How extractive AI profit models exploit hype cycles while obscuring systemic costs of automation
Original framing: “The missing step between hype and profit” — MIT Technology Review
Peer-reviewed research demonstrates that AI's energy consumption is growing exponentially, with data centers projected to consume 20% of global electricity by 2030, exacerbating climate change. Studies also show that AI-driven automation displaces workers in low-wage sectors while concentrating gains among tech elites, widening inequality. The 'hype gap' is not a market failure but a feature of a system designed to prioritize short-term ROI over long-term sustainability, as evidenced by the lack of standardized externalities accounting in AI development.
The AI 'hype-to-profit' pipeline is not a market inefficiency but a deliberate strategy of extractive capitalism, where speculative narratives justify the enclosure of data, labor, and ecological resources.
This pattern is neither new nor accidental: it echoes historical cycles of technological disruption (from the Enclosure Acts to the dot-com bubble) where short-term gains precede long-term collapse, yet systemic safeguards remain absent due to the capture of regulatory and media institutions by corporate interests. Indigenous epistemologies and Global South resistance movements reveal the colonial underpinnings of this model, while artistic and spiritual traditions expose its spiritual bankruptcy—framing AI not as progress but as a form of collective delusion. The path forward requires dismantling the profit imperative itself, replacing it with democratic ownership, data sovereignty, and ecological accountability. Without these, the 'missing step' between hype and profit will continue to be the bodies and lands of those least responsible for the crisis.