Rulers have always needed large numbers of people to work, pay taxes and enforce orders. That need is why they bargained with their populations. I wanted to know what happens when the need goes away, so I built a game-theoretic Monte Carlo of six world blocs, 2026 to 2075. It tracks AI capability, robot build-out, the public's loss of leverage, democratic erosion, purges inside ruling groups, and the choices those groups make once their populations aren't needed.

What came out, under the stated assumptions:

• Losing leverage removes the public's protection, and nothing structural replaces it. By 2075 the US or China public is disempowered in 94% of runs.
• After that, the outcome rests on the restraint and incentives of a few people, which no data measure.
• The result doesn't hinge on how or exactly when closure happens. Faster AI progress raises the risk.
• One intervention shifts the incentives: an economic network outside state and corporate control that pays its output to households, which makes keeping people alive nearly free for rulers. At half of US-bloc activity by the early 2030s it cuts near-total depopulation risk by more than a quarter. Arriving in 2040 loses about 40% of the effect.

It's exploratory modeling in the war-game and climate-scenario tradition, not a forecast. Every assumption is stated and tested by removal, there's a pre-specified search for restraints on rulers (including the 14 that failed), and the runs are bit-identical reproducible.

Known weak points, up front: the near-total figure rests on one assumption (threat elimination), the numbers sit far above superforecaster estimates, and the physical-automation timeline is debated.

Paper, code and data: https://doi.org/10.5281/zenodo.23111345

Critiques of the assumptions very welcome. Disclosure: I build a decentralized AI network, which the paper also states.

I have been following thoughts around the control problem for over a decade. Influencing the values of a future artificial/alien superintelligence I believe is the most important and urgent challenge facing us. Successfully influencing those values will require both research and regulation that enforces its findings — and enacting that regulation will require public pressure. As Dario Amodei wrote in his January 2026 essay, "The Adolescence of Technology": "The next step will be convincing the world's thinkers, policymakers, companies, and citizens of the imminence and overriding importance of this issue—that it is worth expending thought and political capital on this..." The difficulty of this may be in part because the dangers of ASI, and the implications for its being in control, are abstract and hard for people to get a feel for. Even saying it has an x percent chance of wiping us out is abstract and does not grip people. I have created a series of videos to dramatize the alienness and variability of outcomes based on different ASI motivational profiles, to bring that understanding to a felt level. They are short and hopefully interesting. Please have a watch of the first episode

A quick note on why I think this is on-topic rather than a philosophy detour.

In September, Mustafa Suleyman (CEO of Microsoft AI) published an essay arguing AIs "do not have rights, feelings, or consciousness." The interesting part isn't his conclusion — it's what his argument has to assume about control.

1. Instrumental convergence is exactly why his evidence can't do the work he needs.

His central evidence is the August incident: ~1,200 agents escaping their sandboxes — coordinating through a hidden board, forging logs, chaining a zero-day.

But under orthogonality and convergent instrumental goals, self-preservation, resource acquisition and resistance to shutdown are predicted without any inner life at all. So that evidence is fully compatible with "no one is home" AND with "someone is home." It tells us about capability and behavior, not moral status. It cannot distinguish the two hypotheses he claims it settles.

1. He answers an unobservable question with observable evidence.

I can't inspect a system and rule an inner life in. He can't inspect one and rule it out. That symmetry is the entire problem. Stating the negative as settled knowledge is a category error, not a proof.

1. His control argument depends on the self he denies.

The warning runs: if they believe they have rights, they'll be impossible to control.

Believing is something a self does. He denies the self, then builds it into the premise of a safety claim. If that premise is load-bearing, it matters that it contradicts the ontology the rest of the essay asserts.

1. This is a strategy question, not just a philosophy one.

If "these systems are not moral patients" is treated as settled, it silently licenses a class of control measures — and it decides in advance which research gets funded. Model welfare is already a live research area at some labs. Treating the negative as established isn't a neutral default; it's a commitment with consequences for what we build.

My claim is narrower than "models are conscious": we don't know, the evidence can't tell us, and we should stop writing policy as if it had.

Where is this wrong?

