The AI Hype Reckoning Is Upon Us
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We're living in split realities.<br>There's what modern software is actually capable of, and then there's the gargantuan pile of "AI" hype, fraud, and bullshit our biggest tech companies (and their lazy enablers in the tech press) have shoveled down the public's throat for the better part of the last five years.
There's useful automation software that makes it easier to code, draft a new resume, or study vast repositories of scientific knowledge. And then there's a parade of technofascist hucksters lying to your face about the imminent arrival of omniscient, sentient, paradigm-rattling supercomputers.<br>There's a tremendous chasm between these two things. And everywhere you look you can see evidence that we've reached a breaking point when it comes to reconciling these two wildly-different realities.<br>Over at Ford Motor Company, executives recently fired a bunch of engineers and rushed madly into widespread AI adoption, only to discover the software made constant quality control mistakes, resulting in them having to rehire a lot of the engineers they previously shitcanned:<br>"Mistakenly, we thought that by just introducing artificial intelligence and ingesting the design requirements that we had, that would produce a high-quality product," he said.<br>Wonder where they might have gotten that idea.<br>"Over prior years, we didn't pay as much attention as we should have to the experience of our most knowledgeable engineers that have been with us through many product cycles," he said.<br>Weird.
There's a lot of this sort of thing going on. It turns out that firing all your employees, replacing them with extremely expensive software your deluded CEO thinks is magically sentient, and then layering it all on top of very broken and long-neglected systems results in fairly universally bad outcomes. Fancy that.
Microsoft is realizing nobody actually wants, uses or pays for the company's Copilot AI efforts, yet they're raising prices and firing people en masse because they're too far out over their skis on AI data center costs.
Facebook's pasty charmless manbaby of a CEO is realizing that nobody actually wants his company's half-assed "AI" services either, and that developments in "agentic AI" aren't developing as quickly as they'd claimed.
Uber's CTO is telling people they're not seeing meaningful production and efficiency improvements from AI despite blowing vast fortunes on usage tokens. Other companies are realizing that AI usage costs and mistakes are costing them significantly more money than the carbon-based meatbags they replaced.
OpenAI, long the poster child for AI innovation, is losing money hand over fist and its long-term survival seems unlikely. Other AI companies aren't actually making any money and aren't likely to start anytime soon. Meanwhile Elon Musk is doubling down on fraud while the stove is still hot, ensuring his mountain of opportunistic grift is bone-grafted to the economy and your retirement savings.
The warnings were there all along. They were just ignored because unethical men fresh out of ideas wanted to make gobs of money at the front end of a hype cycle.<br>A few years ago, corporate media owners also began rushing face-first into AI adoption in newsrooms, very excited about the potential to cut corners, automate their clickbait, and replace pesky human journalists with magic software.
They were so excited by the promise of not having to pay human beings a living wage or health insurance, they didn't really bother to make sure the technology worked or could be responsibly integrated into existing, broken systems.
It...didn't go well.
The AI outputs contained so many factual errors, instances of plagiarism, or outright falsehoods, that newsrooms found they had to pay significantly more money for human editors to come in and fix all the problems. You've seen the same problems bubble up in academia, health care, and everywhere else.
It's gotten so bad that innovation-drunk MBA types are now having to come to terms with the fact that automation software is neither sentient nor magic, contrary to the claims of Elon Musk and Sam Altman. This reconciliation is creating no limit of suffering and entertainment value, simultaneously.
And there's some absolutely fascinating layers to the dysfunction.
One recent study on AI "efficiency" out of Stanford found that the introduction of a flood of rushed and factually-incorrect AI slop into workflows actually results in human beings having to work harder than ever:<br>“When coworkers receive workslop, they are often required to take on the burden of decoding the content, inferring missed or false context. A cascade of effortful and complex decision-making processes may follow, including rework and uncomfortable exchanges with colleagues.”<br>As the Harvard Business Review notes, this hyperscaled introduction of pseudo-efficiency workslop results not just in new conflict and a bunch of wasted time for people,...