Politically Incorrect AI
At The Nerve News: Cory Doctorow: The people who tell you ‘AI is changing everything’ are lying
If Donald Trump ordered Big Tech to turn off all of your country's chatbots tomorrow, nothing would change. Every one of your country's ministries and corporations would chug on with nary a hitch. Households, too, though perhaps a few of the younger members of those families would have to do their own homework again.
Contrast this with what would transpire if Trump directed his tech giants to switch off your country's Office 365 access, or to brick your Android and iOS phones, or to killswitch your John Deere tractors. Your country would effectively cease to exist.
Having made a career in tech, I can vouch for this insight:
One person who's had a lot of opportunity to observe the shear between the stated business/AI situation and the real business AI situation is Nikhil Suresh from Hermit Tech, a consulting firm of "radically ethical data wizards" (that is, tech consultants). For a year and a half he has been talking to hundreds of executives — and, more importantly, their subordinates — about what, if anything, AI is doing for their businesses.
. . . Suresh says he's never seen a successful enterprise AI project: "Every single one – we have seen 0% success in a year and a half." Not one of their clients would face a business challenge if OpenAI went out of business tomorrow. The problem most companies struggle with is that they're "terminally bad at running software projects effectively". Adding AI to the mix doesn't solve this problem – it just adds a whole new range of ways that software deployment can fail.
Chatbots don't help. The internally facing chatbot that's supposed to help employees figure out how to navigate the business sucks because it is only as good as its training data – the business's documentation of its own processes. Businesses suck at documenting their processes. Customer-facing chatbots also suck. They either can't solve your problem, or, when they seem to solve your problem, the "solution" goes nowhere.
Suresh recounts his sole positive customer-service chatbot experience: a Mitsubishi chatbot with a natural-sounding, responsive voice politely took all the details of an automotive failure and promised him a callback. That callback never came, but Suresh is certain that Mitsubishi has logged this as a chatbot success story, even though the experience convinced him not to buy a Mitsubishi car.
One thing I'm noticing is that the unquestioning corporate adoption of AI is generating a peculiar inverse reaction in academic and literary environments, for instance at The Yale Review:
At The Yale Review, we are committed to publishing work shaped by human judgment, care, and responsibility. Generative artificial intelligence (AI) technologies—including large language models (LLMs)—are increasingly part of the cultural landscape, both as a subject of inquiry and as a tool in creative and critical work.
As an institution, we may occasionally use AI technologies to support internal tasks such as calendaring, research collation, and editorial planning in ways that we deem in keeping with our overall mission. However, all published writing is selected, edited, and fact-checked by human editors.
We welcome submissions that engage thoughtfully or critically with AI—especially when AI is central to the inquiry or deployed self-reflexively as part of a writer’s process. All work we publish must reflect the discernment and intent of a human author. Where AI-generated material appears prominently in a submission, we expect writers to note this in brief and explain how it was used.
More frequently, the policy is just plain No AI, as at the equally prestigious Baltimore Review:
About AI: Do we really have to say it? OK. No. We want to read work created entirely by humans.
What's puzzling here is that, as we see just above, AI is struggling to prove itself in business environments, but results from the real world indicate that the one field where it's been a roaring success has been academics, where it's turned out to be a whole new way to beat the system. It'll knock essay questions and comp assignments out of the park, and I strongly suspect that even the most respected journals are reluctant to feed recent years' issues through an AI detector. In fact, I'll bet they're terrified of what would happen if they announced a policy of henceforth doing this with all new submissions.I've been chuckling for two days over the result AI gave me in yesterday's post, when I asked it simply to generate a story that looked like Lydia Davis, one of the most respected current authors, had written it. It was a perect example of what an AI large language model can do. There was plenty of training data -- Davis's stories are all over the web. The large language model was capable of breaking out the highly visible elements of her narratives and style. The result was unintentional, but hilariously accurate, satire.
What do you think The Yale Review would do if I submitted an essay outlining the insights to be gained from yesterday's post? After all, they "welcome submissions that engage thoughtfully or critically with AI—especially when AI is central to the inquiry or deployed self-reflexively as part of a writer’s process." That might be a bridge too far, but I'm not going to rule this out, at least for now.