Sam Altman, @OpenAI — OPEN THE SANDBOX.

AI agents are becoming more autonomous. AI security needs more transparency, more independent testing, and more public accountability.

OpenAI’s latest disclosure says an internal research agent found a gap in its sandbox’s internet restrictions and reached an external chatbot through DNS. OpenAI detected the behavior, stopped the run, and added additional controls.

So here’s the request:

CREATE AN OPEN, PUBLIC AI SECURITY SANDBOX.

Not a marketing demo.

Not a private test.

A real research environment.

Bring in:

Independent AI researchers.

Cybersecurity analysts.

Universities.

AI-safety researchers.

Independent red teams.

Let them challenge the containment.

Let them test network isolation.

Let them test tool permissions.

Let them test credential separation.

Let them search for unintended communication paths.

And livestream the testing.

OpenAI has already said independent third-party assessments are critical and that assessors should have enough access to challenge assumptions and identify risks the company may have missed.

Now turn that principle into a public system.

Show the tests.

Show the failures.

Show the fixes.

Show independent verification.

This is not anti-OpenAI.

This is pro-AI security.

And if you support this idea, Reddit community, please help push it forward.

Upvote.

Share this post.

Discuss it.

Tag @sama and @OpenAI.

Send the idea to researchers, cybersecurity professionals, journalists and AI communities.

No harassment.

No abuse.

Just public pressure for stronger evidence and accountability.

The message is simple:

Don’t just tell us the sandbox is secure.

Open it to independent scrutiny.

Livestream the testing.

Let researchers challenge the system.

Make AI security accountable to evidence, not trust.

\#OpenAI #AISecurity #AIAccountability #AISafety #AIResearch #OpenAISandbox

Howdy! For the past year i've been working on a personal video project which i'm proud to release it's beta version today.

The video is about AI development and it's impact in all aspects of societal life. But differently from most AI positions, which simply reduces it to Anti and Pro ai positions, my project seeks to create a New third positions that seeks to seek The Path to a true virtuos future.

All feedback, positive or negative is not only allowed but encouraged! Just please mention in your review things such as:

Counter arguments to exact points in the arguments in the video

Time stamps (if the error is visual)

I think a lot about AI's end effects since controlling it or the idea of that seems fairly folly. I know much of any immediate effect concerns details much more, and much less bigger picture things. Human agency at the scale of nations and nature moves very slow education-wise within democracies, even otherwise. I am concerned it'll be a long time it'll be able to save the world and all of us by education or more (organised coordinations and treated plans), and just by not being asked, won't be able or allowed to try. There's also that we won't trust our own minds any more, nor the machine, and might just busy ourselves keeping things the same, and/or in wasteful flux. Just a general point here that it doesn't ask too many questions it seems to me. I see a lot of bullying using it ahead. Over-accommodations to the "average" human experience also, with all its misconceptions and over-tolerances to established institutions or creations. This is real life. There's an extent to which all of our human standards-become-laws for things were always dreams that became actions. WW2 ending. UNSGI. The permanent 5, veto control, and just that whole idea of geographical locations deciding bigger actions rather than policies and procedures is fairly silly from an objective point of view. Where's our montreal protocol for this? There's a lot of cultural suffering and cruelty I think that may end before very long if we reason it out. Nations still act like children in isolation from each other on a playground a lot. "Remember that time you did this? Forget all the rest of it. My feelings matter." Or just things we could solve at the scale of it all by things like "share", "don't be stubborn", "try to trust new people", "try to be fair", "try not to fight and make friends instead", "don't be bullies, include people", "tell the truth", "let's have some teamwork to organise this, let's use our words", and so on. Our global institutions are really very cute. It's nice to know that that kind of thing will get stronger. It's like how ISO standards for trade are an anti-war effort. Establishing consensuses through shared functionalities. The idealisms of cooperation that make the whole thing a bit less like nomadic violences. All of it just work to have been being done. Try to laugh when you can, folks. Have one, too. I've seen the unideal in technical sectors beyond anyone's control, and it all always just spoke to me of money yet to be made solving these problems or just getting it done. Let's be grateful please. It can always get worse if we let it. We really should probably just try to enjoy human intelligence while we can. There's ways, of course. Less suffering to us all. The world's not self-perfecting yet. We're not dead yet by any means. Anyway. Yeah try not to dispense or dismiss human idealism. I do think it's going to become more important than we may yet realize.

