9 reasons against a near-term AI slow-down

By Jordan Arel @ 2026-09-28T17:26 (+21)

I’ve heard more arguments in favor of a near-term[1] coordinated AI pause/slow-down[2] than arguments against. I think such questions, including complex flow-through effects, are difficult, and it’s important to really consider both sides. I am not convinced by these arguments, and feel highly uncertain as to when a slow-down would be best, but believe it most likely will be good to slow down or pause AI development at some point.

Here are 9 reasons against a near-term AI slow-down:

  1. A near-term slowdown could prevent the warning shots that would make the public take AI risk more seriously. And techniques for safe near-term AI may be insufficient for advanced AI, so a near-term slow-down could give a false sense of security for handling truly dangerous AI.
  2. Slowing down too early could have an idea inoculation / boy-calls-wolf effect, where the topic becomes more politicized[3] and taken less seriously because people haven’t see anything scary enough to make them see AI as truly dangerous, and then when we really need to go slow later it’s much more difficult to get political will.
  3. Not slowing down means we have less of various types of overhang that could make things more dangerous if/when full-speed research resumes, such as:
    1. Compute overhang (if hardware is not also fully paused) and other technical advances that complement AI
    2. Progress on robotics
    3. More AI researchers joining the field
    4. Overhang of new ideas for training AI more effectively
    5. Progress in biology that lowers the floor for AI capabilities needed to create omnicidal pandemics
    6. Various AI related info risks, such as would-be dictators realizing they could use AI to take over, and entrepreneurs realizing AI could make them rich
    7. Etc. (I haven’t thought about this much but suspect there are more)
  4. Getting near-human level AI systems before slowing down or pausing could give us AI that is much more helpful for making the most of the slow-down, e.g. AI for alignment research, epistemics including forecasting, coordination, policy and strategy research, etc.
  5. Waiting to slow down means that we will have a much better understanding of the kind of AI risks that are most serious to focus on when we do pause or slow-down, including more realistic model organisms to study, as the shape of danger could shift significantly before AI becomes truly dangerous.
  6. It is plausible that if we get advanced AI sooner, people who care about x-risk and the long-term future will be more differentially advantaged by AI use, as they are currently disproportionately focused on AI, but if things slow down this may give others time to catch up and cause regression to the mean with less altruistic or existentially concerned values influencing AI development.
  7. Safety-focused labs are currently more in the lead, a slow-down could lead to loss of lead, and if the slow-down breaks down, safety focused labs may then have less of a buffer for slow-down when they need it (this could be considered a subset of number 6.)
  8. Getting powerful AI sooner means we can save more people currently alive if this brings forward longevity escape velocity and doesn’t increase extinction risk[4]. More generally, advanced AI might help with many near-term issues such as animal welfare, poverty, and climate change.
  9. A coordinated pause/slow-down, if it requires government involvement, would currently involve the Trump administration and Chinese Communist Party. At least half of this equation will likely change in a couple years.

Curious if people have anything they would add to this list? Also would love to hear arguments against each of these points, a red-team of my red-team!

  1. ^

    What I mean by “near-term” is far more about when these factors come into play than it is about any wall-clock timeframe, but very roughly I’d estimate “near-term” means something like less than 6 months-2 years.

  2. ^

    Note that whether or not a near-term coordinated slow-down is good is a separate question from whether it is good to advocate for or build the machinery for an eventual slow-down in the near-term; these may be necessary significantly in advance in order to spread awareness of the idea, widen the overton window, strategically prepare, and iteratively develop concrete high-quality plans for what the best version of a slow-down would look like. Whether a coordinated slow down would be good is also a separate question from whether individual actors should slow down.

  3. ^

    Slowing down could also cause an economic downturn, increasing chances a premature slow-down would polarize people to be more against safety.

  4. ^

    An important consideration for person-affecting views. If not slowing down does increase x-risk, then this seems highly dubious, even from a person-affecting perspective, as we would be risking all lives to save some fraction of lives.


Vasco Grilo🔸 @ 2026-09-30T16:07 (+2)

Hi Jordan.

A near-term slowdown could prevent the warning shots that would make the public take AI risk more seriously.

Do you think this generally applies to other risks? For example, could decreasing the risk of hard aircraft landings increase the risk of catastrophic aircraft landings?

Jordan Arel @ 2026-10-01T01:36 (+3)

Hi Vasco, interesting question. I think it’s actually quite a complicated question, and I wouldn’t say I’m knowledgeable enough about aircraft risks to have an informed guess. Factors like how risky and how frequent hard landings are, what social opinion is on aircraft safety and how much hard landings would change public opinion, how catastrophic a catastrophic landing is, the opportunity cost of slowing down aircraft progress to make landings safer, etc. all come into play.

I think the arguments around this I find most persuasive in the case of AI is that the technology is accelerating extremely fast, public opinion is to see the risks as somewhat sci-fi and perhaps just marketing or regulatory capture strategies by the labs, and it seems possible that with enough effort we could prevent early warning shots until AI is smart enough to strategically decide for itself to bide its time, not cause any warning shots, and pretend to be aligned until it has the opportunity to take over.

So it seems like in the case of AI, the cost-benefit analysis could plausibly be that early warning shots may be far less catastrophic than later catastrophes, yet bad enough to really turn public opinion toward having more political will for later safety efforts.

And I think the calculus could be different for other risks depending on:

  1. Are people more or less skeptical of the catastrophic risk to start with
  2. Is risk getting exponentially worse over time, and how fast
  3. Will warning shots be similar enough/will they raise the right kind of concerns to increase political will for catastrophic risk reduction
  4. Is reducing catastrophic risk tractable, given political will
  5. Is loss of value due to slowing down the industry actually worth the reduction in risk
  6. Will the warning shot back-fire, itself causing some kind of over-regulation or overly aggressive slowing that raises overall risk for other reasons (e.g. other reasons in the original post)

I would say the amount of complication here is part of why I feel pretty uncertain, but I think the things that make warning shots plausibly more helpful here are that much of the public is currently skeptical, and the risks seem like they will get much worse over time, so an earlier warning shot could be high value if it reduces risk skepticism for the bigger risks.

Vasco Grilo🔸 @ 2026-10-01T14:13 (+2)

Thanks for elaborating. I created this post with Claude about whether reducing small risks increases large ones. I plan to publish it in 7 days or so. I will let you know once I do.

Denis @ 2026-10-01T23:35 (+1)

Great post!

I'm a member of Pause AI, and I find it super valuable to have all the arguments that I (presumably should) disagree with clearly stated to give me pause for thought. 

We do this far too little. 

I still think we should pause (at least, after one quick read-through), but I also think that if we pause, we need to look at each argument like this seriously to find solutions or mitigations. 

Thank you for posting this!