Tried a few different hairstyles on Hanako, still like the Nirv hair best (last pic). It just goes so well with the colors and low-key clowngirl makeup.
1. The court holds Google responsible for statements made by its AI, considering them Google's statements (search engines have limited liability for results in their engine as they're the words of other sites/companies/people), meaning when their AI lies/hallucinates they're liable for the defamation/harm resulting from those statements.
2. Google's defense that customers are generally aware of the lack of reliability and are responsible for fact checking was dismissed. As the court pointed out, that would "significantly diminish" AI Search's stated purpose and it can't be distinguished from Google's business practices/statements as a search tool.
3. Studies have found about 91% of Google's everyday AI responses are accurate, leaving millions of searches per HOUR with potential liability for falsehoods. 56% of correct responses weren't supported by the sources the AI listed. Both of which mean Google is now liable for a LOT more AI "errors."
4. Google was held liable for 80% of court costs in this case and this precedent is expected to reverberate around the world. This is a massive shift from the 3rd-party search provider role Google has previously played and it comes right as they've tied ALL searches to their AI search.
While I occasionally enjoy enhancing my Daz Iray renders using a local installation of Stable Diffusion, that's all I actually want from AI - denoising and enhancing images like a Photoshop filter. Everything else about AI is literally bullshit imo, all its claims about enhancing research are suspect, chatbots make people psychotic, and the only assistance an AI shopping helper gives is to big business.
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.
Love Wetton-era Crimson and have been an Asia fan for all the years Steve Howe was in the band, but I totally slept on U.K. and have been making up for it this year.
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