@hausfath
"A tireless chronicler and commentator on all things climate" -NYTimes. Climate research lead @stripe, writer @CarbonBrief, scientist @BerkeleyEarth, IPCC AR7 lead author / NCA5 author. Substack: https://theclimatebrink.substack.com/ Twitter: @hausfath
I have no idea of AI will ever become conscious, and I'm not sure that is a question that can be answered.
But I'm increasingly convinced that any sufficiently advanced AI will be indistinguishable from consciousness.
For more details on how a strong El Nino might impact 2027 temperatures, see my December post on 2026 and 2027 forecasts: www.theclimatebrink.com/p/my-2026-an...
The El Nino cometh.
This would push up our estimate for 2026 global temperatures (though its still unlikely to surpass 2024 as the warmest year), and make 2027 very likely to be the warmest year on record given the historical lag b/w ENSO and surface temp.
Time series plot depicting predicted Nino 3.4 region ocean temperature anomalies from the latest (Mar 2026) ECMWF ensemble. It depicts an extremely rapid rise in such temperatures, from modest negative anomalies to strong positive anomalies, by mid-summer 2026--indicative of a transition from weak-moderate La Nina conditions to moderate-strong El Nino conditions over just a few months.
Whew.
All signs are increasingly pointing to a significant, if not strong to very strong, El Niño event. I'll have more to say in coming weeks & months, but for now I'll just say that this is increasingly likely to become a major regional-to-global climate driver in 2026-2027.
That being said, the error bars in our study are large enough (0.27 [0.2–0.4] °C per decade) to encompass the new Foster and Rahmstorf estimate.
I'd say the increase that we estimated in Forster et al 2025 is closer to 40% than doubling (as the Foster and Rahmstorf method is imperfect at removing short-term natural variability): essd.copernicus.org/articles/17/...
That being said, clean energy investment has grown rapidly, and in 2025 the world spent more on clean energy ($2.3 trillion) than global military spending back in 2022 ($2.2 trillion).
One of my predictions during our Climate Brink end of year wrap-up was that 2026 might be the first year where global clean energy investment exceeds global military spending.
Unfortunately with recent wars we will likely have to wait a few more years for it to occur: www.theclimatebrink....
Highly recommend this Dean Ball piece on the Anthropic / DOD imbroglio over the weekend:
Important point: fuel costs go up, inflation goes up, interest rates go up, RE deployment suffers
For more (and daily updates to the data), check out the Climate Dashboard: dashboard.theclimate...
For 2026 annual temperatures, we are currently on track to see the 4th warmest year on record at 1.47C above preindustrial levels, but uncertainty remains large enough that it could end up anywhere between the warmest and 5th warmest year.
February 2026 was the 5th warmest February on record, at 1.5C above preindustrial levels in the ERA5 dataset.
This is not that surprising given weak La Nina conditions at the start of the year; February tends to be one of the months most sensitive to ENSO.
An obituary for the short-lived DOE Climate Working Group, from Andrew Dessler over at The Climate Brink. It arose with a bang and died with a footnote in the EPA's endangerment finding repeal. www.theclimatebrink....
Definitely one of my favorite lyrics.
Hmm… www.nytimes.com/2026/03/01/t...
📉 Global Temperature Dashboard - The Climate Brink / @hausfath.bsky.social
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Explore our article: climate.copernicus.eu/c3s-data-pow...
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Well well well. Be very interested to hear more from folk who are in the loop with this.
www.anthropic.com/news/stateme...
We need a bigger scale!
I do think there is a Jervons paradox risk here, where AI work becomes so cheap (compared to humans) that the amount of work being done dramatically increases. Its less us using it as a tool to enhance scientific output (in my case) and more swarms of autonomous agents doing tasks.
Yeh, I was considering adding a section on its performance in mathematical proofs, but my knowledge of that is mainly second hand. This was a really good discussion of what it can (and cannot) do there: www.daniellitt.com/blog/2026/2/...
AI has an impact, and we need policy to ensure that it is primarily powered by clean energy. And its still helpful to contextualize it relative to other things that we do in our lives.
All reasonable points, though I'd suggest that the median day with Claude Code here is a bit of an outlier (as it represents using the AI tool non-stop all day with many agents running), and even in that case uses less energy than their refrigerator.
Thats a good analogue. One thing I want to work on is improving the planning process to get better results; I was reading some folks at Anthropic who recommended having it ask a lot of questions when developing the plan rather than making assumptions solely based on the initial prompt.
How well it performs will depend on the problem, but I've found that it has gotten much better in recent models (and I myself am not always very good at this!).
Its usually a process of both reviewing the code it writes and looking through the resulting merged dataset for errors or remaining issues. Though I've increasingly started working with Claude Code to develop tests prior to running the analysis to catch potential issues.
I remember back in grad school spending weeks creating my own version of a simple climate model you and Nathan Myhrvold developed: github.com/hausfath/Sim...
It would be trivial to do with AI today, but you'd miss any understanding of "how" that (for me at least) was the most important outcome.
I agree, the impacts that this will have on the broader workforce (and early career folks) is really worrying. And I'm not comforted by vague platitudes from AI executives about future universal income / post-scarcity socialism. The more likely outcome is ever growing inequality...
Agreed; I worry that over reliance on these tools will lead folks to skip learning why and how things actually work. Thats the knowledge thats essential to determine if the AI tool is actually doing the analysis you want (vs its oft-incorrect interpretation of what you want).
Frugal compared to some people I know 😉