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How to think of AI as a normal technology

While Silicon Valley descends into existential panic over the imminent arrival of superintelligence, Alberto Romero offers a jarringly pragmatic antidote: treat artificial intelligence not as a god, but as a screwdriver. In a landscape saturated with doomerism and hype, Romero's central claim is that the "ontological uncertainty" paralyzing tech workers is a self-inflicted wound, distracting us from the tangible utility of tools that already exist. This is a necessary corrective for anyone feeling the tremors of the current AI boom, urging a shift from speculative dread to immediate application.

The Bubble of Existential Dread

Romero begins by dissecting the frenetic atmosphere of San Francisco, where a recent viral observation by venture capitalist Deedy Das highlighted a deep malaise. Das noted that while a small elite has achieved retirement-level wealth, the broader workforce faces a terrifying ambiguity: "The divide in outcomes is the worst I’s ever seen... Many software engineers feel like their life’s skill is no longer useful." Romero argues that while Das framed this as a financial crisis, the root cause is far more psychological. He cites former OpenAI researcher Nick Cammarata and rationalist Quiaochu Yuan to illustrate that the anxiety isn't about money, but about the "foreshocks of the singularity."

"The money is the concrete manifestation of a much larger eldritch hyperobject roaring into existence. The stormclouds gather. The winds whip. The world holds its breath."

Romero contends that this "SF bubble" creates a feedback loop where fear of the future prevents engagement with the present. He suggests that for those outside the epicenter, this anxiety is a "psychological infohazard"—a paralyzing truth that, even if true, renders you incapable of acting. This framing is effective because it reframes the "permanent underclass" narrative not as an inevitable economic outcome, but as a mindset that blocks agency. However, critics might note that dismissing these fears as purely "ontological" risks underestimating the very real structural shifts in labor markets that are already displacing workers, regardless of whether they believe in the singularity.

How to think of AI as a normal technology

The Screwdriver Principle

To combat this paralysis, Romero proposes a radical simplification: "You must fight the appeal of the SF bubble." He urges readers to separate AI as a tool from AI as a civilization-altering event. The core of his argument rests on the historical reality that the distance between invention and widespread impact is always longer than it appears. He invokes Amara's Law—"People tend to overestimate the effect of a technology in the short run and underestimate its effect in the long run"—to argue that while innovation is fast, adoption is slow due to human friction and bureaucracy.

"Even if superintelligence is eventually real, it’s not synonymous with omniscience or omnipotence. Like you and me, it will have to wait for the electrician."

This is a crucial distinction. Romero points out that even if the technology is revolutionary, the "bottleneck for effective change doesn't disappear; it moves somewhere else." He draws a parallel to the companion topic of "Information hazard," suggesting that worrying about the distant future is a trap. Instead, he champions the "screwdriver" analogy: "Whatever may happen next, it doesn’t retroactively influence what you can do today." The argument here is that the gap between current capabilities and human imagination is the real opportunity, not the gap between current AI and hypothetical superintelligence. By focusing on the tool, we reclaim our agency.

The Distortion of Proximity

Romero is particularly sharp when critiquing the voices closest to the technology. He argues that industry leaders like Dario Amodei and Sam Altman are often the worst judges of AI's meaning because they are "high on their own supply." Their warnings about existential risk or mass unemployment, he suggests, are strategic moves to influence regulation and investment rather than reflections of ground-level reality.

"They live inside the SF bubble, and so they see the future in real time—a distorted one at that—but perceive nothing about the present. They are tone-deaf."

He contrasts this with the reality outside Silicon Valley, noting that in places like Spain, "there’s literally no trace of AI anywhere." This observation serves as a powerful reality check against the media narrative. While Romero's dismissal of industry warnings as mere "hype-y anti-hype" is a bold stance, it requires nuance; these leaders do hold unique insights into technical trajectories, even if their public messaging is often performative. Nevertheless, his call to ignore the "fictions coming out of SF" is a vital reminder to evaluate technology based on its actual utility, not its marketing.

