I'm Happy That the AI Industry Is Being Constantly Mischaracterized

You reap what you sow, or something to that effect

Narcissus by Caravaggio, ca. 1600

I love Futurism. It’s a great outlet because the stories it features are low-quality in a way that’s easily detectable (unlike AI-written prose, which is often bad but you can’t always put your finger on why). It’s also great because all the people who care little about AI as a potentially beneficial technology—yet care a lot about getting anti-hype clout from it—will quote it endlessly. But the main reason I love this magazine is that it’s contributed to the emergence of a new kind of AI influencer; the type that constantly misrepresents the industry’s advances (sometimes unintentionally).

As the author of articles like “I’m Losing All Trust in the AI Industry,” I can hardly be accused of complicity, but above all, I owe myself to the truth, so here it is: The industry will do everything it can to sell you whatever it makes, but a considerable portion of it is legit anyway. I mean, you can log into ChatGPT and decide to focus on the edge cases it fails to solve or on the many things it can do that no other technology could do before 2022. It’s your choice; mine is to see both sides.

Nevertheless, I’m happy that the AI industry is being undercut by mischaracterization for two reasons: 1) it deserves this treatment because, since ChatGPT came out, they haven’t turned off the AI Hype Machine a single day, and 2) because this is the only possible counter-measure to that machine of hyperbolic promises: All information markets eventually find their equal opposite; once it became saturated with pro-AI evangelists, it was the turn of the opposite camp. Black and white, yin and yang. I like a universe in equilibrium, and Futurism with its pandemonium of parrots performs that humble, self-sacrificing, chaotic balancing act. It is a necessary evil.

(I don’t want to single out one news site, though; plenty are competing to take a portion of this anti-matter pie, including traditionally pro-technology publications, unwilling to let the hate wave pass without cashing in.)

But the situation is more serious than journalists carving out a space with a timely reading of the zeitgeist; in any case, their command of the mob deserves my praise. Perhaps the clearest sign that there’s a broader paradigm shift that will eventually reach the general public is that Gary Marcus, once touted as the loudest critic of the industry, is now moderate compared to his fellow skeptics. The New Yorker wrote on August 12th that, “In the aftermath of GPT-5’s launch, it has become more difficult to take bombastic predictions about A.I. at face value, and the views of critics like Marcus seem increasingly moderate.” You get one failed launch, and they kill you.

Indeed, let’s review why the GPT-5 launch “failed”, because it’s a great example of why the industry deserves to be mischaracterized and how that mischaracterization emerges in the first place.

A few topics dominated the conversation in the weeks following the demo: two mislabeled charts were mocked and meme’d on Twitter; the r/ChatGPT subreddit collectively demanded OpenAI to bring back GPT-4o because GPT-5’s personality was not flattering enough; the benchmark scores were good but not as strong as one might have expected, given the press coverage and CEO Sam Altman’s lofty comments; Altman admitted in an interview with The Verge that they “totally screwed up some things on the rollout.” So, basically, a slide blunder, angry customers due to a software update (which never, ever happens), and a CEO whispering in investors’ ears and being taken out of context.

It is fascinating, in a good way (good for me, not OpenAI), that an AI model that has nothing to envy any other (it’s the other way around: most others have something to envy GPT-5) has come to carry such a negative valence in the public opinion. A remarkably high number of people I interact with online think GPT-5 was a failure (a few techies know it wasn’t, and most people simply don’t care).

I called it, though. I knew this would happen. Four days before the release, I wrote that GPT-5 would be treated with “unfair disappointment”: unfair because I knew it would be good (and cheap), and disappointing because it faced impossible expectations. That’s the crux, right? Things are good or bad only against expectations. So, who’s to blame for this blatant misrepresentation of GPT-5? The intern who made the slides? Those addicted redditors for wanting the previous version? Benchmark designers for letting them max out? Interviewers for asking obvious questions?

Or perhaps the fault lies with Sam Altman and his cadre hyping up everything they do (whether it’s genuine enthusiasm or performative tribalism matters little, I’m afraid).

The entire industry is like this, by the way, not just OpenAI. They play master trickster without realizing that the Gods of marketing always claim their due: if perception rules the market, then what the general public preaches is gospel, even if it has zero resemblance to the underlying reality. And, regardless of whether this gospel is good or bad for the industry leaders, they only have one choice—echo the chorus. Altman didn’t want to tell The Verge that they “screwed up” GPT-5’s rollout (he probably didn’t even think it was true; what they screwed up was simply not realizing how many users are in love with GPT-4o, not the GPT-5 product itself). He knew his words would be used to push a narrative, but he had no way out. When you play the game as if words, not substance, are the only thing that matters, don’t be surprised when the world holds you to the same standard.

This phenomenon has been so ubiquitous in the last few months that it’s been a source of as many article ideas to debunk shallow criticisms against the AI industry as it has been to debunk shallow hype by the AI industry. You guys are making my job easy. And, actually, you are vindicating something I wrote a while ago that I thought would be harder to defend: extreme hypers and anti-hypers are often cut from the same cloth; both love to ridiculously overextend any seed of truth for social media clout. A sad state of affairs through and through.

But I prefer to laugh rather than cry.

When an MIT study says people who use ChatGPT are inevitably getting dumber and people doom-and-gloom about brain rot, I laugh despite having read the entire thing myself and having concluded, for there’s no other possible conclusion, that AI can deteriorate your cognitive capacity, but only under certain conditions, namely, relying on it excessively to solve problems before engaging your brain.

When another MIT study says that 95% of generative AI pilots are failing, and people share it everywhere because 95 is big, I laugh, despite knowing the sample is small (52 interviews), the methodology weak, and that the lead author himself argued the reason for failure is not the low quality of the technology but that workflow integration is hard when current models don’t learn contextually and continually.

When a METR randomized controlled trial (gold standard) concludes that “when developers use AI tools, they take 19% longer than without—AI makes them slower,” and people go crazy calling generative AI a dud even for the “killer app,” I laugh despite knowing that the specifics—the study was done on older models, with programmers familiar with their repositories, and didn’t account for human failure (e.g., thinking AI takes longer)—are essential to correctly interpret the results.

When an Apple paper says that AI thinking is an “illusion” and people use authority arguments (it’s Apple!) to defend it, I laugh despite knowing that the results are based on various misunderstandings: explicit reasoning traces don’t reflect the actual thinking of the model, and an “accuracy collapse” event is expected without a scratchpad—even in humans!

When Harvard Business Review reports, earlier this week, that “employees are using AI tools to create low-effort, passable looking work that ends up creating more work for their coworkers”—a phenomenon they coined workslop—and the new buzzword goes viral, I laugh, despite this result highlighting that people are lazy, uncreative, and seek cognitive offloading, not that AI is bad.

I laugh repeatedly because the AI industry deserves this treatment. It is unfair to the extent that it’s an incorrect assessment of the technology, but in another sense, they absolutely brought it on themselves. They earned all of it with their exaggerated promises and constant marketing hype. They distorted the information landscape first, so now when I see some skeptics and critics do the same thing, I laugh instead of crying (unfortunately, two wrongs don’t make one right). For if bullshit is their currency and empty words their weapon, they may as well be paid in kind.