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On Monday, I'm recording a podcast with @ketanjoshi.co. He's going to present the strong version of THE CASE AGAINST (AI) DATA CENTERS. Tech company fuckery, discarded green pledges, the rush to gas, the empty promises that AI will help reduce emissions ... all of it. Got questions?

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An early argument for support was solving big problems for the good, e.g. cancer cure. Bespoke models are more efficacious for many of these and current capabilities seem adequate to speed less daunting problems. That moves the constraint to the physical testing etc. Are these assertions true?

could we advance LLM technology at 1/100th the scale, committing a fraction of the externalities if the firms didn't have to race to have the best model and win a monopoly share on the market?

If #AI was so "intelligent", why doesn't it shut itself down after so much proof of it's lack of intelligence..... over and over and over? That question is only 1/2 sarcastic. If it can't catch it's own errors, all it is is a bad video game. www.ms.now/rachel-maddo...

ms.nowKennedy’s HHS appears to have been caught misusing AI — for the fourth timeThe Department of Health and Human Services has suffered more than its share of AI-related humiliations. The list, alas, is still growing.

btw - If we had programmers that refused to use (or code/test) error handling functions, they wouldn't have a job because we wouldn't have customers/employers. #AI is code!

Like all high capex businesses in history early builds always lead to a collapse & consolidation. We can be absolutely certain that much of we build will become stranded assets. China is ensuring that their clean energy & grid assets will maintain their value. We could do the same but aren’t. Why?

Q2 - the downtown Vancouver data centre proposal would decarbonize the [nat gas based] steam system. A rare symbiosis. Are any US district energy systems (NYC?) even big enough to absorb all of a hyperscale [GW] data centre's waste heat at midwinter peak? resourceworks.com/data-centres...

resourceworks.comData centres for district energyVancouver’s single largest carbon emitter could be cleaned up by the very thing residents just protested.

Has everyone forgotten why we ditched mainframes for personal computers in the 1980s? I think of data centers as the new mainframes. So the question is: do you really need giant data centers for this? Or is just a way for the VC world to suck more money out of everybody?

@ketanjoshi.co do you know of any politicians anywhere in the world who have made an effort to increase their tech literacy to really understand their decisions? Do their staff know and actually advise them? Or do they drink any Kool-Aid with the words ‘increased productivity’ on the label?

my question is maybe dumb but why aren’t more data centers run on clean energy. seems they would be less friction for them is they used more solar wind and batteries

Q1. If AI capability capability keeps on its exponential curve, is it a good climate moonshot investment? (Moonshot as no one can predict the problems it could solve) Q2. Does increasing elec demand help build a v large clean elec grid and the possibility of abundant (and v cheap) clean enegy?

If all data centers were required to build on-the-grid additional clean energy and storage (or VPP) to match their 24/7/365 hourly load and pay for grid upgrades before interconnection permit (and behind the meter BYOP was illegal), would the data center boom be a good thing for climate progress?

Ask him if he understands the paradoxical moral vs material survival drives of the human brain. When people understand how cognition works enough to see the global-emotional system, the profiteer simulator brains (AI) trigger moral disgust because of their material harms. That's moral clarity

From someone in WI, can you cover water impacts? Ex: water consumption, water pollution, impact on Great Lakes Even if Data Center energy is fully clean, the water stuff worries me

There is some research ongoing about emissions abatement, using reclaimed/oilfield produced water for cooling, etc. How much of a difference can we realistically make on emissions and water use reduction vs nibbling around the margins?

Is it only ai datacenters we are concerned about? How about crypto datacenters? Or cloud hosting datacenters? Or networking datacenters?

"We need to keep up with China." We are: we are investing way more than them. But me (and the system) support some data center investment. Other than outright bans, what sort of sand-in-the-gears would work? Big greenhouse taxes? Distribution & grid charges? *Tax on output*? 1/2

Do we have the technology available to have data centers that don’t emit GHGs, don’t pollute air & water, don’t add heat & noise to neighboring communities. i.e. can build them with no adverse environmental health impacts

What's their plan after they've covered the world in data centers? Are you guys going to get into network states and freedom cities at all? Are you familiar with Ann Pettifor author of The Global Casino? Are you going to talk about credit/debt at all?