Reclaiming the Human Element

Finally, Romero addresses the ultimate question of purpose in a post-work world. He argues that even if AI becomes a "normal technology" that transforms the economy, it cannot conquer the "sacred places" of human experience. He quotes philosopher Shannon Vallor to challenge the notion of "superhuman" machines, asking, "Doesn’t granting the label ‘superhuman’ to machines that lack the most vital dimensions of humanity end up obscuring from our view the very things about being human that we care about?"

"Humans like humans. I don’t want to kiss a robot, however perfect the robot or the kiss might be."

This section ties back to the theme of "Post-work society" by suggesting that the solution isn't to fear the end of labor, but to recognize that our value lies in our imperfections and connections. Romero's conclusion is that we should stop viewing ourselves as "kings losing our kingdom" and start relishing the very human traits that AI cannot replicate. It is a comforting, if somewhat idealistic, counter-narrative to the cold efficiency of the algorithm.

Bottom Line

Romero's strongest contribution is the pragmatic reframing of AI anxiety as a barrier to utility, urging readers to focus on the "screwdriver" in their hand rather than the "god" in the clouds. However, the argument's vulnerability lies in its potential to minimize the immediate, non-existential economic disruptions that are already occurring for many workers. The most valuable takeaway is not to ignore the future, but to refuse to let a speculative future rob you of the present. Watch for how this "normal technology" framing holds up as the gap between AI's promise and its reliability continues to narrow.

Deep Dives

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  • On the Principles of Political Economy and Taxation Amazon · Better World Books by David Ricardo

  • Post-work society

    The article explores the existential dread of workers facing obsolescence, making the theoretical framework of a post-work society essential for understanding the shift from material anxiety to ontological uncertainty.

  • Information hazard

    The text describes the psychological torment caused by knowing a transformative event is imminent, which aligns with the concept of information hazards where knowledge itself creates danger or distress.

  • Economic rent

    The article's description of a small group accumulating massive wealth while others face stagnation illustrates the concept of economic rent, where value is captured through scarcity and position rather than productive labor.

Sources

How to think of AI as a normal technology

Hey there, I’m Alberto! Each week, I publish long-form AI analysis covering culture, philosophy, and business for The Algorithmic Bridge. Paid subscribers also get Monday how-to guides and Friday news commentary. I publish occasional extra articles. If you’d like to become a paid subscriber, here’s a button for that:

This one is on the house.

San Francisco, Silicon Valley, the Bay Area—epicenters of the AI boom—are crazy places for people who are going crazy. The past Saturday, a tweet by Deedy Das, partner at a venture capital firm based in SF, went viral.

It describes a malaise that afflicts the people building AI. Even if you are not one of them, it is interesting for anthropological reasons (edited for length):

The vibes in SF feel pretty frenetic right now. The divide in outcomes is the worst I’ve ever seen.

Over the last 5yrs, a group of ~10k people - employees at Anthropic, OpenAI, xAI, Nvidia, Meta TBD, founders - have hit retirement wealth of well above $20M (back of the envelope AI estimation).

Everyone outside that group feels like they can work their well-paying (but <$500k) job for their whole life and never get there.

Worse yet, layoffs are in full swing. Many software engineers feel like their life’s skill is no longer useful. The day to day role of most jobs has changed overnight with AI.

...

There’s a deep malaise about work (and its future). Why even work at all for “peanuts”? Will my job even exist in a few years? Many feel helpless. You hear the “permanent underclass” conversation a lot, esp from young people.

...

Living through a societally transformative gold rush in that environment can be paralyzing. “Am I in the right place? Should I move? Is there time still left? Am I gonna make it?” It psychologically torments many who have moved here in search of “success”.

Ironically, a frequent side effect of this torment is to spin up the very products making everyone rich in hopes that you too can vibecode your path to economic enlightenment.

Das framed this as a job/money thing to make it legible for his audience, but the underlying cause is not so much material anxiety as ontological uncertainty: “who am I in a world that’s about to suffer the greatest transformation in history?”

Nick Cammarata (former OpenAI researcher) and Quiaochu Yuan (a rationalism-adjacent guy) explained what I mean:

I ...