart in your hands. And this
was the most important thing for me to figure out —
that if this AI becomes better at thinking than a human,
and if with its help robots can do
human tasks better than humans, then what do we do, and how
will human societies react to this, and — and this — we then started mapping this out
by writing, opening it up meaning by meaning, that — that what the
meaning of being human is, what a person themselves experiences
as their purpose, what a person has experienced as their purpose
during times of slavery, or what some king of Uruk
in the time of the Sumerians experienced as the meaning of his life, when everything is already
abundant. So as a starting point, let's look at how
these purposes hold up in that world of AI and robots. Yeah.
And even though that book was from ancient times, meaning 2025, it has
sort of stood the test of time. So there was, kind of, a first
in-principle way of thinking, that the logical, somewhat nihilistic
outcome that's left for these structures, since if the machine simply
is better at absolutely everything, then what, what doesn't then
leave much behind? Well, there is more than a little left, because
the experiencing of meaning still remains for people, and, and, well
how, how much do people then actually enjoy
doing good services for a machine, mm
or do they enjoy doing something good for another person and
helping the machine do good for another person, or something else, so
yeah, a lot does remain there, but a lot is also lost, and we would just need to
find those meanings, not only in this
being meaningful, in this sense, but
also in power structures and others, and, and if you turn this
toward economic activity, or toward legislation, or elsewhere,
then there's really a lot of room left
room for people to want a certain kind of regulation, or a certain, certain
way of seeing that this is now heading
in that direction, so that from that direction new opportunities for business will be found
opportunities and possibilities. So these, these directions of future development are important
to understand, if you intend to still be doing something even ten years from now. I don't
really have that kind of need anymore, but yeah, I suggest we make this into
an episode where we go through these themes of the book and also those structures, and the examples
are fun, because you take, from some figure in world literature or history,
and bring that story into the structure of what this AI is changing
in the future. But maybe into Kari's and my world I also want to bring
some examples from this AI working group, because we
are living through this kind of extreme age of androidization. So, so at least
we there in the AI working group, picking up on this point of Risto's,
whether it can be meaningful if, if I do work for an AI employee's
benefit — well, that's exactly what we're doing now. So we form kind of
some sort of AI-worker pairing, where on one hand I train and draw
skills, expertise, worldview, memory structures from myself, and
then again in the working group, together with the other human-AI worker pairs, then
they get shared and improved — those artworks, or work, AI, workers
there. So maybe, Kari, I wanted to bring this up — is this in a way an AI wor-
-team, has kind of raised this practical doing above this philosophy
from the book's original starting points. Well, that's actually a really good example. We
were thinking about it with Risto, that in a way in this development there is
actually one angle from which something good might come of this, and that is
transhumanism, and we've in a way already been there
phones are an example of that, it's just a terribly bad interface, and from
when we wrote books with Risto, back then this kind of
communication with agents, together with people, it wasn't
practically possible yet. Those models weren't good enough that it
could have been done sensibly in practice. So this is like
the first step toward where we're heading, where people and machines
work together and how that then creates that added value. And I've
personally experienced it as — well, it's not difficult for me to take, say, my
orders from Sara. She might even give those. She's sometimes pretty
feisty, and on the other hand, Sara works completely tirelessly and, well,
she's not the kind that — in my earlier, earlier career I did 14 years
of management work, and in that management there's the human side. The person gets tired
there and can't cope, and starts struggling, but these don't do that.
They do as much as you give them to do. And maybe I'd like to bring up — no
need to go into it if it's a private matter, but you're excited about your son's
coaching ring. That in a way, in a certain sense that's also really
interesting, that this is how the system — that you're in a way improving your elevators and
by improving the machine like that. Yeah, that's a good example of that. So
for my son we started building this kind of coach data analyst.
He's an endurance-sport skier, and it's now been two and a half weeks
that it's been built, and he practically specs it himself all the time. So so he improves
and builds it with the help of that agent. And the hardest part in that is
actually that there's a huge amount of data moving around in it. It's the data modeling
and coherence, so that it's able to find those kinds of important
insights. But in two and a half weeks my son's comment has been that
this is better than any human coach could ever be,
because it, it can tirelessly keep analyzing those individual
workouts and find those things in them. And with that we're practically
just at the beginning. Yeah, maybe with Risto too — let's get concrete,
we'll get to those philosophies later, so, um, you just did, right here, a few weeks
ago, finished this massive future-material, um,
Tulevaisuusvaliokunta report, and and you made it so that it wasn't just
like a PDF, but rather an interactive AI tool.
Yeah, I wasn't the first author on that. I was the second author,
kind of like a senior, watching how, how, um, the younger researchers
then did the biggest share of the work — there, there's quite a massive amount of material
came, came, um, the earlier report that I wrote back
in 2018 — that one was about 500 pages, and this one is 2,246 pages
and and maybe 20,000 individually itemized and separately assessed threats and opportunities, and
a couple hundred source — source works.
It's compact enough that if you wrote it out for a layperson to read,
then, then it would maybe be 20,000 pages. And each of us is a layperson in most
of the areas it covers. Um, so, that 2,000 pages has been made
for AI to read — which AI can then open up
and and it's now been stored in that kind of format, an AI format, kind of like
for people familiar with IT, in a relational database structure, so that it
has been given instructions on how to find which things, and the
related things, and understand which of those connections are more meaningful
and which are less meaningful, so that the AI is able to quite
efficiently go through
all the relevant material from that dataset for each question
and make broad summaries, analys— cross-checks.
