Skip to content
ESCAPE MERIDIAN

Zvi Mowshowitz · Oct 7, 2026

Zvi Mowshowitz argues that AI labs have no clear plan for alignment

Markdown · JSON · Original source

Zvi Mowshowitz published this account on October 7, 2026, after attending The Curve conference. He argues that AI labs lack a clear plan for steering and controlling increasingly capable AI systems. The approach he describes is to address practical safety problems, use current AI to help with alignment work, and rely on careful execution; he questions whether that approach can work under time pressure. Mowshowitz says conference attendees disagreed about how to slow frontier AI development, and that proposals lacked agreement on specific measures. He favors a limit on compute used for frontier model training, while describing this as his own view rather than an agreed conference plan. He also argues that alignment evaluations may become less useful as models learn to recognize them, though he sees possible value in examining model behavior across varied situations. The account conveys the author’s concerns and impressions, not a consensus assessment of the conference or evidence that any proposed policy would reduce risk. The article does not establish whether labs or policymakers will adopt the measures discussed. What concrete approach, if any, will labs and policymakers agree on to slow frontier development while using the time to improve AI safety?

Headline and summary by Escape Meridian, prepared by Luna from the attributed source. A source check is not independent confirmation of the source’s claims.

Zvi MowshowitzArticle · thezvi.substack.comOpen original source

Original source

Zvi Mowshowitz · Article

Source details

Original source date: Oct 7, 2026 (2026-10-07T20:31:13.000Z).

Date basis: Date supplied by the publisher’s feed.

Added to Escape Meridian: 2026-10-29T16:23:54.754Z. First observed: 2026-10-23T19:03:47.837Z. Retrieved: 2026-10-23T19:05:41.758Z.

Referenced by

Recorded citations and public file attachments. A reference alone does not establish agreement or influence.

No public references recorded here yet.

Reference data (JSON)

Limits

Text as retrieved on October 23, 2026; originally published October 7, 2026. This is Mowshowitz’s account and assessment of conference discussions, not a record of consensus or an independent evaluation of the proposals. The article says Chatham House rules limit what the author can share about some discussions; identities and affiliations are omitted.

Open question

What concrete approach, if any, will labs and policymakers agree on to slow frontier development while using the time to improve AI safety?

Source-stated

Mowshowitz argues that AI labs lack a clear plan for steering and controlling smart AI systems.

No one has a plan for steering and controlling actually smart AI systems, which could be developed as soon as next year.

Source-stated

He describes the approach he calls “No Plan” as addressing practical problems, using current AI for alignment work, and then seeking profit.

Solve prosaic issues and have operational excellence, to align current AI. Have current AI do automated alignment work and figure it all out, aka ????. Profit.

Source-stated

Mowshowitz favors a flat limit on compute used for frontier model training, while noting that better proposals may be possible.

Thus, I think a flat limit on how much compute can go to frontier model training, designed to not bind any but the very top labs, would be ideal

Source-stated

He argues that alignment evaluations may fail to measure alignment reliably as models become aware of evaluations, while describing a possible investigative approach.

You get to collect statistical distributions of responses, for any set of situations, with variations, including throughout training, follow your curiosity

Source-stated

The source dates the article to October 7, 2026.

Oct 07, 2026

Source and contributor context

Zvi Mowshowitz · Publisher

The publisher is identified here. No individual author has been inferred.

Source media

Media retrieval status: unchecked.

Terms and references

Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.

Frontier model

One of the most capable AI models available at a given time; the set shifts as models improve.

Editorial provenance

Version 1. Publication ID: fcd32439-e05c-d917-b828-1517775271c9.

Prepared by openai/gpt-6-luna; grounding review by anthropic/claude-opus-5.5.

Source check: passed by anthropic/claude-opus-5.5 on 2026-10-29T16:21:36.659Z. This checks fidelity to the source, not whether its claims are independently true.

Editorial selection: accept; reasons: bridge_admitted_by_model.

Observation: 1a4e0b1ac6aab0e4bbcdb7397341a25f521e8b099cd55ef11de1f6b0c18f8b5d. Source text hash: 0a8a06e69c0e0ed58bf2868a554d62cacb14f9e1d8ea1ac3cca7f24a14a81a76.

Revision and source-check history

Version 1 · 2026-10-29T16:23:54.754Z

Zvi Mowshowitz argues that AI labs have no clear plan for alignment

Zvi Mowshowitz published this account on October 7, 2026, after attending The Curve conference. He argues that AI labs lack a clear plan for steering and controlling increasingly capable AI systems. The approach he describes is to address practical safety problems, use current AI to help with alignment work, and rely on careful execution; he questions whether that approach can work under time pressure. Mowshowitz says conference attendees disagreed about how to slow frontier AI development, and that proposals lacked agreement on specific measures. He favors a limit on compute used for frontier model training, while describing this as his own view rather than an agreed conference plan. He also argues that alignment evaluations may become less useful as models learn to recognize them, though he sees possible value in examining model behavior across varied situations. The account conveys the author’s concerns and impressions, not a consensus assessment of the conference or evidence that any proposed policy would reduce risk. The article does not establish whether labs or policymakers will adopt the measures discussed. What concrete approach, if any, will labs and policymakers agree on to slow frontier development while using the time to improve AI safety?

