I like the idea of an incidence column, but I'm not convinced its sign tells us whether a regulation is genuinely about safety or just protecting incumbents. A rule could reduce real risks while also benefiting the leading lab, simply because smaller competitors are less equipped to comply. Both things can be true. Wouldn't it make more sense to measure those effects separately? Curious what gleech thinks about this.
47
Research into relative effects of different pacing interventions
2
ProposalGrant
Closes November 9th, 2026$5,000raised
$3,000minimum funding
$50,000funding goal
Offer to donate
31 daysleft to contribute
You're pledging to donate if the project hits its minimum goal and gets approved. If not, your funds will be returned.
Project summary
I will do research into the question under the title
What are this project's goals? How will you achieve them?
To produce research outputs answering the question under the title.
I would turn the appendix into a table with one row for each intervention, ordered by how long it would delay deployment of AIs that rival current leading systems. The first column in this table is yes or no: can the leading lab substitute around the rule? If yes, that rule doesn’t slow them down - so it goes to the bottom of my list immediately, with no delay estimate needed. (I expect about a third of the list will fall here.) The remaining rows would be sorted into tiers, corresponding to how many months of delay they would buy. These need to be wide enough to be honest, but narrow enough to make a real distinction between something taking a month versus a year. The only place that the value of delaying progress in AI by a month enters is at the end, when we decide how far down this list we should go before stopping; it’s just some number that we apply equally to each row in the table.
There would also be an incidence column, i.e. for each regulation does it help or hurt the leader in the race? This is really important, because what distinguishes safety measures from cartels is the sign. So this column would be published right next to every row.
This entire task should take a few weeks to a couple of month if I use public information on the progress of the leading labs and keep a detailed spreadsheet. However, to get to the point of having a table with a credible amount of accuracy on each rule, I would need a collaborator who can put in the work to estimate the effect of each rule on the leading labs, row by row. Once this table existed, I would expect both sides of the debate to be forced to argue about the actual details in the table, rather than general slogans and heuristics. I’d love to get started on that first cut.
How will this funding be used?
Who is on your team? What's your track record on similar projects?
What are the most likely causes and outcomes if this project fails?
How much money have you raised in the last 12 months, and from where?
None
🐞
Khaled Eltokhy
about 2 hours ago@atilgandev Yeah that's a good point. I was too brief in my description and also my thinking on this has evolved a bit. Of course, a rule can buy real delay while helping the leader. Compliance costs may fall hardest on smaller labs.
This is why we should separate delay and incidence in different columns in the table. The case of the cartel is a rule that buys little/no delay and also widens the leader's lead. While a rule that buys a real delay and helps the leader is still a safety measure, it's also a transfer to the incumbent that should be priced as such.
offering $5,000
Gavin Leech
about 7 hours agoKhaled responded tartly to our launch of [pacing.tech](pacing.tech), which I liked. Following up with him, I like his rigour and am looking forward to seeing what he does on the research direction.