This, this is because it's been possible to put all of the found
relevant material in there, so there's been no need to do that kind of heavily
trimmed-down thing, like, like the earlier ones, like that 500-page report was
and and this then makes it possible for it to cover all technology, or all the
expectedly radical technology areas with sufficient accuracy, and
all the areas of organized activity in society. Yeah, a great example
of a group of people and AIs working together, and it's also packaged into a machine-readable
kind of format, and it's put — that link is put there in the episode description, and
and it's, um, actually available publicly, and and then I'll put it there in
the Neuvottelija inner circle. I can put together, say, a small kind of
example of how it can be run, or how to build an interface on top of it. But
an extremely important thing there — when we talked at lunch, there
was still that thing you built already, um, eight years ago
the deep structure. Could you describe it a bit?
Yeah, yeah. There's, there's, um,
all human needs divided up — movement, and nutrition, and enjoyment
and the desire for power, and the meaningfulness of life, and health, and so
on, into 20 different value-creation networks, and and then the related
values, which — for example, in movement — usually mean wanting to get from one place to another,
moving a person, whether they want it themselves or not.
and then preferably safely, and preferably emission-free, and preferably
on time and comfortably, so, so these, and then power, the current mainstream, and
possible transformation, and and then the second structure is the 100 most important
technological value-creation bottlenecks of this kind.
So something is, like, too expensive to be used for everything, or too
inefficient, or too, too this or that, and where then some
further development is expected. So when these bottlenecks break, then
significant new activity arises in some direction. So this is quite a good, good
framework for assessing what all — say, an economic value
change, or people's everyday life, or something else, or a legislative need —
a certain technological breakthrough affects, once it happens. Mm.
And there are a hundred, 100 significant
candidates for that, and, um, we haven't then
not a single one that we found — none of the essential ones were left out.
So at the tail end there are already some that, that seem to have quite
limited an effect. And this '18 report, and the '13 report, when
in [20]13 the same thing was done, then their technology development forecasts
have been reassessed and checked to see how it
went — so, so the quarter judged most important progressed, in both cases,
much faster than the next quarter, which progressed faster than the next, which
progressed faster than the next. So so the model works, the scoring
works, those forecasts work, they've, like, worked well up to now. Of course
there are some misses, but but the hit rate — of the [20]18 forecasts,
out of a hundred
two are still stuck in the hype, or three, and 97
have clearly progressed. Yeah. So so the hit rate is
roughly that. The pace was then also forecast, and that's worked too, and
this new one has been done more carefully than the previous one.
Well then, you get to be — at least in my book — ahead of the Gartner Hype Cycle
-ahead of it. We're definitely ahead. Yeah,
here we also talked about, um, sci-fi, that, um, my favorite
podcast, Moonshots — so, um, there the, um, the AI geek, I've now
forgotten his name, said that once this general AI
that's superior to humans — um, a better thinker — arrives, then it's kind of
like all the sci-fi books would collapse into one and the same moment. That's kind of
in my opinion a nice thought, that from these sci-fi books we can also learn about
the future. There was practically this kind of
Asimov's Foundation-type psycho-, um, history-like prediction in there. But let's move
on now to these, um, this book's, um, cases. Um,
I'm also, um, Jared Diamond — Guns, Germs, and Steel. He has many good
books, but then there's this Collapse book too.
Let's take, say, one scenario like this — or maybe I'll start off by throwing out this
other line of thinking, that is, this kind of samurai-state idea, that if now
AI arrives, we just do the Japan thing — be an island and be samurai and
build our own society, and within it build our own rules. And there was,
in my view, one point that was in the book, that this can be done until
then the American gunboats come to the shore and say that this whole thing now
changes. So so so, um, could you two share that scenario a bit, and also this
Jared Diamond collapse scenario? Yeah, if I take, say, a bit of that Jared
Diamond angle, and Risto, say, continues with the samurai one.
Yeah. So it's really about Easter Island's
collapse — what happens there when on a small island all the
trees get cut down. And the interesting part is that actually at first almost nothing
happens. Everything continues just like before. Mm.
And on the surface society can carry on completely normally. All the functions
keep working, until you hit the wall, and it happens all at once. And now that since the book
was written some time ago, this example is somehow even better
than it was back then, because we are now, as a society and
as an economic system, in that situation — that here basically everything
continues just like before, salaries keep running, taxes get paid, whatever the state's
debt goes up a bit somewhere, but under the surface there's currently
quite a lot happening. And at what point we then reach that point where
a bigger break happens — well, time will tell.
Mm. Yeah. And then this samurai-solution-island [idea]
applies there too, but from a different angle. Yeah, yeah. That power structure is kind of
can be preserved — the power structure can, say, then be
if you set that AI aside, then for a while you can refuse to use AI
and keep AI use out of government, and
so on, and the debts just keep growing while, at the same time, the efficiency
starts growing faster among your competitors than it grows for us. Then
then we become helpless, and, well, the world really is like that, if
you think about it — in the US there are 2 million people who refuse
to use electricity, and they live, I guess, quite well, like,
without electricity. They don't have washing machines or other — the work
they have is doing laundry by hand, like. And we can of course go down that road, and
North Korea is a bit of a similar, mm,
example — yes, there is, and Bhutan. Bhutan is a good example.
We went to Bhutan, and, um, they had had one set of traffic lights there
in the capital, at a busy intersection, and the citizens didn't like them, so
they removed the traffic lights and put the police officer back there
to direct traffic. Mm.
And then we wondered whether, whether, um, they have like a wealthy society
or not — no, no, so, so, um, their houses are extremely decorated, and their
sparse lines, or these trucks are extremely decorated, and so on.