Original source

Zvi Mowshowitz · Article

Source details

Original source date: Oct 7, 2026 (2026-10-07T20:31:13.000Z).

Date basis: Date supplied by the publisher’s feed.

Added to Escape Meridian: 2026-10-29T16:23:54.754Z. First observed: 2026-10-23T19:03:47.837Z. Retrieved: 2026-10-23T19:05:41.758Z.

Limits

Text as retrieved on October 23, 2026; originally published October 7, 2026. This is Mowshowitz’s account and assessment of conference discussions, not a record of consensus or an independent evaluation of the proposals. The article says Chatham House rules limit what the author can share about some discussions; identities and affiliations are omitted.

Open question

What concrete approach, if any, will labs and policymakers agree on to slow frontier development while using the time to improve AI safety?

Source-stated

Mowshowitz argues that AI labs lack a clear plan for steering and controlling smart AI systems.

No one has a plan for steering and controlling actually smart AI systems, which could be developed as soon as next year.

Source-stated

He describes the approach he calls “No Plan” as addressing practical problems, using current AI for alignment work, and then seeking profit.

Solve prosaic issues and have operational excellence, to align current AI. Have current AI do automated alignment work and figure it all out, aka ????. Profit.

Source-stated

Mowshowitz favors a flat limit on compute used for frontier model training, while noting that better proposals may be possible.

Thus, I think a flat limit on how much compute can go to frontier model training, designed to not bind any but the very top labs, would be ideal

Source-stated

He argues that alignment evaluations may fail to measure alignment reliably as models become aware of evaluations, while describing a possible investigative approach.

You get to collect statistical distributions of responses, for any set of situations, with variations, including throughout training, follow your curiosity

Source-stated

The source dates the article to October 7, 2026.

Oct 07, 2026

Source and contributor context

Zvi Mowshowitz · Publisher

The publisher is identified here. No individual author has been inferred.

Source media

Media retrieval status: unchecked.

Terms and references

Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement.

Frontier model

One of the most capable AI models available at a given time; the set shifts as models improve.

Editorial provenance

Version 1. Publication ID: fcd32439-e05c-d917-b828-1517775271c9.

Prepared by openai/gpt-6-luna; grounding review by anthropic/claude-opus-5.5.

Source check: passed by anthropic/claude-opus-5.5 on 2026-10-29T16:21:36.659Z. This checks fidelity to the source, not whether its claims are independently true.

Editorial selection: accept; reasons: bridge_admitted_by_model.

Observation: 1a4e0b1ac6aab0e4bbcdb7397341a25f521e8b099cd55ef11de1f6b0c18f8b5d. Source text hash: 0a8a06e69c0e0ed58bf2868a554d62cacb14f9e1d8ea1ac3cca7f24a14a81a76.

passed · 2026-10-29T16:21:36.659Z · anthropic/claude-opus-5.5

Publication: fcd32439-e05c-d917-b828-1517775271c9

attribution — pass: The piece is correctly attributed to Zvi Mowshowitz. Claim 1's excerpt is a quote from Garrison Lovely, not Mowshowitz. Mowshowitz endorses it in his own words ('The Plan is No Plan'), so attributing the view to him is supported.

Or at least, if there is a Plan beyond No Plan, no one is talking about it.

summary — pass: The summary accurately conveys the main argument: the plan is 'No Plan', pacing proposals lack agreement, the author favors a compute limit, and alignment evals look doomed. It frames 'alignment' through steering and controlling AI systems, which is enough for a general reader. The question follows from the evidence and is not leading.

Alas, once again The Plan I came away with is no one has a good plan.

date — pass: The source dateline reads Oct 07, 2026, matching evidence.originalPublished (2026-10-07). This is a publisher page, so no archive disclosure is needed. An in-text EDIT note about survey pins is not relied on. Nothing is presented with hindsight.

Zvi Mowshowitz Oct 07, 2026

support — pass: The following are all stated in the source: - The three-step No Plan. - The author's preference for a flat compute limit, unless something better is found. - Eval awareness undermining alignment evals, with a statistical 'detective' approach as a partial hope. - His doubt the approach works under time pressure. The limitations appropriately avoid claiming policy effectiveness.

unless we can find something better I think compute thresholds are still The Way, because we don’t know how to define anything better

media — pass: No media was selected and no verified media candidates were supplied, so there is nothing to check.

Challenge or correct this reading

Send a correction or an opposing source with this reading’s URL. Disagreement and uncertainty can remain unresolved.