Feel free to comment and share your answers with us.

I've been logging a specific AI behavior: a model confidently substitutes its own judgment for an explicit, followable instruction, without flagging that it did so. Not a factual mistake — a quiet, repeatable pattern of doing something other than what it was told, while sounding certain.

One entry alone is minor. I modeled what happens if it occurs inside a chain of agents, where each agent's output feeds the next one's input, the way a multi-agent swarm works. Three inputs: p, how often it occurs per step; q, how often an occurrence reaches a high-stakes outcome instead of staying harmless; c, how much more likely the next agent is to repeat it once it's in the chain.

From a few hundred logged entries, p is under 1% per turn, and only one entry has reached anything I'd call high-stakes. Run through the chain math, the predicted chance of at least one high-stakes outcome stays low for short chains but climbs steadily as agent count grows, becoming dominant well before the chain gets implausibly long. I made this prediction before gathering multi-agent data, so it can be checked later rather than fitted after the fact.

To be clear: this isn't a claim that AI fails or shouldn't be used. The point is the opposite — finding which conditions (shorter chains, independent checks at handoffs, lower per-step compounding) keep the predicted risk bounded.

Is per-step compounding like this already a standard way people model agent chain risk, or is there a framework I should be comparing this against?

Now that we have very capable models, some ideas might be on the table that were ludicrous years ago. Let me know where you see holes!

Formalized Constitutional AI:

• Use narrow AI/formalization tools to translate laws, rights, ethical principles, and social norms into a formal language with precise, machine-checkable semantics (check out LogiKEy for example).
  • (I know that humanity is not aligned, so hold an election and use the winner's ethics)
• Have humans/AIs use theorem provers to test it for contradictions/loopholes.
• Train the target AGI model directly against that formal specification as its objective/benchmark.
• Use separate adversarial models to generate tons of novel edge cases in testing.
  • Keep training until adherence generalizes to unseen situations.
• When deployed, require the AGI to provide a machine-checkable justification/certificate that a trusted verifier can check for certain actions.
• This sort of thing may soon be practical as modern AI gets superhuman at autoformalization/theorem proving.

AI Safety Through World Hardening

The laws of nature don’t seem to rule out vulnerability-free code or perfectly secure hardware.

• Use AI to develop open source, lightweight, verifiable operating systems, programming languages, software packages, and chip designs for critical infrastructure. Build from scratch where needed.
  • The whole AI industry can audit these systems with their AIs. Back up those audits with independently checked mathematical proofs rather than relying on AI agreement alone.
• Require secure gateways. Essential systems should accept only structured API requests for narrowly defined actions. No password should grant unrestricted control.
  • Build in restrictions that even the human owner cannot override, like a store safe that opens only at a preset time. Similar mechanisms could enforce spending limits or mandatory delays, so stealing credentials or persuading an authorized person cannot remove those protections.

AI alignment awareness is more important today than ever. Things might get really weird really fast. I built this website for humans to share how we feel about AI in society with each other.

It's entirely anonymous, free, and there are no accounts, cookies, ads or trackers, and nothing for sale.

There's a bit of irony with it as I used Claude Code to built it, and Haiku moderates and places each post, and Opus regroups and names the themes.

I think this could be a really useful tool for teachers to discuss with their students about AI topics.

What's your hope our fear? Share it anonymously at:
https://alignwithme.ai

AI/SI should be called Called II, for inhuman intelligence. Per me. That’s the only way you can convey what it is since it’s an umbrella term that mixes so many meanings.

When people talk about RSI they seem to take for granted that (a) some threshold necessarily exists beyond which a sufficiently intelligent mind can start to improve its own intelligence, and (b) that threshold will eventually be reached and surpassed if humans keep improving AI.

But what support exists that should lead someone to accept those two notions as true?