Is there any reason not to laugh anyone who spouts eventual geo engineering as an eventual pie in the sky climate solution out of the room, or at least avoid giving them any credibility with a platform for their dangerous, denialist, delays to excuse burning fossil fuels for AI?

Would he reconsider his stance on AI if it was reprogrammed to create armies of self-replicating robots that systematically stole everyone’s ICE vehicle tire rims and melted them down to make new pv module frames and server racks?

Tangential, but... talking point was used a lot that AI would solve climate change. Is there anything there? Technology or process that AI could conceivably help develop that would have an impact? Like drug development where there is at least real potential. Or is that all just full on BS?

How will companies or governments handle the increase of e-waste generated by AI data centers? I’d love some discussion of environmental aspects that goes beyond energy/water and into the materials used/discarded due to the build out.

Any good strategies of how to preserve or open source-ify the “good” applications of AI/ML (machine learning for research purposes, and the data analysis helper programs like ugh Claude code) when the bubble bursts?

Picture the morning the API key dies. The team that still has eval fixtures, prompt files, and a local runner in git can keep working that afternoon. The team that only had the SaaS tab is stuck. That folder is usually what is worth open-sourcing.

Personally, I'm skeptical about the practicality of suggestions that we "just" organize around projects that are some form of "*first*, does this particular project meet some idealized perfect standard of decarbonization first and foremost", and I worry that (especially local) datacentre opposition

might actually be helping establish the playbook for opposition to the many other components required to "electrify everything" that will also require a lot of power, land, grid connection, heat dissipation etc. [and, separately, I wrote a separate multi-post suggestion for the interview, which...

This strikes me as a very odd guest/subject, unless you are planning to also have an episode making the opposite case *or* you make clear whether "Tech company fuckery, discarded green pledges, the rush to gas, the empty promises that Al will help reduce emissions" is your position or you are just..

...hosting an episode to give a forum for a guest to make the case/possibly sell you on the case. More on that in a bit, but I also think upfront you should get Ketan on record as to his personal assessment of Al generally and the frontier LLM/ GenAl model capabilities - current and, say, 18 months

I assume you'll cover what we're talking about when we say "data center" & why they're being built & why these locations. Are they really needed at all to do what they're supposed to do, is there a way to do that w minimal impact? Comparable to ordinary light industry. Or is heavy industry closer?

Maybe some perspective on the case for datacenters in Europe, such as the Google-case in Finland. Why do tech companies even bother trying to build there, with all their governance? And also; is there truly a way in which (ai) datacenters can be net positive for net stability when using smr's?

As someone who worked in government to resolve 2 banking crises, I’d like to know if this bubble is repeating the mistakes of the past - that being financial institutions loaning money for things they don’t understand? Or is this mostly a kind of check kitting scheme - loaning money to each other?

Q: Some AI (eg for research) can make sense. So some data centres capable of AI processing can make sense. But how to *practically* prioritise those over AI-slop data centres? Through public ownership of the former?

One scenario of how the data center gold rush ends (or winds down) is with one or more major companies going under. That way lies risks of recession, bailouts, etc. Another scenario involves democratic decision-making that manages the scale/pace/locations of buildout. What might that look like?

How much actual physical steel-in-the-ground non-fossil energy infrastructure have AI companies paid for since 2023? Did any of it displace existing fossil fuels, or did it just avoid hypothetical fossil fuel burning that might've existed in a parallel universe? Did any of it reduce pollution.

No steel in the ground yet, but the power purchase agreement with Google's 1 GW data center in Michigan has them paying for at least enough renewable and batteries to serve the facility. Likely they'll be subsiding some renewable grid power. (Depends on their actual usage.)

How many permanent jobs does a 1 GW data center (typical cost: $30 to 60 billion or so) bring to a community? Are the jobs... good? Or are they, like, security guards standing around all night being driven slowly mad by the incessant mechanical whine of a massive air-conditioned computer warehouse

For comparison, how many permanent jobs would $30 to 60 billion worth of factories making batteries, solar panels, or EVs bring to a community.

I sometimes hear data center supporters say they're good because we need them to stream Netflix or check weather apps. How do such conventional data centers compare in scale to modern AI data centers? How much of the current data center growth is to serve AI vs non-AI purposes?

