To everyone who wants to go "you're literally 40 and arguing online" yes I am 40. I'm also disabled and unable to leave my house most days and for financial reasons not able to live in Seattle with all my real life friends. So I am bored and talk to people online. I'm also autistic so when people make blatantly factually incorrect statements I feel the need to correct them.
I don't know what you expect me to be doing at 40. Perhaps you are just bringing up my age so you feel better about losing the argument.
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Legal experts say employers must take AI-related religious objections seriously, as a 2023 ruling raised the bar for denying such accommodat
"The funniest possible outcome of the AI mandate era is about to be HR departments discovering that 'sincerely held religious belief' under Title VII has a much lower bar than they assumed, and Pope Leo handed every Catholic employee a written excuse," wrote Corey Quinn, a software-startup founder in San Francisco, on X.
Employers could wind up in court if they outright dismiss workers who request a faith-based exemption from using AI, said Ashley Herd, a former McKinsey counsel and head of North American HR who now advises managers and employers on workplace issues.
"Playing priest, and telling employees their request isn't legitimate, does not tend to bode well for companies," said Herd, also a cohost of the "HR Besties" podcast. "A jury doesn't like it when employees get made fun of by managers or HR."
"My religion means I don't need to do the job you hired me for" has been so wide spread. It's pretty funny seeing it used to fight against actual worker-hostile shit instead of just to screw over customers.
the issue with growing up in the 2000s and 2010s was like there was this really big push toward "accepting your weirdness" overall but they meant like idk wearing mismatched socks or something not being tangibly beyond the norm in any way shape or form
People can think what they think.
I can think what I think.
But I no longer feel the need to hand people the opening statement for the prosecution before I am allowed to describe my own life.
This is how I feel.
This is what I know.
This is the language that finally fits.
Somewhere between a Stewart Lee gig in Wexford and the rain on the drive home, I finally said the sentence I had never allowed myself to say
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If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:
"Gish Gallop" is the debating term for an opponent who makes so many claims that "it's impossible to address them in the time available" (it's named for Creationist Duane Gish, who was notorious for this tactic):
https://en.wikipedia.org/wiki/Gish_gallop
I think about the Gish Gallop whenever I'm asked to comment on AI.
Here's a recent example: last week, I had a pre-interview call with a radio producer who wanted me to come on a 13-minute segment to discusses "whether there's a problem with AI governance?"
I asked what the show meant by that: was it whether regulation of AI in commercial or public sector decision-making needed more oversight? Was it that the siting and provisioning of data-centers needed more democratic accountability? Was it that workers deserved more of a say in AI's impact on labor markets? Was it that customers and/or audiences should be able to opt out of AI customer service and AI slop? Was it about whether we needed some kind of system to prevent "runaway AI," in the event that we teach so many words to the word-guessing program that it wakes up, becomes God, and turns us all into paperclips?
"Oh," the producer said, "all of that."
In 13 minutes.
You see the problem, right? The AI industry has made so many claims about its past, present and future that it's almost impossible to have a reasonable critical conversation about it:
Shortly after I did the radio show, a newspaper editor who'd heard my segment got in touch to ask me if I'd write an 800-word op-ed about the subject, and also, could I address claims that "AI is the next Industrial Revolution?"
I keep finding myself on stages or panels where an AI-struck person says something like, "AI is the next industrial revolution. It will change everything we do. It will let anyone create important works of art. It will cure cancer. It will take us to space. It will solve the climate crisis."
Or sometimes it's an AI critic, but that person's criticism is really more "criti-hype," which is when you accept tech industry hype claims at face value, and then criticize them rather than questioning them:
AI criti-hype might ask what we'll do once AI takes all our jobs, or what we'll do when AI replaces the government or teachers or doctors, or what we'll do when AI can bypass our critical faculties and brainwash us or drive us all mad.
What do you say to that? I usually start by talking about whether there's any economic basis for keeping the AI servers running. AI is – by far – the money-losingest venture in human history, and it's practically impossible to overstate just how bad the AI business is. Not only does AI have terrible unit economics, those unit economics are getting worse over time:
AI's happiest customers cite cost-benefit calculations that depend on truly unimaginable subsidies from the AI companies, who are basically selling $100 bills for $5 apiece. It would be pretty amazing if you couldn't find people who'd extol the virtues of this arrangement. But when AI companies try to raise the price of those $100 bills to, say, $20 apiece, those ecstatic customers fly into a rage and start loudly proclaiming that AI is so inefficient that they will lose money on this arrangement:
Now, it shouldn't fall to me, a card-carrying member of the Democratic Socialists of America, to point out that capitalist enterprises require profits to be sustainable. You can't keep a business afloat by selling $100 bills for $5, nor for $20. You can't even make a profit selling $100 bills for $100 apiece! For a company to succeed, it needs to take in more than it expends.