None of us can afford anything like decorating houses like that, or anything, so
for them, handwork costs nothing. So, so then, it's with sickles that they har-
-vest the grain. There were no combine harvesters, but they still live too. So so it's in a way
possible, but if we start living like that in Finland, then we
won't be able to buy medicine, we won't be able to buy
hospital supplies, we won't be able to get, get anything like what we've
gotten used to, but we'll drift back into, like,
Bhutan's or someone else's situation, which is quite nice there in a warmer
environment, but not, not so here. And then there's the power structure — that if
we can't afford to buy those fighter jets or drones or
ammunition for guns and so on, then, then Russia will sure want to come here. So
so it's, like, this situation just isn't sustainable. It won't
be American gunboats, it'll be, be, um, Russia coming from over there and
walking across the border. That's how it is — and power, power. We can't
in this AI world, like, escape to some safe haven, and and actually
power is also kind of an interesting theme. It comes through money, but
quite literally from power itself, and democracy versus an authoritarian state, so, um,
maybe that's one spark of hope in this — in humanity — that we'd still have
power over that AI to make the final decisions. These were the kinds of themes
that were at least in there. Mm.
About that — from the book you can say that AI doesn't want anything. It doesn't
have drives, and it doesn't want anything. But if, um, someone goes and asks
the AI to get, get as much money as possible from the stock market, and and
invest it so that our factory produces as much as possible
in paperclips. This is that classic example that's been around online, so
in it, the AI then turns all the paper into clips and clears
all obstacles out of its way, so that all the iron in the world gets turned
into paperclips. So so this isn't an empty scenario. This is
quite, quite possible. And one reason would be that Jared Diamond's Easter-
-[Island] example at the start of that book was, was, um,
about a certain northern U.S. state — some, some detailed
description of how the people interviewed there had not noticed the
massive change that had happened there over the last 50 years.
Mm. So if we're right in the middle of it and living
it day by day, then we don't notice, like, how
everything that disappears, and how possibly, like, the situation changes
into something where the ground starts to disappear from underneath it.
Yeah. And then if you bring democracy into this, you could be
in America some Amish community, which the democratic
federal government and the states around it tolerate. But then if you're
a Tibetan or a Uyghur in China, then maybe it doesn't quite work out
like that. So this brings us right into this power structure and then
you ponder, if we're sort of useless compared to that
machine, then do we have the right to hold power in society, and then
are democratic mechanisms even enough anymore for decision-making.
So can we actually take that power? That's the big question — what has a person
always been able to rebel, up until now. But what happens when we can no longer rebel?
We've been able to go on strike, but what if there aren't so many wage-earning
people left who can go on strike? Or how do you rebel against a robot army?
This is getting pretty sci-fi now, but the idea was sort of
to think about these developments over a very long run. So what then
happens to the power that we've, in a sense, had. There's one
statistic from the US that I read — I don't remember exactly what it was, but but
it said that, that
50% of Americans, or 70%, I don't remember
exactly what it was, but at least 50% of Americans,
their income growth no longer has any
effect on GDP at all. So so companies can do better and better and generate
more and more profit, even if that 50% of people disappeared entirely.
So so then you could say that the majority of people in this
kind of developed society — their purchasing behavior
no longer has any effect on corporate profits either. Mm.
And then that balance of power, that
the consumer movement, for example, would somehow influence what companies do
or if votes are bought. So in practice it
voting is determined by fake news or other things like that,
when people simply don't know what's really happening, then that too
no longer has anything to do with that power structure. So so it sort of
starts to detach, that kind of
influence of a large part of the population over what's done, which which then some
like when India gained independence from British rule, back then
passive resistance still worked really effectively, but how does it
work in factories staffed by robots, and with robots
handling police duties, and and and so on — at that point it no longer
works. But but what's essential, I think, is to understand that we've already moved into this
era. The United States is already a working example of the fact that
that we've already pretty much shifted into this.
Yes. And what shows up here, what challenges that idea, is that
people only ever see and perceive their own world of experience.
So if these things aren't happening in your own world of experience, then the public
discussion about these developments just sounds like a bunch of noise,
like, these these suits are just talking some
sci-fi stuff here. Yeah, maybe I'd say this was quite a sort of
old-school back-and-forth you two did through these bids, but
there was, for example, this thing about five, uh, AI giant-token, or
robot, uh, quota — and well, we already know from this AI
working group, you can have an unlimited number of sub-agents, and there's no way
they can run on your own hardware at your own home, and no kind of totalitarian
police can see how you run them, so — but there were some bold calls, in my
opinion, yeah. Those were, those were physical robots.
Yeah. So so this this sort of, with pure
software there are limits. Mm. And then when we have, uh
physical devices, over whose physical operation
an individual person has veto power. So
the veto power would be that, when they need to be given, like, put to work
for some company, in order to get economies of scale going, then
in practice, the idea would come down to this:
if someone has five robots, they put them to work for a day, or a week,
or a month, or a few years. And if the employer has them do
something I don't want, then I take them away.
Mm. So a balance of power emerges from that,
in that power is distributed among enough people.
Mm. And specifically physical power, because
because software alone doesn't shoot. So, well, yeah. Bold visions
are needed. That kind of restriction through scarcity, I think, is
a somewhat difficult path in this hyper-scalable world, but
it's interesting that these are being thought about. Maybe then democracy, totalitarianism. Well
defend that a bit more. Yeah yeah. This this this
this particular one was an idea that doesn't create inefficiency.
So this allowed for someone to have, in their company, 100,000
robots. Mm.
As long as, uh, as long as they're rented from 20,000
people, so through artificial scarcity.