One of the issues with AI data centers is apparently very rapidly fluctuating load. This seems like a readily solvable issue that is likely only a problem because the techbros can’t be arsed to do anything that slows things down one iota, but I dunno. I’d be interested to hear his perspective.

Related: Some people say the current surge in electricity demand growth comes only partly from data centers, and also comes from electric vehicles, heat pumps, induction stoves, and so on. How much of the current surge in electricity demand growth comes from those other things vs data centers?

You two are among the rare few media people who don't make money off ads or event stuff, so can speak relatively freely without fear of alienating a company such as Google or Anthropic that might otherwise be a big client of yours. I think you should discuss how that influences your conversation on

this topic. Also how media outlets that depend on such revenue streams may or may not bias coverage to appear friendly to businesses, and particularly to the big rich businesses that are build, use, or power data centers. I suggest discussing this fairly early, because I suspect this conversation

Many energy people who used to describe themselves as climate activists or renewable champions have chased the AI gold rush and are now getting rich off of the data center boom, pollution be damned. Should anyone take these people seriously ever again when they talk about clean energy or climate?

Are tech companies all secret greens who are just building gas power plants at their data centers to keep Trump's handlers happy while they're in power? Do they all prefer renewables and batteries in their quiet hidden hearts?

If we could wave a magic wand and instantly produce electricity transmission lines wherever we wanted them, for free, do you think data center developers would all start using grid power (possibly supplied by renewables) rather than natural gas combustion turbines?

More specifically, if they really *would* start using grid power, would they all sign power purchase agreements with clean power plants, or (better) *additional* PPAs that support genuinely new clean capacity addition, or (still better) *additional* PPAs with something like 24/7/365 power matching?

(Note all the off-ramps here for a switch from on-site gas turbines to grid power not actually being helpful. Not switching to grid power because gas is faster or manlier or whatever; just buying vanilla grid power, however coaly or gassy it might be; non-additional PPAs; etc.)

Every Republican presidency this millenium has ended with the US economy in shambles: Great Recession after Bush, covid and inflation after Trump I. What odds would you place on Trump II ending with a recession or depression induced by one or more massive AI company collapses?

Follow-up: What could or should policymakers be doing now to prepare for a possible collapse of a massive AI company? In particular, what alternatives are there to using taxpayer money to bail out "too big to fail" AI companies, chip makers, or other firms entangled in the web of AI finance?

There are efforts among researchers and open-source communities to create open-weight and open-corpus models. Other researchers are working on ways to reduce the compute required to train an LLM by 10x or 100x. If one or more of these efforts pan out, what happens to AI companies/the economy?

AI has its flaws, but it also has its uses. Uses for good, and uses for bad. Could you talk about how AI companies take credit for the good uses while downplaying or ignoring the bad uses? What are some bad uses, for example in accelerating discovery/exploration of new oil and gas fields? Has anyone

investigated how the impacts (pollution, etc) of the bad uses of AI might compare to a) the direct "footprint" of AI (data center gas, etc), or b) the impacts of the good uses of AI?

AI companies have spent ~$1 trillion so far. That's about 1,000 years worth of the annual research expenditures (inflation adjusted) at Bell Labs, the most successful research lab ever. Are the things LLMs can do today, or might do tomorrow, worth the opportunity cost of a millenium of Bell Labs?

Kevin J. Kircher@kevinjkircher.com

By my napkin math, total Bell Labs research expenditures from 1930-1980 were on the order of $50 billion in 2026 dollars. AI companies have spent ~$1 trillion so far: The equivalent of ~20 Bell Labs histories. In its history, Bell Labs researchers discovered the transistor, the solar cell, the laser

Alt frame: The $1 trillion AI companies have spent so far could have paid for 10 million years of work at $100,000 annual salary. What could we have created with a decade of labor from one million experts? What would AI need to do to pay off that opportunity cost in discovery, creativity, progress?

Data-driven prediction and decision software has been around for decades. We called it AI in the 90s, big data in the 00s, machine learning in the 10s, now AI again. Can you distinguish today's large language models from this lineage, eg in scale and purpose, and talk about how rolling all this

software under the same umbrella "AI" term as LLMs affects how people think and feel about AI, especially its potential to do good stuff for climate?