Why the 'intelligence explosion' might be too fast to handle | Will MacAskill

The 20th century saw unprecedented change: nuclear weapons, satellites, the rise and fall of communism, the internet, postmodernism, game theory, genetic engineering, the Big Bang, quantum mechanics, birth control, and more. Now imagine all of it compressed into just 10 years.

That’s the future Will MacAskill — philosopher, founding figure of effective altruism, and now researcher at the Forethought Centre for AI Strategy — argues we need to prepare for in his new paper “Preparing for the intelligence explosion.” Not in the distant future, but probably in three to seven years. (https://www.forethought.org/research/...)

The reason: AI systems are rapidly approaching human-level capability in scientific research and intellectual tasks. Once AI exceeds human abilities in AI research itself, we’ll enter a recursive self-improvement cycle — creating wildly more capable systems. Soon after, by improving algorithms and manufacturing chips, we’ll deploy millions, then billions, then trillions of superhuman AI scientists working 24/7 without human limitations. These systems will collaborate across disciplines, build on each discovery instantly, and conduct experiments at unprecedented scale and speed — compressing a century of scientific progress into mere years.

Will compares the resulting situation to a mediaeval king suddenly needing to upgrade from bows and arrows to nuclear weapons to deal with an ideological threat from a country he’s never heard of, while simultaneously grappling with learning that he descended from monkeys and his god doesn’t exist.

What makes this acceleration perilous is that while technology can speed up almost arbitrarily, human institutions and decision-making are much more fixed. So there’s reason to worry about our own capacity to make wise choices. Will lays out 10 “grand challenges” we’ll need to quickly navigate to successfully avoid things going wrong during this period.

In this wide-ranging conversation with host Rob Wiblin, Will maps out the challenges we’d face in this potential “intelligence explosion” future, and what we might do to prepare.

Learn more and see the full transcript on the 80,000 Hours website: https://80k.info/wm25

This episode was originally recorded on February 7, 2025.

Chapters:
• Cold open (00:00:00)
• Who’s Will MacAskill? (00:00:43)
• Why Will now just works on AGI (00:01:03)
• Will was wrong(ish) on AI timelines and hinge of history (00:04:21)
• A century of history crammed into a decade (00:09:19)
• Science goes super fast; our institutions don't keep up (00:16:15)
• Is it good or bad for intellectual progress to 10x? (00:21:44)
• An intelligence explosion is not just plausible but likely (00:23:41)
• Intellectual advances outside technology are similarly important (00:30:04)
• Counterarguments to intelligence explosion (00:32:42)
• The three types of intelligence explosion (software, technological, industrial) (00:39:00)
• The industrial intelligence explosion is the most certain and enduring (00:42:01)
• Is a 100x or 1,000x speedup more likely than 10x? (00:53:44)
• The grand superintelligence challenges (00:57:39)
• Grand challenge #1: Many new destructive technologies (01:01:29)
• Grand challenge #2: Seizure of power by a small group (01:09:10)
• Is global lock-in really plausible? (01:11:06)
• Grand challenge #3: Space governance (01:21:50)
• Is space truly defence-dominant? (01:32:19)
• Grand challenge #4: Morally integrating with digital beings (01:36:04)
• Will we ever know if digital minds are happy? (01:45:01)
• “My worry isn't that we won't know; it's that we won't care” (01:50:39)
• Can we get AGI to solve all these issues as early as possible? (01:54:05)
• Politicians have to learn to use AI advisors (02:07:05)
• Ensuring AI makes us smarter decision-makers (02:11:25)
• How listeners can speed up AI epistemic tools (02:15:11)
• AI could become great at forecasting (02:18:54)
• How not to lock in a bad future (02:20:26)
• AI takeover might happen anyway — should we rush to load in our values? (02:32:14)
• ML researchers are feverishly working to destroy their own power (02:41:57)
• We should aim for more than mere survival (02:45:23)
• By default the future is rubbish (02:57:03)
• No easy utopia (03:05:21)
• What levers matter most to utopia (03:15:19)
• Bottom lines from the modelling (03:29:32)
• People distrust utopianism; should they distrust this? (03:33:34)
• What conditions make eventual eutopia likely? (03:38:26)
• The new Forethought Centre for AI Strategy (03:47:15)
• How does Will resist hopelessness? (04:00:42)

Video editing: Simon Monsour
Audio engineering: Ben Cordell, Milo McGuire, Simon Monsour, and Dominic Armstrong
Camera operator: Jeremy Chevillotte
Transcriptions and web: Katy Moore