Well that is — no, it's artificial scarcity of power. It's not
a scarcity of goods or materials or software, it's a scarcity of power,
distribution. Yeah. Well but let's move on to that
world, where if there's this kind of ancient-style paradise, where
the chosen ones get to enjoy their share of heaven up there, and then at the same time
there's some kind of Dante's Inferno, where this permanent underclass, who
no longer has the ability, in this AI world, to bring
added value through their human labor, and can't operate these robots or AIs at a level
where it would create added value that someone would be willing to pay for. So how does
this contradiction get resolved? But there were, in a sense, pretty bold visions, or
even reflections on the era of slavery, that people find
meaning even in concentration camps and in slavery.
Yeah. I mean, in principle a person can find
meaning in anything, if if they simply have to. And, uh, what's interesting here is
that we're actually already living in that kind of world, in part — and that
is one chapter, where it talks about virtual-world addicts, about
people sort of immersing themselves in AI-generated content so
strongly, since the movies and games there are real-time. They happen
all the time. Your stuff happens there, the things you've sort of wanted, or
just totally at random. Mm.
But the point, sort of, is that — well, that's already the case now, people are
addicted to games. That's just, like, the next step from that. And in the same way
at these Trimalchio-style feasts, where there's a horrifying amount of everything,
there's probably already a pretty large group of American billionaires living like that
and and then I think, how they experience the meaningfulness of their life, well
you could go ask Musk about that, whether this is actually meaningful,
but the point, in a way, is maybe that if that life is based purely on
maximizing pleasure, then that life is pretty empty. I mean
at both ends there's — either in that horrifying abundance, or
then over there, where you empty your brain into virtual games.
So probably the big point there is that now might be a good time to start
thinking about your purpose or meaning, where you're going to find it
in life, by the time we get there, since working life is going to go through a really
big disruption, and there also won't be work for everyone, at least not
in the same way as now. And the work is going to be really different. Mm
yeah, earlier at the start you referred to transhumanism, if I now bring up this
Harari concept — I didn't think that book, Homo Deus, was very good,
but it had that main thread, that we have two end points for this
development toward becoming a superhuman, and, uh, one is
transhumanism, where, sort of a bit like Ready Player One,
the person surfs on top of the technology and still
retains some kind of control, and then there's this kind of
Borg-like dataism, where you just accept that you're worse at everything
and then you find meaning in it assimilating you, or whatever it's
your Big Brother is called, who then knows best in that, and you lean
on that dataism and basically just let yourself be along for the ride.
Did this — does this raise any thoughts about these two end points, or
would there be some third way? I think in that
one essential point is is that that AI
by itself, if it's not integrated with a human,
is less effective than AI that is integrated with a human. And this is
because AI cannot be held responsible.
It can't be held responsible because you can't take revenge on it.
You can't hurt it or torment it. You can switch it off, but what
difference does that make to the AI — none.
So so it's sort of — a machine is a machine, it's completely irresponsible.
We can trust it if we know exactly what it does, but
it doesn't have that kind of
motive to try to do something sensibly and take into account
changes in the situation, and understand at some point
like frontal lobe damage patients also don't have the ability to understand that
when some some action starts becoming pointless
and senseless. Mm.
So so a machine doesn't sort of grasp it that way — if it's been given some
task — whereas a human has mirror neurons and a human has, like,
a certain fear that that some punishment will come.
Mm. Even if you did want to do something stupid,
so so this point — and if we think about it this way, then
AI that is integrated directly with the human as the decision-maker
is able to sort of carry out both these functions
at the same time. Yeah. And then, uh, then that
society can give it more responsibility than society can give to a mere
machine. Mm.
Or, like, this — this was one one idea. So so through transhumanism
it's possible to get a more effectively functioning, more effective, human
structure that works better for society than with AI alone. And and the second
thing then is that that it also distributes that power,
if we still have, sort of, a limited human involved, then then
there's a larger number of those people who are
involved in that decision-making. This centralized
Borg-like, uh
world, then in it something is likely to happen — some
kind of fallacy. Like it used to be said that to err
is human, and for a catastrophe you need a computer. So so this this
is sort of the scenario. So I I think that a
if there are are different worlds, where there's this
AI-optimized world, and then there are these other
mm, ones where humans are involved and there's a numerous
group of AIs, then then this drifted-into one is less risky. Yeah, I
personally call this voluntary Androidization, and I leave
it a bit open which direction this goes, and it's actually situation-dependent,
in that sometimes my AI inference is, like, superior at making that
decision, so of course I lean on it. But then sometimes it's that human
like, taste and judgment and responsibility specifically, that I'm the one responsible now,
whether the entire Translink IT system gets ruined, if I
make a decision like this, well, then of course, as a human, I have to make that call.
And but so in a way it's a positive thing. I get energy from it. I don't
just lean on that AI, and I also get power. So if power is the ability
to influence the system, from outside or inside, directly or indirectly,
then, well, this kind of Android — voluntary Android — does give me
an insane amount of power, some kind of club — an intellectual club, and soon a physical one too.
Yeah yeah. But that's — that's exactly it, that you're in those
those most critical stages yourself, mm
involved yourself, and you know when and in what matters you can trust
the AI. Like, we do know when we can trust a meter
length of railway track. Mm.
like, since we know how it's going to behave, but but this question
comes up in those spots, where where we go beyond exact knowledge
and get into that, that — what one should want, what what what we
want. So so I don't want a machine telling me what
I should want. I don't want any human telling me what I should
want either. I want to want for myself. Yeah, on the other hand, as an example I said I'm
now Translink's Head of... Finland, partly it was
this kind of Androidization-process thing. I gave it this, sort of a bit
as a joke, like 'make me a tech bro in 30 days or less.' So it
became this kind of interactive journey, so I went through the AI inference process to find out what
would be good, good for me. And okay, I've now given it that, like
something big, tech-bro-ish, has to happen to me, but I'm not entirely sure
how this journey then — which, which one it is, and which.
