Scott sent me this Twitter link of a rural Texas voter, here’s what she said:
MSNOW: “You are willing at this point to forego basically EVERY conservative issue, and let the Senate fall into the hands of Democrats if that’s what it takes to kill [AI] data centers?”
Hood County TX Conservative voter: “Yup. My entire community is going to break ranks.”
Underneath that link the first time I looked (not now, of course, since Xitter) were some tweets from Virginia State Senator L. Louise Lucas roasting Abagail Spanberger:
If you don’t want to click on the video, it’s just Spanberger starting to talk and then a high-pitched whine taking over. Here’s Lucas’ take on the negotiations in Virginia:
I’m not anti-AI — I use it in my work and it’s helpful. I got a free subscription to Google’s “Pro” Gemini edition, and as far as I’m concerned it’s basically doing 10X the amount of AI that I want it to do. I don’t need every email summarized. I don’t need Gemini’s suggested AI response for every email. I don’t need every search result summarized by AI. If we got to a point where users were allowed to pick and choose when they interact with AI, many, many fewer cycles would be used at these massive data centers.
Cory Doctorow has a piece about this that I thought was pretty good. It’s behind a soft paywall so a big excerpt:
I’m not saying AI is not real. It is. A decade ago, computer scientists tried applying existing statistical methods in novel ways, and made a substantial breakthrough in machine learning. These techniques turned out to be highly scalable. When we simply apply the same techniques with increasing intensity, we got better and better results.
But these results have since plateaued, and anything that can’t go on forever eventually stops. Some of these results lend themselves to being turned into products. But in the absence of the bubble, we would call these products “plug-ins”.
My first word processor was a programme that came printed in the pages of a magazine, which I had to retype into my computer. In the 45 years since then, my word processors have got new features all the time. Many of these features are useful – and some of them are awfully stupid.
Now we have a new word-generation plug-in (ChatGPT, Claude etc). If you like that plug-in, good for you (please don’t send me its output, though… ugh). The existence of a new plug-in, even an exciting one, does not militate against feeding all the writers into a wood chipper, nor does it herald the imminent emergence of a new machine god that might enslave the human race.
And that plug-in isn’t worth $1.4tn. We can tell, because no one is willing to pay the true cost of the “tokens” the AI giants sell. As these giants get ready for their flotation and attempt to clean up their balance sheets by raising prices, their largest enterprise customers are imposing strict limits on AI usage.
Twenty-five years ago, I lived through the dotcom bubble. Many people point to that bubble and insist that even though that market frothed with silly firms, the underlying ideas were sound, and a bet on the web was a good one. It is argued that this means AI must be a good bet, too. This is an obvious fallacy: the fact that one thing stopped losing money and became profitable doesn’t imply that losing money is itself an indicator of long-term growth.
Unlike AI, the web had brilliant unit economics. Adding a user to the web made the web more profitable. Every new AI user makes the AI sector lose more money. Each use of the web made the web more profitable. Every time you prompt an AI, the company supplying it loses money. Every generation of the web was more profitable. Every new generation of AI loses more money than the last one.
AI then is a normal technology, a grab bag of plug-ins that different people will find useful to different degrees. But it is also an abnormal bubble, vastly larger and more dangerous than the tech bubbles that preceded it.
AI isn’t going to do your job, though an AI salesman might well convince your boss to fire you and replace you with an AI that can’t do your job. And AI might still destroy your livelihood, when 35 per cent of the stock market collapses overnight. (Anything that can’t go on forever eventually stops.)
Doctorow makes the point that one of the big attractions of AI for our tech overlords is the promise that AI will let them replace human employees. This will end badly, but I’m sure it will happen before employers realize their mistake and back down. We’re going to go through a big “AI correction” both in the stock markets and in the way that corporations look at AI. That correction will involve the need for many fewer data centers. There’s no reason for Democrats to support a single tax break or any other legislation that doesn’t make a data center pay its way. The fact that most Democrats are doing the opposite just shows another way in which the party is broken. Credit to Pritzker and Lucas for bucking the trend.
