Chapter 1: What are AI timelines and why do they matter?
Broad Timelines by Toby Ord Published on March 19, 2026 No one knows when AI will begin having transformative impacts upon the world. People aren't sure and shouldn't be sure. There just isn't enough evidence to pin it down. But we don't need to wait for certainty. I want to explore what happens if we take our uncertainty seriously, if we act with epistemic humility.
What does wise planning look like in a world of deeply uncertain AI timelines? I'll conclude that taking the uncertainty seriously has real implications for how one can contribute to making this AI transition go well. And it has even more implications for how we act together, for our portfolio of work aimed towards this end.
Chapter 2: How does epistemic humility relate to AI uncertainty?
There's an image here. Description.
Graph showing a curved line that peaks early, then gradually declines.
Subheading. AI Timelines. By AI Timelines, I refer to how long it will be before AI has truly transformative effects on the world. People often think about this using terms such as Artificial General Intelligence, AGI, Human Level AI, Transformative AI, or Superintelligence. Each term is used differently by different people, making it challenging to compare their stated timelines.
Indeed, even an individual's own definition of their favoured term will be somewhat vague, such that even after their threshold has been crossed, they might have trouble specifying in which year it happened. Many commentators have suggested this makes terms such as AGI useless, but I don't think that is right.
I like to think of it in terms of a group of hikers seeing a mountain in the distance, towering up into the clouds and beyond, with its snowy peak catching the sun's light. They talk animatedly about how amazing it would be to climb so high that they are inside a cloud. Or imagine being above the clouds, looking over them like an angel.
After many hours of climbing, they notice there is a faint haze. Are they inside the cloud now? The mist gradually gets thicker until they can only see 10 meters ahead. Are they inside it now? Then it drops to 9 meters. Then 8. Then visibility starts to increase again. After an hour there is only the slightest haze. Are they above the clouds now?
Another 30 minutes and there is no haze, and they can all agree they are above the clouds. It is clear that at some point they were inside the cloud and sometime later were above it. And it is clear that these were sensible and useful concepts.
For example, they took precautions like roping themselves together for the journey through the cloud due to the low visibility and took cameras with them because they knew they could take beautiful photos above the clouds. A lack of sharp boundaries that doesn't make these concepts useless.
but they were admittedly a lot more useful when the hikers were on the ground, planning their route, and a lot less useful in the debatable boundary zones. I think of AGI and human-level intelligence as the cloud and superintelligence as being above the cloud. They are useful concepts, despite their vagueness. But they're markedly less useful when you get close to them.
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Chapter 3: What challenges arise from vague definitions of AI terms?
A country of geniuses in a data center, with the profound economic, societal, and security implications that would bring. End quote. At the other end, a good example of long timelines is E. Jerdil, co-founder of Epoch AI, whose median time for the full automation of remote work is 2045, 20 years away.
While experts continue to disagree on when AI will start having transformative impacts, they are clearly not stubbornly ignoring the evidence. For as Helen Toner explained in her great essay, long the timelines to advanced AI have gotten crazy short. Before of ChatGPT, short timelines used to mean something like 10 to 20 years, so since it could take a long time to prepare, we should start now.
Long timelines used to mean that there was no sign AGI will happen in the next 30 years, if it happened this century at all, so it is premature to do any work related to controlling advanced AI.
But now we see short timelines like Dario Amadei's with genius-level AI are almost certain to happen within the next five years, and many staunch proponents of long timelines are now saying we'll reach human level in just 10 or 20 years.
Here's a nice graph 80,000 hours put together of how the average forecasted time until AGI on the Metaculous prediction site has shortened from about 50 years to about 5 years in just a 5-year window. There's an image here.
A line graph showing forecasted years until first general AI system announced over time.
Subheading. Broad timelines. So everyone is updating on the evidence and shortening their timelines, yet substantial disagreement remains. This is often framed as a debate. That we should be trying to assess who is right, whether timelines really are short or long, or medium.
People pick winners, affiliate with one side or the other, and rub it in whenever the latest evidence favours their preferred camp. My central claim today is that for most of us, that is the wrong frame. You should have neither short timelines nor long timelines, but broad timelines. That is, quote,
The correct epistemic response to the lasting expert disagreement is to have a broad distribution over AI timelines. End quote. First, there is too much disagreement among very smart and informed people for it to be reasonable to have a narrow range of possible years.
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Chapter 4: How do short and long AI timelines differ in implications?
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