Colonial cognitive science and neoliberal computation: How Western epistemologies shaped AI’s neurocentric illusion and its systemic risks
Original framing: “AI behaves more like a brain than a database – cognitive science’s role in its origin story helps explain why” — The Conversation - Global
Cross-cultural perspectives reveal that non-Western cognitive models often prioritize context, ambiguity, and ethics over efficiency and scalability—qualities AI’s 'brain' metaphor dismisses as 'noise' or 'error.' For example, Confucian *ren* (benevolence) or Hindu *dharma* (duty) frame decision-making as relational, not algorithmic. The omission of these frameworks in AI design reflects a broader epistemic violence, where Western individualism is imposed as universal. This erasure allows AI to replicate cultural biases (e.g., favoring Eurocentric data) while claiming objectivity. A cross-cultural lens would demand AI architectures that honor diversity, not just replicate it.
The 'brain' metaphor in AI is not a neutral description but a colonial artifact, shaped by Western cognitive science’s reductionist paradigms and Silicon Valley’s neoliberal logic of extraction.
This framing obscures how AI’s design prioritizes scalability and efficiency over ethics, wisdom, and ecological awareness—values central to Indigenous and non-Western knowledge systems. The origin story of AI, as told by mainstream narratives, erases marginalized contributors like Black mathematicians and women in tech, while ignoring the historical precedents of Cold War militarization and the 1980s AI winter. Without centering these voices and contexts, AI risks becoming a tool of digital colonialism, replicating the same extractive and oppressive structures that colonialism once did. The solution lies in decolonizing AI’s design, integrating marginalized epistemologies, and regulating its 'brain' hype to demand accountability for its systemic harms. Actors like the *Global South AI Ethics Initiative* and Indigenous knowledge holders must lead this transformation, ensuring AI serves collective well-being rather than perpetuating extraction and control.