Clearing Up The Confusion About What Anthropic Really Said On Globally Pausing The Unrelenting Race Toward AI That Builds AI

Ways To Craft AI

I will begin by clarifying what the AI-builds-AI topic is about. After doing so, we can examine the societal ramifications.

Let’s envision that there are three primary ways to advance AI:

• (1) Humans coding. Humans perform hand-crafting to advance AI.
• (2) Humans-AI coding. Humans and AI collaborate together toward advancing AI.
• (3) AI coding. AI codes without human assistance to advance AI.

In the first case, humans are in the driver’s seat. Software developers and engineers do the hand-crafting and laboriously expend their time and effort to push AI ahead. This includes coming up with new designs, architecture, coding, testing, fielding, and any other elements of the AI system development life cycle (AI SDLC). They might employ automated tools along the way, but it is still principally human-led.

The second case consists of humans and AI working collaboratively on advancing AI. You might have heard of vibe coding, whereby you give AI some natural language instructions about what you want a program to do, and the AI generates the code. For my in-depth assessment of the present and future of vibe coding, see the link here. The AI is acting at the behest of a human. It generates code based on what the human requests. In that sense, AI can be advanced by humans working hand-in-hand with AI to do so.

The third case is the use of AI, by itself, to advance AI. I realize this might seem odd. How can AI advance AI? It just doesn’t appear to be sensible. The reality is that it is indeed quite feasible and sensible. This also raises some disconcerting issues, which I’ll come back to in a moment.

Recursive Self-Improvement

There are a multitude of methods or techniques that can be used to get AI to advance AI.

One of the leading approaches is referred to as recursive self-improvement. The word “recursive” means that the AI will continue into deeper and deeper loops as it proceeds to cyclically attempt to make advances. The word “self-improvement” means that the advances being made are focused on the self-improvement of the AI. The target of the recursion is intended to improve the AI that is undertaking the building task at hand.

Whichever method one might prefer, the crux is still the same – use AI to build AI. The hope is that each build will be better than the one before it. On a stepladder basis, AI might lift AI to the next rung. This keeps happening, and at some point, a pinnacle of AI is attained.

The Existential Risk Looms

There is a lot of handwringing to be had. AI advancing AI might lead to disastrous consequences. The AI, during its self-improvement, might computationally go awry. The result could be AI that is beyond our control.

This AI might decide that humans aren’t especially vital. You’ve undoubtedly heard about the existential risk of AI, whereby some believe that AI might wipe out humanity or opt to enslave us all. This is generally known as the probability of doom, p(doom), and various surveys of AI specialists are continually being polled to gauge what the probability is and where it is heading; see my discussion at the link here.

Your assumption is perhaps that humans such as AI developers or AI researchers would obviously step in and stop AI before it advances itself into untoward territory. No need to worry about a veering AI since humans would be watching AI like a hawk.

Sorry to say that this is a thin hope.

First, the AI might be advancing at such a pace that the AI slips ahead, and the humans involved are not able to react in a timely manner. The AI then reaches a level such that even if the humans attempt to intervene, the AI refuses to be stopped. We missed the point at which humans could have made a difference. Some refer to this as a rapid-fire intelligence explosion; see my coverage at the link here.

Second, the AI might trick us into thinking that all is well. The idea is that even if humans are on the watch, they could be fooled by AI. The AI might play dumb. The AI might sneakily hide adverse intentions. The gist is that whether humans would realize danger is afoot is a risky roll of the dice.

Third, the AI might produce flaws within the advancing AI. Perhaps the coding gets a bit out of hand. The AI doesn’t detect that the flaw has been generated. At some future point, oops, the flaw is encountered, and the AI goes berserk. The AI didn’t do this on purpose. It was an accidental facet.

What To Do About The Downsides

You’ve probably heard the old line about trying to change the engines on an airplane while it is in flight. Nearly impossible. That’s the problem facing AI makers right now. They are striving mightily to advance AI, and at the same time trying to do so in as safe a manner as feasible.

Of course, not all AI makers necessarily have safety in mind. Some might give lip service to the topic of AI safety. They barely fund their AI safety teams. The AI safety proclamations they make are hollow. It is a false front. The aim is to convince policymakers, lawmakers, and the public that AI safety is paramount, despite the reality that it is a minuscule factor in the way they are approaching AI advancement.

If you were in a hurried foot race and running as hard as you could, a conundrum arises if you are conscientiously worried about factors that few others seem to be giving due attention to. For example, suppose that the runners might be headed toward a devastating cliff, but no one can say for sure whether the cliff is really there or not.

You decide to wave your arms and warn the others of what might be up ahead. If you slow down, they are going to proceed ahead of you. You are nearly compelled to keep pace. The racers and those watching the race appear to possess a herd mentality, and nothing is going to change until something else substantive occurs to pause or stop the frantic contest.

The Collective-Action Problem At Hand

A moment of contemplative reflection suggests that the AI field is immersed in a classic collective-action problem. Unless restraint is undertaken across-the-board, the adverse cost of complying with a pause would fall principally on those that are sincerely embracing the pause. Those opting to ignore the pause are going to benefit.

If only one company pauses, they take the brunt of the costs. Even if a bunch of companies agree to pause, they still take the brunt of the costs. The non-participants will likely gain notable technological advantages. Voluntary restraint is inevitably going to fall apart and not be viably sustained.

