AI's unsustainable growth model reveals systemic flaws in tech investment and valuation
Original framing: “Firms spent heavily on AI. Now rising costs are outpacing its value” — South China Morning Post
This AI cost crisis echoes past tech bubbles, such as the dot-com crash of 2000, where speculative investment led to overvaluation and eventual market correction. Understanding these historical patterns reveals the recurring nature of capital-driven innovation cycles.
The current AI cost crisis is not an isolated market fluctuation but a systemic failure rooted in the capital-driven innovation model of Silicon Valley.
This model prioritises rapid monetisation over long-term value, often at the expense of ethical considerations and social equity. By integrating Indigenous knowledge, strengthening public governance, and promoting open-source development, we can create a more sustainable and inclusive AI ecosystem. Historical parallels with past tech bubbles highlight the need for regulatory foresight, while cross-cultural perspectives offer alternative models for AI that align with diverse values and needs. The trickster lens reminds us that this moment of disruption is also an opportunity to redefine what we value in technological progress.