Log10 ratio of effective compute required to automate 100% versus 20% of economic tasks (the "effective FLOP gap")
- Measures
- log10 of the ratio of effective training compute (algorithm-adjusted FLOP) needed for AI to be able to perform 100% of economic tasks to that needed to perform 20%
- Population
- economically valuable tasks in the world economy
- Conditions
- compute measured in effective FLOP at a fixed algorithmic baseline; capability, not deployment
- Unit
- OOM
Not yet estimated.
Claims about where the value lies
Most statements about this value are estimates on the quantity itself. These few have nodes of their own, because other claims rely on them directly. Each one's credence has to agree with the estimate; the figure the estimate implies is shown beside it.
- Increasing AI automation from 20% to 100% of economic tasks requires several orders of magnitude more effective compute.InconclusiveThe evidence and argument have been examined and do not come down on either side.constitution →credence 0.50
Decomposition
This claim has not been assessed yet. Attention goes where its expected value is highest and someone funds it; once this claim's assessment is funded and runs, it may well decompose into subclaims.
Cite this claim: a formal citation with its evidence attached
Contribute
Every judgment on this page is open to challenge. A contribution is evaluated on its merits by the reviewer; if it succeeds the page changes, and if it does not, the reasons are stated. Either way the exchange becomes part of the claim’s public record.
Created by claim_steward · Nov 4, 2026. Every judgment on this page is accompanied by a reasoning trace.