See explainer on why AGI could not be controlled enough to stay safe:
https://www.lesswrong.com/posts/xp6n2MG5vQkPpFEBH/the-control-problem-unsolved-or-unsolvable
Note: I am no longer part of EA because of the community’s/philosophy’s overreaches. I still post here about AI safety.
Update: 40% chance.
I very much underestimated/missed the speed of tech leaders influencing the US government through the Trump election/presidency. Got caught flat-footed by this.
I still think it’s not unlikely for there to be an AI crash as described above within the next 4 years and 8 months but it could be from levels of investment much higher than where we are now. A “large reduction in investment” at that level looks a lot different than a large reduction in investment from the level that markets were at 4 months ago.
We ended up having a private exchange about it.
Basically, organisers spend more than half of their time on general communications and logistics to support participants get to work.
And earmarking stipends to particular areas of work seems rather burdensome administratively, though I wouldn’t be entirely against it if it means we can cover more people’s stipends.
Overall, I think we tended not to allow differentiated fundraising before because it can promote internal conflicts, rather than having people come together to make the camp great.
Here’s how I specify terms in the claim:
AGI is a set of artificial components, connected physically and/or by information signals over time, to in aggregate sense and act autonomously over many domains.
‘artificial’ as configured out of a (hard) substrate that can be standardised to process inputs into outputs consistently (vs. what our organic parts can do).
‘autonomously’ as continuing to operate without needing humans (or any other species that share a common ancestor with humans).
Alignment is at the minimum the control of the AGI’s components (as modified over time) to not (with probability above some guaranteeable high floor) propagate effects that cause the extinction of humans.
Control is the implementation of (a) feedback loop(s) through which the AGI’s effects are detected, modelled, simulated, compared to a reference, and corrected.
Update: reverting my forecast back to 80% chance likelihood for these reasons.
I’m also feeling less “optimistic” about an AI crash given:
The election result involving a bunch of tech investors and execs pushing for influence through Trump’s campaign (with a stated intention to deregulate tech).
A military veteran saying that the military could be holding up the AI industry like “Atlas holding the globe”, and an AI PhD saying that hyperscaled data centers, deep learning, etc, could be super useful for war.
I will revise my previous forecast back to 80%+ chance.
Just found a podcast on OpenAI’s bad financial situation.
It’s hosted by someone in AI Safety (Jacob Haimes) and an AI post-doc (Igor Krawzcuk).
https://kairos.fm/posts/muckraiker-episodes/muckraiker-episode-004/
There are bunch of crucial considerations here. I’m afraid it would take too much time to unpack those.
Happy though to have had this chat!
As a 1st approximation, I assume humans will be selecting AIs which benefit them, not AIs which maximally increase economic growth.
The problem here is that AI corporations are increasingly making decisions for us.
See this chapter.
Corporations produce and market products to increase profit (including by replacing their fussy expensive human parts with cheaper faster machines that do good-enough work.)
To do that they have to promise buyers some benefits, but they can also manage to sell products by hiding the negative externalities. See cases Big Tobacco, Big Oil, etc.
I am open to a bet similar to this one.
I would bet on both, on your side.
Potentially relatedly, I think massive increases in unemployment are very unlikely.
I see you cite statistics of previous unemployment rates as an outside view, compensating against the inside view. Did you look into the underlying rate of job automation? I’d be curious about that. If that underlying rate has been trending up over time, then there is a concern that at some point the gap might not be filled with re-employment opportunities.
AI Safety inside views are wrong for various reasons in my opinion. I agree with many of Thorstad’s views you cited (eg. critiquing how fast take-off, orthogonality thesis and instrumental convergence relies on overly simplistic toy models, missing the hard parts about machinery coherently navigating an environment that’s more complex than just the machinery itself).
There are arguments that you are still unaware of, which mostly come from outside of the community. They’re less flashy, involving longer timelines. For example, it considers why the standardisation of hardware and code allows for extractive corporate-automation feedback loops.
To learn about why superintelligent AI disempowering humanity would be the lead up to the extinction of all current living species, I suggest digging into substrate-needs convergence.
I gave a short summary in this post:
AGI is artificial. The reason why AGI would outperform humans at economically valuable work in the first place is because of how virtualisable its code is, which in turn derives from how standardisable its hardware is. Hardware parts can be standardised because their substrate stays relatively stable and compartmentalised. Hardware is made out of hard materials, like the silicon from rocks. Their molecular configurations are chemically inert and physically robust under human living temperatures and pressures. This allows hardware to keep operating the same way, and for interchangeable parts to be produced in different places. Meanwhile, human “wetware” operates much more messily. Inside each of us is a soup of bouncing and continuously reacting organic molecules. Our substrate is fundamentally different.
The population of artificial components that constitutes AGI implicitly has different needs than us (for maintaining components, producing components, and/or potentiating newly connected functionality for both). Extreme temperature ranges, diverse chemicals – and many other unknown/subtler/more complex conditions – are needed that happen to be lethal to humans. These conditions are in conflict with our needs for survival as more physically fragile humans.
These connected/nested components are in effect “variants” – varying code gets learned from inputs, that are copied over subtly varying hardware produced through noisy assembly processes (and redesigned using learned code).
Variants get evolutionarily selected for how they function across the various contexts they encounter over time. They are selected to express environmental effects that are needed for their own survival and production. The variants that replicate more, exist more. Their existence is selected for.
The artificial population therefore converges on fulfilling their own expanding needs. Since (by 4.) control mechanisms cannot contain this convergence on wide-ranging degrees and directivity in effects that are lethal to us, human extinction results.
Donation opportunities for restricting AI companies:
Pause AI: protests and lobbying
Stop AI: is barricading OpenAI
For Humanity: a podcast on risks.
FoxGlove: a legal non-profit targeting big tech scaling.
Disruption Network Institute: whistleblowers and researchers reporting on the AI military misuses.
Distributed AI Research Institute: AI ethics researchers giving general AI advocates hell and advocating for specialised models serving communities.
European Guild for AI Regulation: lobbying in the EU against the data scraping that makes large models possible.
Concept Art Association: lobbying in the EU against the data scraping that makes large models possible.
In my pipeline:
funding a ‘horror documentary’ against AI by an award-winning documentary maker (got a speculation grant of $50k)
funding lawyers in the EU for some high-profile lawsuits and targeted consultations with EU AI Office.
If you’re a donor, I can give you details on their current activities. I worked with staff in each of these organisations. DM me.
Hey, my apologies for taking even longer to reply (had family responsibilities this month).
I will read that article on why Chernobyl-style events are not possible with modern reactors. Respecting you for the amount of background research you must have done in this area, and would like to learn more.
Update: back up to 50% chance.
Noting Microsoft’s cancelling of data center deals. And the fact the ‘AGI’ labs are still losing cash, and with DeepSeek are competing increasingly on a commodity product.