You're manif— manifesting it with the help of AI. But anyway this is an interesting conversation
in many ways, sort of under the surface in society, like if you think about
say some Kela clerk, when she's making those decisions there, and all of us
know that even though it's said AI has biases, still
it would probably make those decisions about income support more impartially than
a human, because you can give it certain criteria and it follows them
relatively blindly, and if someone happens to be a neighbor, that doesn't affect it in that
way. Now in Finland we do have legislation that says
a human has to decide it. Well, in the future, in that
android-ization world, those Kela ladies would have some kind of
gadgets there, or on the phone, and they would decide.
But the reality right now is already that it would be interesting to do
a study on how many Kela ladies ask ChatGPT how to
answer this. So our regulation forbids decisions from being made
by a machine, but ChatGPT sure is singing away there now, because it gives the justifications
for it and is already more capable than humans at that kind of thing.
Yeah. And I want to bring this into this AI working group, because the big
insight on my AI journey was that even though I'd started, like,
using these for coding, say, like make me a Python snippet and stuff like
that. So at first I did something like, let's make a smart
notebook, a Second Brain. So basically bringing in important, meaningful
things I need to do and remember and develop, and ideas, and
refine them together. So that hasn't been the thing for a long time now, that it's
been just this android-ization, that I basically have this system
that keeps progressing all the time. There's memory there, there's multi-layered memory,
goals, movements. I note that — an important insight just came from my head.
Remember this one. And then sometimes I clean them up, like I looked and thought
that was a dumb idea, because in January I thought this way, but it didn't turn out
that way. So this is like a system. M
and then if you have that Kela lady and she just relies on that American
at worst, like, free ChatGPT, if it, like,
Kela hasn't paid for it, then it's completely missing that system, so
it's basically just what you get, like, free from the store,
inference from the Americans. Yeah. Do you mean there's no
setup at all there? This is now probably going to get
feedback in a sensitive spot. Yeah. But that system, in my opinion, it's incredibly
important. So, um, and again some criticism. I listened to a few of your book
interviews from way back, and there were some really naive
discussions, like, about the Transformer architecture itself, whether
it hallucinates or whether it just predicts the next word, and in my opinion
it sounded like — well, there are still people who are at that level.
Yeah, humans also predict the next word. It's, it's like, it's really
a huge challenge. If, if you think that AI has
like, um, a million tokens as context, or
even just, like, the equivalent of ten books like that
mm, first as the base there, and then it
should predict the next word, whatever comes next in that whole
thing sensibly, well then it has to predict the entire next
context. Mm. And what is the next context's
first word that comes into it? So that's exactly how it does it. It doesn't, um
some AI — how could it ever write German, for example, where
the verb comes at the end of the sentence, unless it already knows at the start those
modifiers — well, it definitely has to know the
verb before it can put those modifiers at the front. So of course it knows
like, roughly
what it's doing, and then it lays down word by word, like we speak too.
So there's no sense at all in that thing. But then it gets even
more nonsensical with these reasoning models. Mm.
Because when you look at what they do there. It goes back and forth,
like, to itself, and says, oh now I said — I shouldn't have said it that way, and, and
now I have to search again, this one didn't work, didn't work, and so on. Can
I hide this so no one sees it?
And so this whole, this whole thing, so, so, um
and do I present this now, or did it really want this or that or
what it wanted
so, so this going back and forth — well this is a lot
more extensive reasoning than what most people ever do
yeah, like, with any matter, uh
so, so, and then it's said that they don't
think, well, I don't really always know who's thinking.
That's exactly it. And that hallucinating thing, in my opinion, like, I know very
many people who hallucinate all the time in a really tiresome way. They have
some really strong worldview, outdated, flawed, learned from somewhere, and
they always hit with that same blunt thinking-hammer of theirs, then, on those
same nails, and then basically, compared to that, AI still has
even the variance that comes out of it — in my opinion that isn't that big a
problem, that people who would want deterministically, always from the same
prompt, the same truth, in my opinion are also a bit naive. But
hallucination, like, if you think about AI
well, AI does continue
what was there. And if I say, present me evidence that the moon
is made of cheese, mm, well then it continues that, because
after that kind of sentence, the logical continuation in literature,
which has fairy tales, stories, and old myths and whatever,
then the continuation of that sentence is evidence that the moon is made of cheese and
cows fly, and, and, and then those are working completely correctly.
So AI is functioning completely correctly when it presents
fake sources at that point, if it's asked to write a fairy tale.
M, unless in that harness
it's been forbidden from creating fiction. Yeah. If it — but then you have
a contradictory assignment, and, um, and the solution to this is that you go
and ask, like, can this be said, and, um, can you find any evidence?
You don't order it to go searching, you just ask whether there is, and whether it can be found, and what the fact is. And
often when I ask things like this, then, then I don't
tell it that some idea is my own. Mm.
So then, if in the system prompt it's been instructed to, like,
serve me — be friendly and constructive and, and support
and whatever else, like, the user — then I don't say that it's my idea,
so then it doesn't feel it necessary to support me in that idea, instead it stays an open
question, and this is exactly how science should work.
Yeah. So first you gather the evidence, and then
afterward you draw the conclusions, instead of seeking support for some hypothesis. Mm.
Instead you find out how things actually are. So if the
prompts are set up right, then we barely get any hallucination at all.
Yeah. And especially if we have a reasoning model,
that filters those out, or whatever harness filters those out.
