As AI Usage Soars, Why Isn't the Public Eager for Automation?

Introduction: A Puzzling Paradox

ChatGPT's user count is skyrocketing at a staggering pace, and major tech companies are racing to embed AI into every product imaginable. Yet an uncomfortable truth is surfacing — the general public's attitude toward AI is far less enthusiastic than Silicon Valley assumes. Nilay Patel, editor-in-chief of prominent tech outlet The Verge, recently published a widely discussed in-depth editorial and video with a blunt title: "People are not asking for automation." The piece has sounded an alarm, prompting the entire tech industry to rethink its AI narrative.

Core Argument: The Disconnect Between "Software Brain" and the Real World

Nilay Patel introduces a remarkably insightful concept — "Software Brain." He argues that a large number of tech industry professionals suffer from this condition: they habitually view the world as a system waiting to be automated, attempting to explain all human activity through information flows and data models. In their eyes, any repetitive task is "inefficient," and any step involving human participation is a "bottleneck awaiting optimization."

However, a vast chasm separates this mindset from ordinary people's lived experience. For most individuals, work is not merely an information-processing pipeline — it carries identity, social relationships, a sense of achievement, and life's meaning. When tech companies excitedly announce that "AI can write your emails, build your presentations, and summarize your meeting notes," many people's first reaction is not delight but a deep-seated unease: if all of this gets automated, where does my value lie?

Deep Dive: Usage Does Not Equal Acceptance

The editorial resonates because it exposes a truth the industry has deliberately overlooked: usage and acceptance are not the same thing.

First, passive use and active embrace are two entirely different things. ChatGPT's monthly active users are indeed growing steadily, but a significant portion of those users turn to AI tools because of workplace requirements, curiosity, or social pressure. That is fundamentally different from genuinely believing that "AI has made my life better." Social media usage is similarly staggering, yet extensive research shows that people's emotional attitudes toward social media are complex and often negative.

Second, the promise of automation frequently comes with a loss of control. When AI takes over content creation, customer communication, and even decision-making recommendations, users feel not liberation but a threat of "deskilling." Teachers worry students will stop learning to write, designers worry creative work will be devalued, and customer service representatives worry about being replaced outright. These anxieties are real and legitimate.

Third, the tech industry's narrative framework itself is flawed. Silicon Valley is accustomed to measuring everything by "efficiency," "productivity," and "scalability," but human society operates on far more than those metrics. An artisan baker does not need AI to "optimize" the baking process, and a community doctor's value is not defined by how many patients can be "processed" per hour. When tech companies apply Software Brain logic to redefine these professions, resistance is virtually inevitable.

Industry Reflection: Technology Adoption Requires a Humanistic Perspective

Nilay Patel's editorial is not a simplistic anti-AI stance; it is a profound critique of how the tech industry communicates. He is effectively reminding the entire sector: if you want AI to be genuinely embraced by the mainstream, you must stop selling it through the lens of the Software Brain.

This means AI product design and marketing must answer a fundamental question: is this technology augmenting human capability, or replacing the human role? The former will be welcomed; the latter will inevitably provoke resistance. Microsoft positioning Copilot as a "copilot" rather than "autopilot" reflects this awareness to some degree, but in actual product experiences, the line is often blurred.

Notably, public resistance to AI is already influencing the policy landscape. From the EU's AI Act to AI regulatory proposals in various U.S. states to the global wave of litigation over AI copyright issues, public sentiment is translating into real institutional constraints. If tech companies continue to ignore the public's genuine feelings, they may face a regulatory environment far harsher than anticipated.

Outlook: AI's Future Depends on Bridging This Divide

This editorial leaves the entire AI industry with a proposition worthy of long-term reflection. The pace of AI's technological advancement will not slow down, but whether it can truly integrate into society and earn broad public trust depends on whether the industry can escape the Software Brain trap.

Future AI products may need to focus more on "people" than on "efficiency." Rather than pursuing "full automation," the industry should consider how technology can serve human dignity, creativity, and autonomy. As Nilay Patel implies, people do not oppose technological progress — they oppose being treated as a system in need of optimization.

This conversation about the relationship between AI and humanity has only just begun. And its trajectory may matter far more than any model parameter upgrade.