Drawing on Cory Doctorow's insight, the immediate risk for workers isn't being replaced by a competent AI, but by an incompetent one. AI only needs to be good enough to convince a manager to fire a human, leading to a lose-lose situation of job loss and declining work quality.

The primary source of employee anxiety around AI is not the technology itself, but the uncertainty of how leadership will re-evaluate their roles and contributions. The fear is about losing perceived value in the eyes of management, not about the work itself becoming meaningless.

Many people's negative opinions on AI-generated content stem from a deep-seated fear of their jobs becoming obsolete. This emotional reaction will fade as AI content becomes indistinguishable from human-created content, making the current debate a temporary, fear-based phenomenon.

Human intuition is a poor gauge of AI's actual productivity benefits. A study found developers felt significantly sped up by AI coding tools even when objective measurements showed no speed increase. The real value may come from enabling tasks that otherwise wouldn't be attempted, rather than simply accelerating existing workflows.

Bill Gurley highlights a paradox where AI is perceived as a threat by employees who are not actively engaged in their work. Conversely, for highly motivated, curious individuals, AI acts as an incredible force multiplier for learning and productivity, making it the "best of times."

AI is positioned to become a universal scapegoat for economic anxieties. Executives can cite AI efficiency to justify layoffs and boost stock prices, even if business is poor. Simultaneously, workers can blame AI for job losses, regardless of the true economic drivers like tariffs or market downturns.

AI's impact on labor will likely follow a deceptive curve: an initial boost in productivity as it augments human workers, followed by a crash as it masters their domains and replaces them entirely. This creates a false sense of security, delaying necessary policy responses.

A UC Berkeley study found employees using AI worked faster and took on broader tasks, leading to more hours worked, not fewer. AI offloads menial labor, making jobs more purpose-driven and motivating employees to do more, which increases stress and burnout.

Resistance to AI in the workplace is often misdiagnosed as fear of technology. It's more accurately understood as an individual's rational caution about institutional change and the career risk associated with championing automation that could alter their or their colleagues' roles.