We (Connor Leahy, Gabriel Alfour, Chris Scammell, Andrea Miotti, Adam Shimi) have just published The Compendium, which brings together in a single place the most important arguments that drive our models of the AGI race, and what we need to do to avoid catastrophe.
We felt that something like this has been missing from the AI conversation. Most of these points have been shared before, but a “comprehensive worldview” doc has been missing. We’ve tried our best to fill this gap, and welcome feedback and debate about the arguments. The Compendium is a living document, and we’ll keep updating it as we learn more and change our minds.
We would appreciate your feedback, whether or not you agree with us:
- If you do agree with us, please point out where you think the arguments can be made stronger, and contact us if there are ways you’d be interested in collaborating in the future.
- If you disagree with us, please let us know where our argument loses you and which points are the most significant cruxes - we welcome debate.
Here is the twitter thread and the summary:
The Compendium aims to present a coherent worldview about the extinction risks of artificial general intelligence (AGI), an artificial intelligence that exceeds that of humans, in a way that is accessible to non-technical readers who have no prior knowledge of AI. A reader should come away with an understanding of the current landscape, the race to AGI, and its existential stakes.
AI progress is rapidly converging on building AGI, driven by a brute-force paradigm that is bottlenecked by resources, not insights. Well-resourced, ideologically motivated individuals are driving a corporate race to AGI. They are now backed by Big Tech, and will soon have the support of nations.
People debate whether or not it is possible to build AGI, but most of the discourse is rooted in pseudoscience. Because humanity lacks a formal theory of intelligence, we must operate by the empirical observation that AI capabilities are increasing rapidly, surpassing human benchmarks at an unprecedented pace.
As more and more human tasks are automated, the gap between artificial and human intelligence shrinks. At the point when AI is able to do all of the tasks a human can on a computer, it will functionally be AGI and able to conduct the same AI research that we can. Should this happen, AGI will quickly scale to superintelligence, and then to levels so powerful that AI is best described as a god compared to humans. Just as humans have catalyzed the holocene extinction, these systems pose an extinction risk for humanity not because they are malicious, but because we will be powerless to control them as they reshape the world, indifferent to our fate.
Coexisting with such powerful AI requires solving some of the most difficult problems that humanity has ever tackled, which demand Nobel-prize-level breakthroughs, billions or trillions of dollars of investment, and progress in fields that resist scientific understanding. We suspect that we do not have enough time to adequately address these challenges.
Current technical AI safety efforts are not on track to solve this problem, and current AI governance efforts are ill-equipped to stop the race to AGI. Many of these efforts have been co-opted by the very actors racing to AGI, who undermine regulatory efforts, cut corners on safety, and are increasingly stoking nation-state conflict in order to justify racing.
This race is propelled by the belief that AI will bring extreme power to whoever builds it first, and that the primary quest of our era is to build this technology. To survive, humanity must oppose this ideology and the race to AGI, building global governance that is mature enough to develop technology conscientiously and justly. We are far from achieving this goal, but believe it to be possible. We need your help to get there.
I am not sure what this footnote means. The "cost of training per 1m tokens" is a very weird unit to talk about, since it depends on the model size and the GPU efficiency. I strongly suspect you meant to write something else and got mixed up.