The tech industry may have led us to believe in a near-future filled with automation and massive job replacements. However, since the release of OpenAI’s ChatGPT two years ago, predictions about the rapid obsolescence of knowledge workers have not materialized as anticipated. It was forecasted that our everyday tasks, from mundane emails to complex data analyses, would be rendered obsolete.

OpenAI’s CEO Sam Altman, in a serious tone, urged global leaders to brace for a potential era of mass unemployment, suggesting the necessity for universal basic income to support displaced employees. Yet, in the 18 months following his warnings, the expected technological upheaval hasn’t occurred. A recent report from Goldman Sachs raised doubts about whether the substantial investments in AI would yield significant returns. Furthermore, the much-anticipated GPT-5 has yet to appear, and the current model is impressive but has notable shortcomings in mathematics and reasoning capabilities, as illustrated by a humorous attempt to convince it of the incorrect spelling in “strawberry”.

This highlights a troubling reality: while generative AI might develop into more sophisticated forms of intelligence, it’s important to recognize that such advancements are not guaranteed. Many in the tech sector have adopted an overly optimistic viewpoint rooted in the belief of inevitable scientific advancements, reflecting a societal expectation that innovation is a straightforward path paved with cash and perseverance. This mindset is deeply ingrained, especially in Silicon Valley where investors perpetually seek the next groundbreaking venture.

However, history reveals a more complicated narrative. Technological progress often encounters plateaus and unfulfilled promises. For instance, advancements in jet-powered flight have stagnated, and the effectiveness of antibiotics has waned due to rising bacterial resistance. The long-held dream of limitless energy through nuclear fusion remains unrealized decades later.

In fact, fundamental physics has not seen significant breakthroughs since the 1970s, and in Silicon Valley, the one major innovation—the iPhone—has been followed by numerous misguided endeavors like Google Glass and the promises surrounding the metaverse. Even Elon Musk’s assurances about the imminence of fully self-driving cars have continually fallen flat since first being made in 2014.

It’s crucial to distinguish between genuine technological progress and unrealistic promises. Not every dismissed visionary is a misunderstood genius; many simply hold misguided beliefs. A recent analysis in The Economist challenged the popular “hype cycle” theory, which posits that every transformative technology undergoes phases of hype, disillusionment, and eventual validation. This cycle is exemplified by the dotcom bubble, which ultimately paved the way for the internet’s success, facilitated by earlier infrastructure investments. However, this trajectory is more the exception than the rule, with many innovations hitting dead ends after initial excitement—examples include carbon nanotubes and decentralized Web3 technology.

The allure of quick advancements benefits tech founders and often enables unprofessional conduct. For instance, Mark Zuckerberg’s mantra of “move fast and break things” suggests that ethical breaches are justified in the name of innovation, a sentiment that misrepresents the value of cautious progress. As industries rebrand their practices under the banner of “AI,” it obscures traditional concerns like cost-cutting.

Amidst these discussions, the media—shaped by over two decades of technological disruption—might assume the worst about emerging trends, recalling past misconceptions. The reluctance among journalists to draw parallels with early skepticism about the internet underscores a continued belief in the promise of technology. However, this has led to an environment rife with overzealous entrepreneurs, exemplified by figures like Sam Bankman-Fried and Elizabeth Holmes, who thrived on misguided faith in technology.

Ultimately, this isn’t to dismiss the potential of generative AI reaching its lofty goals—expertise varies on the matter—but it’s essential to remain open to skepticism. Notably, Facebook’s AI chief Yann LeCun, among others, argues that generative AI’s current flaws hinder its evolution toward human-like intelligence. The idea that technology operates through sheer magic is a fallacy; progress isn’t always a given. Perhaps, in an age increasingly reliant on scientific advancements, this skepticism is the most unsettling realization of all.