The AI industry has been in full-on hype mode for some time now. We’re told that AI will solve climate change. That it will reach human-level intelligence. That we will no longer have to work. But in 2025 some people began to push back against this narrative. Was AI actually making life better in any meaningful way? There were rumblings of a possible bubble. People were starting to have doubts.
At MIT Technology Review we decided to address this moment head-on with a new editorial package called “Hype Correction,” a term we coined to explain the resetting of expectations around this technology. Our expert AI reporters used their deep technical understanding of the underlying models to give our audience a fresh look at what generative AI is really capable of today, what it’s not—and what to expect as we look ahead.
As senior AI editor Will Douglas Heaven wrote in the package’s intro essay, “You can’t help but wonder: When the wow factor is gone, what’s left? How will we view this technology a year or five from now? Will we think it was worth the colossal costs, both financial and environmental?”
Drawing on that reporting as well as a sophisticated understanding of AI itself, in the opening essay Heaven broke down where we are with AI into four easy-to-digest takeaways that avoided scaremongering and boosterism. His essay became essential reading for anyone who wanted to understand where this technology is heading.
Elsewhere in the package, senior AI reporter James O’Donnell examines Sam Altman, the ultimate AI hype man, through the medium of his own words, which in many cases have set the agenda for what we think AI is or might be capable of. The package also included a hype-free explainer from freelancer Alex Heath describing what an AI bubble might look like. His piece lays out what the term means in this context and what we might expect to happen, using his unique access to tech leaders like Altman and Mark Zuckerberg to capture the current mood around the industry.
While they laid out the stakes of unfettered AI hype, Edd Gent went deep on coding with an intensely reported and researched feature that aimed to unpack how developers were using the technology. While there had been many news stories about coding and AI, no one had really tried to answer the biggest questions: How are developers actually using AI tools, and do they really make them more productive? What he found was surprising and ran counter to conventional wisdom.
Finally, Tarbell reporting fellow Michelle Kim analyzed one of the biggest claims in the AI hype cycle: that AI will completely eliminate the need for certain classes of jobs. If ChatGPT could pass the bar exam, surely that meant it would replace lawyers? Well, not yet, and maybe not ever, as Kim explains.
MIT Technology Review’s Hype Correction package was a critical look at where we are today, what AI makes possible now, and where we go next.
