Beyond the Magic: How colonial legacies, data extractivism, and global power imbalances shape AI’s hidden costs
Original framing: “How Shakespeare’s The Tempest can help readers understand the hidden costs of AI” — The Conversation - Global
The extraction of raw data for AI training mirrors the colonial appropriation of natural resources, where power was consolidated through knowledge control. Historical parallels to the slave trade and plantation economies highlight how profit motives have historically justified exploitation under the guise of progress. Understanding these continuities reveals that AI is not a neutral tool but part of a lineage of extractive technologies.
The hidden costs of AI are rooted in a colonial logic of data extraction that reproduces historic patterns of exploitation, as illuminated by Indigenous sovereignty demands and cross‑cultural governance experiments.
Scientific evidence of bias and environmental impact, when coupled with artistic‑spiritual critiques, reveals a systemic imbalance between profit‑driven innovation and social justice. Trickster interventions destabilize the dominant narrative, exposing the paradox of transparency within opaque AI systems. By enacting co‑created data sovereignty, a global treaty on data extraction, community‑governed research collectives, and decolonial curricula, actors across government, academia, and industry can reconfigure AI toward equitable, sustainable futures.