Cross-posted to Lesswrong

Introduction

Several developments over the past few months should cause you to re-evaluate what you are doing. These include:

Updates toward short timelines
The Trump presidency
The o1 (inference-time compute scaling) paradigm
Deepseek
Stargate/AI datacenter spending
Increased internal deployment
Absence of AI x-risk/safety considerations in mainstream AI discourse

Taken together, these are enough to render many existing AI governance strategies obsolete (and probably some technical safety strategies too). There's a good chance we're entering crunch time and that should absolutely affect your theory of change and what you plan to work on.

In this piece I try to give a quick summary of these developments and think through the broader implications these have for AI safety. At the end of the piece I give some quick initial thoughts on how these developments affect what safety-concerned folks should be prioritizing. These are early days and I expect many of my takes will shift, look forward to discussing in the comments!

Implications of recent developments

Updates toward short timelines

There’s general agreement that timelines are likely to be far shorter than most expected. Both Sam Altman and Dario Amodei have recently said they expect AGI within the next 3 years. Anecdotally, nearly everyone I know or have heard of who was expecting longer timelines has updated significantly toward short timelines (<5 years). E.g. Ajeya’s median estimate is that 99% of fully-remote jobs will be automatable in roughly 6-8 years, 5+ years earlier than her 2023 estimate. On a quick look, prediction markets seem to have shifted to short timelines (e.g. Metaculus^[1] & Manifold appear to have roughly 2030 median timelines to AGI, though haven’t moved dramatically in recent months).

We’ve consistently seen performance on benchmarks far exceed what most predicted. Most recently, Epoch was surprised to see OpenAI’s o3 model achieve 25% on its Frontier Math dataset (though there’s some controversy). o3 also had surprisingly good performance in coding. In many real-world domains we’re already seeing AI match top experts, they seem poised to exceed them soon.

With AGI looking so close, it's worth remembering that capabilities are unlikely to stall around human level. We may see far more capable systems potentially very ...

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