Activist and author Cory Doctorow argues that the tech industry’s grand narrative surrounding generative artificial intelligence—framing it as an unstoppable, world-altering inevitability—is a deliberate rhetorical strategy designed to force compliance, stifle regulation, and protect monopoly interests rather than a reflection of technical reality.
Deconstructing the Technologist Determinism Trap
We’ve been here before. Every major technological shift of the past three decades arrives wrapped in the same evangelistic wrapping paper. Whether it was blockchain, web3, or the current wave of large language models relying on heavy neural network parameter scaling, the playbook remains identical. Tech executives and venture capitalists lean hard into technological determinism. They pitch tools not as optional software products, but as environmental forces akin to weather patterns.
Doctorow’s critique cuts straight through this marketing veneer. By treating AI as an inevitable destiny, executives effectively disarm policymakers. If a technology is bound to happen anyway, trying to regulate its data collection practices, copyright infringements, or labor impacts looks futile. It transforms corporate choices into laws of physics.
The reality underneath the hype cycle is far more mundane. Modern machine learning models depend entirely on inputs shaped by human choices. They ingest vast datasets scraped from the public web without consent, run on massive server farms requiring immense municipal resources, and rely on centralized cloud infrastructure controlled by a handful of dominant monopolies. None of these components are accidental. They are engineered outcomes.
The Economics of Enshittification and Platform Lock-In
To understand why tech leaders push the inevitability narrative so aggressively, look at how modern platforms operate. Doctorow coined the term “enshittification” to describe the decay phase of digital platforms. First, services throw subsidies at users to build market share. Then, they pivot to squeezing third-party developers and content creators. Finally, once everyone is locked into the ecosystem, they squeeze the end users themselves.
Generative AI tools fit this trajectory perfectly. Companies are currently burning billions in venture capital and enterprise funding to subsidize token generation costs, offering cheap API access and flashy consumer interfaces. But this phase won’t last forever. The underlying infrastructure—dominated by specialized AI accelerators and proprietary software layers—is designed to drive deep platform lock-in.
When enterprise IT departments bake proprietary LLMs into their core workflows, migrating away becomes technically and financially prohibitive. The narrative of AI inevitability accelerates this adoption curve. It pressures corporate boards to buy in early out of fear of missing out, feeding the very monopolies that will eventually raise prices and degrade service quality.
Regaining Agency Over Our Digital Infrastructure
Accepting that AI is an inevitability means surrendering our capacity to set rules. But history proves that societies can and do redirect technological trajectories when they recognize human agency. Antitrust enforcement, stringent data privacy laws, and robust copyright protections are not anti-technology measures. They are democratic tools designed to prevent corporate capture.
As developer communities and open-source projects push back against closed ecosystems, the cracks in the monolithic AI story begin to show. Smaller, more efficient models running locally on edge hardware challenge the narrative that intelligence must be centralized in massive, proprietary data centers.
The choice isn’t between embracing every capability a tech executive rolls out or falling behind. The choice is deciding who controls the infrastructure, whose labor pays for the training data, and whether our digital future serves the public interest or corporate shareholders.
