Generative AI is widely marketed as a time-saving convenience, but it is actually trapping knowledge workers in a cycle of endless production. Rather than freeing up time, AI drastically reduces the cost and effort of creating content, which in turn leads to an explosion of low-quality output—or “slop”—that overwhelms human capacity to review and absorb it.
The AI Productivity Paradox
Despite trillions of dollars in investment, macroeconomic data shows minimal bottom-line productivity gains from AI. Studies that do show improvements often omit crucial caveats, such as the fact that productivity gains are mostly limited to novice workers. Conversely, experienced professionals, such as open-source developers, have actually been shown to experience slowdowns and a stark gap between perceived and actual efficiency.
The Burden of Verification
While AI rapidly generates documents, code, academic papers, and job applications, it essentially shifts the human workload from creation to verification. Research indicates that the time saved by using AI to generate content is almost entirely consumed by the hours needed to review and correct its output. AI-generated content suffers from high rates of hallucinations, confident inaccuracies, and security bugs, which heavily compounds this verification burden.
The Jevons Paradox and Worker Exhaustion
The article applies the Jevons paradox to knowledge work: as the “cost” (in time and effort) of producing output decreases, the organizational demand for that output skyrockets. This creates an “AI Efficiency Trap.” Workers face inflated expectations, are forced to juggle multiple AI threads, and suffer from high rates of burnout. Employees are drowning in an infinite supply of AI-generated “workslop,” which actively erodes workplace trust and leads to skill atrophy.
Conclusion: The Illusion of Efficiency
The author concludes that AI operates much like a strip mall—sacrificing curation and quality for fast, cheap abundance. Current corporate investments in generative AI far exceed realistic returns, especially given estimates that only a tiny fraction of economic tasks can be profitably automated. Ultimately, AI has not made workers less busy; it has merely buried them in a massive volume of low-grade artifacts demanding finite human attention.
Mentoring question
Are the AI tools you use actually reducing your overall workload, or are they simply shifting your time from creating content to verifying and managing an increased volume of output?