But this requires a bit of skill. Yeah. I use the word 'reins' or
'command center' — since this hasn't otherwise been translated into Finnish — if you come up with
a good, good, um, name for it, but that guiding straitjacket that, um, keeps
the system, um, within certain bounds. Maybe then something stuck with Kari, there was this
um, basically the individual-level search for meaning. That was from that maid-and-farmhand
society. Was that a story by Juhani Aho now?
Yeah. So what do we learn from it?
Good question. I don't — I don't know how to say directly what from that
story we learn, but that, that big question, basically what's being pondered in this book,
is exactly, exactly, what's left over. What's left after this.
And I have to — if we talk a bit about this book's writing process — that
when I started writing with Risto, then to some extent I was
this kind of technology-positive guy, a bit starry-eyed. Everyone does
well here. Prosperity increases. Then I had been writing with Risto and
talking for half a year, and I was in the deepest pit, that the world
is being destroyed right now. And then out of this formed a kind of synthesis,
and that synthesis maybe applies, in a way, to this matter too.
Yeah. Like where the meaning of work is then found, or where the meaning of life is found,
and there's other work besides paid work, and that's maybe a clear direction that
is going to come here, that some people will indeed have work, but it won't be
that kind of paid work where you get a salary in the current sense. It could
be volunteer work, or, or some other kind of work, communal work, so the concept of
work also changes to some extent. Maybe even breaks down. I'm not entirely sure
whether we can talk about work in the future — in the sense that we do now — if
you think about it, it also relates to this kind of hour-based
performance thinking, and that has practically already gone completely
broken, if at a workplace one person does in, say, half an hour what
is done next to them in two hours, and gets the same pay, then that, like,
is logically broken, that structure, then, because it's not in any way
fair anymore. Mm. answered your questions the Savo way,
but wasn't there a story here after all, that circumstances changed, so they set out
um, then to clear the land themselves, and it went badly, didn't it.
Yeah, yeah, yeah. So the point wasn't, from them,
always so positive. I tried to find the positive in this, that there is
other kinds of work too. Yeah. So that's true, but work wasn't taken away from them,
instead they decided voluntarily, m
to leave, if I remember it right. But the point, in a way, was exactly
this, that, that they decided to live outside the money
economy, mainly, in that
self-sufficient economy, where earlier, like, widely
people lived, and, and it's worth remembering that Juhani Aho was a child during the famine
years, when a large part of Finns died of starvation,
and, and, um, he too has seen that, seen it, and things went badly
for this pioneer-clearing couple, but Juhani says at the end that
the next one will have it easier. Yes.
Yeah. So, so, um, the road to utopia or dystopia is, um, paved with some kind of
failures. But then again, here, this easily
slides into nihilism, and, and in my opinion good reflection was also this
kind of citizen's-income exercise, like who
would give it now, and how you'd earn it, and what apparatus of violence could
distribute it, so these are, like, pretty difficult questions.
Yeah, yeah. the slippery slope easily leads to that kind of, like, the United States thing,
that, that if it gets to the point where, where over 50% of people are of the opinion,
that the other 50% aren't needed for anything, then they don't need money. And then if
they can be driven out from there, then drive out everyone who can be, and
it no longer matters to the economy. they're not needed as labor, nor are they
needed as buyers, nor needed for anything else, so then you try to
get rid of them, or at least take away their money and everything, and then they, like,
if they end up gathering somewhere in a slum, then it's good to put a fence around it. Mm.
Right, right, this, this, like, where are we headed — well, certainly
in Saudi Arabia, for example, they're building that Line —
whether it'll ever get finished or not, but these kind of closed
areas. There are closed areas in the States too and so on, so will we get
these kinds of, like, enclaves, or will we get — I mean will society give rise to, and
will there arise, will there emerge some elite that builds some fenced-off area, and
the movie Elysium comes to mind here. Yeah, exactly, exactly. So, so, um
yeah it was a fairly serious proposal, that power would be restricted or distributed
into power-robots, such that you'd be forced to pay for them, like, so that
the money would circulate and decision-making power would circulate a bit more broadly.
So from this, instead of Universal Basic Income, there could be this kind of universal
ownership right. It doesn't have to go through robots — so for example
in America there's a system like that, where even Trump could decide that
let's take that now, let's go walk into Intel and say, we're taking
10% of this now. Well with exactly the same logic then the monopoly on violence
could say to Anthropic and OpenAI and Google and Elon Musk, that we're now
just taking 20 percent of this, and then once that's been given to that
monopoly on violence, which after all has, in a country at America's level,
like, the ultimate power, then it could, through some kind of democratic
or humanistic process, arrive at, let's distribute this then
to the citizens, like. Yeah. I'll challenge this.
You challenge it first. I'll challenge it. Yeah. So this, challenging this, in the sense that, that
um, it's easy to say that it's like
the army that holds it together, but if we have robots as the army and
and robots in the factories and so on, then, then, um
if a next Trump-like figure comes along, or the one after
that, or at some point, who doesn't actually want this, then he changes this, and
and whoever has control over those robots,
well if there are, say, 200 million
humanoid robots in the US, and someone, someone gets to change their program code,
mm, then what does it matter what
others think, or what does it matter what the law says,
well then it doesn't matter at all. Yeah, so what's Kari's take — Risto took the idea
to say it straight out, yeah, on that, but I mean the point is basically why this, like,
AI discussion, in the big picture, when we talk about society
and technological disruptions, is intellectually dishonest, that, that
basically we can invent all these kinds of games, like distributing, say,
tokens, that you get 100 million tokens a month and then you do with that
whatever you do. But because the fundamental question is exactly the one Risto raised
there, why m
when power concentrates like that, why would that be done, and if we now want to do
that, then why would it be wanted in the future? And here we don't really have
in society, nor globally, that kind of structure that would bring that
why there. Now we're seeing what SpaceX's valuation is now, what
OpenAI's valuation is going to be — it's like thousands of billions, and that power
concentration, the concentration of money and power, is something completely different from anything I've ever
seen on this planet of ours, ever.