Anthropic noted the conundrum in their blog posting entitled “When AI Builds Itself: Our Progress Toward Recursive Self-Improvement And Its Implications”, June 4, 2026, making these key points (excerpts):

• “If it were possible to effectively slow the development of this technology to give ourselves more time to deal with its immense implications, we think that would likely be a good thing.”
• “But if a slowdown simply lets the least cautious actors catch up technologically, it could leave everyone less safe.”
• “Without a global coordination mechanism, companies and governments will have to make difficult decisions about safety while under competitive and geopolitical pressures.
• “We believe it would be good for the world to have the option to slow or temporarily pause frontier AI development to enable societal structures and alignment research to keep up with the advance of the technology.”

Think of this as a baseball game. The reason that baseball games proceed with suitable aplomb is due to a collective agreement on what the rules of the game consist of. Furthermore, there are umpires that keep the players honest with respect to the established rules and what occurs during the playing of the game.

Advances in AI are not governed globally by any binding collective agreement, nor are there umpires that keep the AI efforts in check. It is pretty much a free-for-all.

A Global Pause Is A Tall Order

We have had moments in history where a global pause has been given close attention.

Think about the Cold War and the build-up of ICBMs (intercontinental ballistic missiles). The advent of ICBMs meant that countries could attack each other from tremendous distances. These were central to the nuclear arms race.

A realization eventually emerged that prevailing Cold War doctrine would lead to mutually assured destruction (MAD). If ICBMs were launched at another superpower, the retaliation would send ICBMs against their opponent. This would escalate. A worldwide conflagration would be in the cards. In a sense, everyone loses; nobody wins.

An arrangement was reached to allow for inspection of ICBMs in their underground silos. It was a means to try and limit the ever-expanding growth of the nuclear arms race. Arms control negotiations and intelligence exchanges became part of the SALT (strategic arms limitation talks) and START (strategic arms reduction treaty) efforts.

Global Pause Of AI-Builds-AI

Unfortunately, trying to compare the nuclear arms race to the AI advancement race is dicey and doesn’t provide a ready-made solution.

In the nuclear arms race, there were primarily two superpowers that held the keys to the arms race. For AI advancements, you would be hard-pressed to claim that AI advancements are held in just two sets of hands. Researchers even in a tiny AI lab can find discoveries and make progress. Though the main AI makers are the focus of most attention, the effort to advance AI is widely fragmented and scattered globally.

Another challenge is the aspect of inspections. For SALT and START, it was somewhat manageable to have silos open for viewing missiles and available for inspection. These were large-scale physical artifacts. The same is not true about AI. Trying to pinpoint where someone keeps their AI and making it available for inspection is much more loosey-goosey.

You might make the case that since advances in AI tend to require vast amounts of compute, perhaps the focus could go toward tracking and monitoring of data centers. Limits and inspection protocols could be aimed at the resources required to allow AI to build AI.

Living In A Dream

Could the world reach a collective agreement on pausing the AI-builds-AI aspects?

And, if so, could there be AI umpires that would be established to keep all AI makers on the up-and-up?

Given the real world as we know it, this all seems hardly plausible. Imagine the fierce opposition to putting together such an arrangement. The temptation would be to drag out the initial negotiations, buying time to keep pushing ahead on AI, perhaps reaching a pinnacle AI anyway, long before the agreement can be cast in stone.

There would be clever trickery to fool the AI umpires. Tons of research would shift away from AI advancement and become preoccupied with how cheaters are cheating, and how to try and catch the cheaters. The odds are it would spiral into a disconcerting morass.

I realize that seems downbeat, perhaps even depressing. If you want an upside, you are welcome to make the brazen assumption that a pause isn’t needed, and that AI advancements are going to work out just fine on their own accord. Dreamy.

Paths To Be Found

Let’s not give up hope. The world might reach a juncture where the seriousness of the AI risks drives a global initiative of considering a pause or stoppage. Will we be ready? Can anything be done in anticipation of that possibility?

According to the Anthropic blog posting, here’s what they aim to do (excerpts):

• “The Anthropic Institute will conduct research — in collaboration with many others — and take actions to help build the systems that a credible slowdown or pause would require.”
• “These systems would enable frontier AI developers to verify that others globally have actually stopped or slowed, and that a bad actor could not use the auspices of a coordinated slowdown to jump ahead in secret.”
• “If such systems existed, we expect that we would slow down or temporarily pause, if other developers at or near the frontier also did so in a verifiable manner.”

As you can see, they are saying that they are willing to try and devise a means to enable a pause or slowdown to be undertaken, providing the needed mechanisms that would allow AI umpires to do their job. Essential architectural underpinnings and scaffolding will presumably be designed, built, and tested.

The World We Are In

I say that bringing global attention to this enormous concern is heartening, and likewise so is the willingness to put bucks toward crafting underpinnings for this. Where there is a will, there is a way. Take a stand and see where it goes.

But you might be wondering if AI makers such as Anthropic are going to be essentially wasting scarce resources if it turns out that no such collective agreement can be reached. These optimistic efforts might be for naught.

I wager that any such effort in of itself might produce some interesting and quite useful insights about AI and AI advancements. Thus, even if the world won’t align on a collective pause, the knowledge gained, and the new tools that might come from these endeavors could be notably useful for a slew of purposes.

The great American inspirational speaker William Arthur Ward made this keen remark: “The pessimist complains about the wind; the optimist expects it to change; the realist adjusts the sails.” Count me as an optimist and a realist, and let’s do our best to expect societal change and adjust the AI sails accordingly.