AI is a money-furnace, and AI hustlers are clearly on the hunt for a way to force all of us to feed every dime we've got to it. Elon Musk's (now scuttled) gambit to make every pension saver in America bail out Grok (and Twitter, but at a mere $44b, the losses from Twitter are dwarfed by the titanic losses from Grok) was the most ambitious and shameless population-scale bag-holder scheme, but it's not the only one:
So before we ask about the capabilities AI will acquire in the future, we should at least give some consideration to the question of whether anyone will be willing to fund the development of those capabilities, and if so, where the money would come from? Likewise, before we ask whether AI can perform adequately in a job, we should at least consider the possibility that the company that sells that AI tool will be bankrupt in a year or two. When we fight about data-center buildout, we mostly talk about the (considerable) environmental downsides to them – but what about the question of what we will do with these data-centers after their owners go bankrupt, possibly even before they can be provisioned with electricity? How many laser-tag arenas do we actually need?
This is just one example of the questions that you could spend days unpacking, which make many of the other questions about AI a little silly. Like, even if you think there are limitless returns to scale for creating new AI capabilities, which means that if we keep the money-furnace burning it's only a matter of time until it powers a cure for cancer and the end of the climate emergency, how much money do we need to shovel into the furnace before that happens, and where will it come from? There are plenty of cancer researchers who have promising approaches they haven't been able to pursue due to funding shortfalls.
Unless there's some way to estimate how much money we have to give to AI companies before they cure cancer, we should at least consider the possibility that the true sum is "more money than exists now and that will ever exist." We should also consider that whatever benefits to cancer research that AI might deliver could come with a higher price-tag than the promising cancer research we're dropping because we can't find far more modest sums.
Likewise, it may be that the amount of CO2 that AI will generate atmosphere before it "solves climate change" will render Earth permanently unfit for humans, consuming the only habitable planet capable of sustaining human life in the known universe. I mean, I suppose that's one way to "solve" climate change, but it's a pretty drastic solution.
My next book (out later this month) is The Reverse Centaur's Guide to Life After AI. I wrote it because I was frustrated by other people demanding that I talk to them about AI, and then handing me 800 words or 13 minutes to address fifty nebulous, poorly supported claims about AI:
Now that I'm about to go out on the road with the book, I find myself frustrated anew by the need to try and pull together a compact way to address the broad, incoherent claims the industry uses to keep its bubble inflated and the money furnaces roaring. The series of essays I've developed here on Pluralistic are part of that effort:
But it occurred to me that this whole enterprise of making sense of AI needs to be framed in the context of the messiness of AI itself, and AI boosters' overwhelming, promiscuous and disjointed Gish Gallop.
This flimsy, half-assed logic is how the AI bubble got inflated in the first place. Supposedly smart people continually show a total lack of awareness of how jobs work at basically every level
The last few years of AI hype have been built on lies. Every company has conspired to make you think that AI is affordable and sustainable, that profitability was possible, that hallucinations were fixable, and that any problems you faced today were a result of being in “the early innings.” In reality, the AI industry has absorbed over a trillion dollars, effectively all tech talent, the majority of startup funding, the majority of media coverage, the art and work of millions of people, and been given chance after chance after chance to fix the obvious, glaring issues.
...
Four years and a trillion dollars in, AI is more expensive, its companies more cash-intensive, its products just as unreliable, and its boosters more desperate than ever to make you ignore reality as a means of empowering one of a few ultra-rich oafs.
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An AI data center full of AI GPUs is useful for AI and very little else. There are GPU-powered analytics tools, GPU-powered modeling and scientific applications, but the nature of GPUs — good at doing the same thing across big data sets in parallel, but bad at handling many little independent tasks — makes them impractical for most of what modern computing demands.
The entire Dot Com Redemption storyline comes from the idea that it “left behind useful infrastructure,” by which they mean “cabling that allowed hundreds of millions of people to use the internet.” While there was some amount of further construction and capex to handle, the end result was useful fiber that connected people with a faster connection at a lower cost.
No such story exists for AI.
If all we’re left with from this era is the ability for some people to write Python scripts without learning Python, this is still an egregious and horrifying waste of capital.
While it might allow some things to go theoretically faster, the overall economic impact of AI-generated code appears to be worse code, worse software, and massive, multi-million dollar bills from Anthropic and Cursor.
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You are paying for a tool. You are paying for software. You are a customer. Your job is not to explain to others why this is exciting, nor is it your job to cover up for its mistakes.
