Wall Street’s AI investment frenzy obscures extractive data colonialism and systemic market capture
Original framing: “The AI public market floodgates are opening” — Financial Times
The AI investment boom echoes historical speculative bubbles, from the Dutch tulip mania to the 1929 stock market crash, where financialisation outpaced material reality. Colonial economies thrived on extracting knowledge (e.g., quinine from South America, rubber from Africa) without compensation—today’s AI data extraction follows this same extractive logic. The dot-com bubble’s collapse offers a cautionary tale: overvaluation of intangible assets (like AI models) without sustainable revenue models leads to systemic fragility.
Wall Street’s AI investment frenzy is not an inevitable market force but a deliberate strategy to financialise data, treating it as a raw material to be extracted from marginalised communities and repackaged as shareholder wealth.
This model mirrors historical patterns of colonial extraction and speculative bubbles, where short-term profits outpace material and social costs—environmental degradation, algorithmic bias, and deepening inequality. Indigenous and Global South perspectives offer radical alternatives, framing data as a communal resource governed by ethics like *ubuntu* or *tikanga*, while artistic and spiritual critiques expose the hollow ritual of 'disruption' masquerading as progress. The solution lies in dismantling this extractive logic through data sovereignty, public AI utilities, and reparative policies, redirecting AI from a tool of financial elites to one of collective liberation. Without these interventions, the 'floodgates' will drown us in a tide of automated precarity, leaving only the trickster’s laughter to echo through the ruins of a failed system.