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AI Impacts: Likelihood of Discontinuous Progress
webAuthor
https://aiimpacts.org/author/katja/
Credibility Rating
3/5
Good(3)Good quality. Reputable source with community review or editorial standards, but less rigorous than peer-reviewed venues.
Rating inherited from publication venue: AI Impacts
Published by AI Impacts, this piece informs the classic 'fast vs. slow takeoff' debate by grounding predictions in historical data on technological discontinuities, making it a useful reference for safety researchers assessing risk timelines.
Metadata
Importance: 62/100organizational reportanalysis
Summary
An AI Impacts analysis examining the probability that progress toward AGI will be discontinuous—featuring sudden jumps or takeoffs—rather than gradual. It surveys historical precedents of discontinuous progress in technology and science to inform predictions about how AI development might unfold. The piece is relevant to debates about fast vs. slow AI takeoff scenarios and associated safety implications.
Key Points
- •Examines historical cases of discontinuous technological progress to assess how likely a sudden AGI transition would be.
- •Distinguishes between different types of discontinuities (performance jumps, capability thresholds) and their relevance to AGI development.
- •Historical evidence suggests discontinuous progress is relatively rare, though not absent, in technological domains.
- •Findings bear directly on takeoff speed debates central to AI safety strategy and governance responses.
- •Slow, continuous progress would allow more time for safety measures; discontinuous progress increases risk of inadequate preparation.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| Long-Timelines Technical Worldview | Concept | 91.0 |
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We aren’t convinced by any of the arguments we’ve seen to expect large discontinuity in AI progress above the extremely low base rate for all technologies. However this topic is controversial, and many thinkers on the topic disagree with us, so we consider this an open question.
Contents
## Details
### Definitions
We say a technological discontinuity has occurred when a particular technological advance pushes some progress metric substantially above what would be expected based on extrapolating past progress. We measure the size of a discontinuity in terms of how many years of past progress would have been needed to produce the same improvement. We use judgment to decide how to extrapolate past progress.
For instance, in the following trend of progress in chess AI performance, we would say that there was a discontinuity in 2007, and it represented a bit over five years of progress at previous rates.
[](http://aiimpacts.org/wp-content/uploads/2014/12/SSDF-progress.png) Figure 1: Machine chess progress, in particular SSDF records.
### Relevance
Discontinuity by some measure, on the path to AGI, lends itself to:
- A party gaining decisive strategic advantage
- A single important ‘deployment’ event
- Other very sudden and surprising events
Arguably, the first two require some large discontinuity. Thus the importance of planning for those outcomes rests on the likelihood of a discontinuity.
### Outline
We investigate this topic in two parts. First, with no particular knowledge of AGI as a technology, how likely should we expect a particular discontinuity to be? We take the answer to be quite low. Second, we review arguments that AGI is different from other technologies, and lends itself to discontinuity. We currently find these arguments uncompelling, but not decisively so.
### Default chance of large technological discontinuity
Discontinuities larger than around ten years of past progress in one advance seem to be rare in technological progress on natural and desirable metrics.[1](https://aiimpacts.org/likelihood-of-discontinuous-progress-around-the-development-of-agi/#easy-footnote-bottom-1-1086 "") [We have verified](http://aiimpacts.org/cases-of-discontinuous-technological-progress/) around five examples, and know of several other likely cases, though have not completed this [investigation](http://aiimpacts.org/discontinuous-progress-investigation/).
This does not include the discontinuities when metrics initially go from zero to a positive number. For instance, the metric ‘number of Xootr scooters in the world’ presumably went from zero to one on the first day of production, though this metric had seen no progress before. So on our measure of discontinuity size, this was infinitely many years of progress in one step. It is rarer for a broader metric (e.g. ‘scooters’) to go from zero to one, but it must still happen occasionally. We do not mean to ignore
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