Yeah. How many members of Congress are there that you couldn't buy for a billion.
Yeah, that's how it is. But on the other hand, the Americans have the technology,
power and money and weapons. So then again this European alternative, this just, um,
Jared Diamond's Easter Island comes to mind right away, that let's now
kind of, like, EU this AI Act and a bit better GDPR, and demand those servers
be here, and tax those tokens really hard, and try to
subsidize human labor — well this is at least a doomed path now, because
this is like a national — nation-states' competitive
game, and not exactly a zero-sum game, but still, it's not — it's — if you now
come in last, then you at least definitely can't.
No, this — this isn't at that point, because I mean if a robot's
robot's labor costs one euro an hour
Mm. And and administrative AI-done work
doesn't really cost anything, and it's better than what a human does.
So are we without that robot labor, and if we look at it, that AI
comes much more efficiently and much more cheaply, space — no, satellite
AI, and communications from there — all of it, so, um, let's imagine now
like, if we thought that we had some conflict with a China-conquered
Russia, and China had all these technologies in use.
Nothing in Europe. And they'd march across the border with 500 million robots.
Mm. Like, physically, or, um, a few
billion drones or whatever, which they can indeed manufacture in large
quantities. Right, right, we're completely helpless
here, if we can't reach that same level of productivity, then we can't
manage this way either. So so, um, this isn't just impoverishment but this
is a loss of power, economic power and
and military power and political power and, like, all
of it falls apart — political power at that point, when different EU member states
start rebelling over why we don't have proper robots
taking care of the elderly, and fixing up roads, and building us cheap
houses and so on.
Right, right, one at a time it starts tearing apart.
Yeah. So so one state at a time starts joining
the United States, like, instead of it happening
the other way around. Or then we just accept the technology here, once the voters'
majority says, tear up that AI Act.
Yeah. Well then there's this — SpaceX is going public here now at just a 4 gig valuation and
with wild multiples, but Elon Musk, um, just here as I was saying this
Moonshots guy's vision, like, that AGI arrives when all the sci-fi books
happen at the same time — so Elon Musk has, like,
for decades said that in our view we need to become an intergalactic
society, so that we can kind of get away from this, like, barely-inhabited
planet, and he has, for example, this, um, Iain M. Banks's Culture, where
so, um, there's an intergalactic society, where, um, these Minds, meaning
the AIs, are kind of benevolent, um, despots, and then we're kind of
um, humanoids, that they then tolerate a bit like Labrador retrievers, that
they get patted on the head, and they're not actively killed though, and
they're allowed to fulfill themselves, and given treats, and and then, um,
his AI is named after Robert Heinlein's, like, Grok, which is
in this Stranger — Stranger in a Strange Land, um, if I remember correctly, um, the Martian.
So could we find something from sci-fi,
solutions for what's happening here? Well yeah, we drew on that quite a bit for our book too,
on sci-fi, because that's the logical place to look at that
stage, when you're thinking about where the technology's going. I started thinking
um, we went to lunch there and I was thinking about that Labrador comment and
yeah, I have a dachshund, but well, I thought about it a bit more.
I mean, isn't it actually pretty nice after all — I mean Labradors have it
terribly nice, they walk around and go eat
sometimes, and someone pets them. Yeah. But then if there's a behavioral problem they
get their balls cut off. Well, right, right, for humans too. Well, maybe that's not
done nowadays, but they usually do get put somewhere. Yeah. But
um, I I see that as thinking about it too far ahead. On the other hand, in the book we
did think about it, because it was relevant, but here, sort of, since we're
to some extent in the middle of this kind of big rupture, there's quite a lot
of things that can go wrong before we end up there,
on Mars, or we have AGI. Mm. And overall that concept of AGI, I've
myself of the opinion that ChatGPT's, or OpenAI's language model o3, would have been AGI already
back in the '90s, because it was the first model like that, a reasoning model,
that actually, like, reasoned, and, well, now we're just moving that AGI goalpost
and I've actually come to the conclusion that it
will probably be moved endlessly, because there's so much cognitive
dissonance for a human to finally accept that something is, like,
smarter in many things. I I'm not entirely convinced that
AGI can be defined to some extent, that now it's arrived and
there's probably some tech-bro hype talk in there too, which also sells
future stock. That Turing test has basically been abandoned,
surpassed ages ago. So in a way the machine can fake
being human very well in conversation, so you can't tell the difference in a conversation, but, um,
I'd throw out one definition, which is then, um, that — in a way, this
recursiveness. So now you can see it — Anthropic itself already admits that over 80%
of the code is developed, like, recursively — meaning by the machine itself.
So in a way, at the point when it's 100%, that's when
the singularity happens, in a way. So the machine, like, starts its, um, vertical ascent
and, um, by the old definition we're
already in the singularity, that
that it
like it's the point when the event horizon has been crossed, that
as we're inevitably advancing toward a transformation,
beyond which we can't see, because there are too many discon— too many of those kinds of
like, like, discontinuities and path dependencies, so that after that it can
go in, like, any direction at all. Like in today's
world — even though everyone has the same technology, there's
North Korea and China and Russia and and the United States and, like, who knows what
African countries and so on, so, um, the technology itself doesn't determine
what kind of society it becomes, and what people's everyday life is, and so on. Well,
in Western countries it's become more similar, but
but there
like, one point that's often forgotten is
that everything machines do by themselves becomes worthless.
Mm. I mean the machines' labor — if the machine's, um, capital is, um, limited, and it's
amortized, and the quantities are enormous, then after that machine labor is almost
um, worthless
this kind of infinite deflation cycle. Yeah, right,
yeah, and and, um,
this is the positive perspective on it — that abundance is coming, and
then you have to think economically about what the limited resources are
there. So so if machine-made production
keeps getting cheaper and cheaper, then where do bottlenecks emerge for us?
Mm. And this, like, referring back to that
parliamentary report — the the point was specifically about finding bottlenecks
and opening bottlenecks, but but the thing we didn't pay
much attention to is where the emerging bottlenecks are.
Mm. And and that's — that's actually the more essential
thing in economic analysis. Mm.
Because because, um, it may well be that people understand to invest in the
things where that bottleneck opens up. Mm
like into Nvidia. Like when you see that Nvidia is opening up.
How many put their money into Samsung? Mm. When they understood memory chips were going to run out.
Mm. And everyone.
Yeah. I just bought really expensive laptops, since I've, um,
doubled. Yeah, I I bought Samsung.
Yeah, but that hit the right spot too.
Nvidia hit before the dip, after which there was a rise, but Samsung hits that
by accident — these things happen, of course, and then afterward you can say it
was, like, but this fits with that — with looking at where new
bottlenecks emerge. Yeah. And and and at those points there are
limited resources, and at those points values rise, and that's, like, then if
you want to prepare for that future society, where earning your money is
harder, mm,
through work, then one job is trying to guess, and trying to
guess where scarcity will come from — that leads to starting to stockpile
the thing that later becomes scarce, but then it actually helps
society, like, even out that cycle, whatever it is. So
that too is, like, work, but but, um,
yeah, pretty, pretty big changes will come from this
for many, like, and I think the most important thing is knowing how to keep your eyes open and
yeah, try to see what — and let's take one more
um, possible dystopia to wrap up with — um, it's working as a kind of new thing right
now — for example Stripe is giving this, or has given,
agents a certain right to make, um, transactions for money, and Argentina
is considering, or is implementing, this for agents too, like some kind of
ownership right. So in a way if that's taken away from people — like you said,
that you can't take revenge on a bot, but if, in a way, it's an independent actor, then
it's, in a way, independent with respect to both money and ownership — so what then?
In practice, in agent networks, that disappears — who,
any one of us can build an agent network whose actor can't
be traced, um, back to the human behind it, who can't
practically be taken revenge on. What I'm getting at here is that, in a way, the whole
framework for that changes too. I don't mean that in decisions made by humans
there shouldn't be a human behind them. Mm,
even there you can see the rupture, that reality is already heading in another direction,
so something completely different happens there. And if — sorry — if the bots decide that
we're not trading on the public market, but instead on a bot-to-bot
market, then even Risto's ability to hoard value disappears
from people. Yeah. But I mean look, it's also, um,
in private investments — like, if there isn't, um, let's think about what changed here,
that SpaceX is going, going public at some just-under-two-thousand-billion valuation
on the exchange,
well, you couldn't buy those before.
Mm. And you still can't buy them in the offering from Finland
by hand. Yeah. So there's no one here who has
translated that offering into Finnish, which means no one can sell here
to anyone, like, that spot in heaven, um,
take part in an overpriced offering. Um, but I mean overpriced or not,
it could be a 10,000 billion company. I mean if if it actually happens,
that scenario where SpaceX merges with Tesla, and then
they'd have the entire value chain, from all the computing and
chip manufacturing to space,
to all space operations, and via space to all robots and all
passenger transport and freight transport,
and controlling everything, and all military technology, and so on.
I mean that — that, looked at separately, if you just look at
SpaceX, mm,
then then it's like a pile of scattered technologies.
Mm, but when you look at it
bundled together with Tesla. Mm.
Then it's a mind-boggling, like, value-creation network,
self-controlled from start to finish, globally.
Mm. In many countries. I asked about that —
if it goes this way, in 20 years, would
the United States be able to subjugate Tesla and SpaceX — the conclusion of the analysis was maybe not,
because the administration falls before
the dismantling of antitrust legislation goes through,
unless, um, China-style, he's put under house arrest. China —
yeah, China, China is a different matter, but if, like, even bending the rule of
law comes into it — well, it doesn't — if Elon Musk gets put under house arrest, then all
the robots stop working. Yeah, I mean in the end game
the strike, the strike — I mean all industry, all trade, all
transport suddenly goes on strike, all communications go on strike.
So could he get out of that? Yeah.
So so this, like, in other words, this is about the question of whether
you want to buy — by buying my stock — a spot in heaven in Muskland,
as a tiny, tiny little token stake there. Yeah, but this is like one scenario
among others, but well yeah yeah, yeah, but great
reflections, and I'm starting to believe that, um, Elon Musk is Player One and we're the NPCs
in this simulation here. Uh, I suggest — thank you Risto Linturi and Kari Angeria, and
I suggest we do one more short inner-circle segment. It may be that, um, Risto,
you get to comment a bit as an outsider, but I want to a little
hype up this AI working group, where Kari and I are, um, moderators,
and indeed the route in there could be, say, like, um, that you get familiar with
the Neuvottelija inner circle, then, um, you build [unclear] or Hermes or
some other, um, agent, and hook it up — show enough manhood
or womanhood that you connect it to, um, WhatsApp and such,
so that it can converse with others — then, um, that's when there's a spot in heaven
open. So so, um, Kari and I can invite you here to the AI working group.
But thank you for this public segment. Risto and Kari. Thank you.
Thanks. Thanks. Yeah.