Decolonizing AI Governance: How Trust as Infrastructure Requires Systemic Equity and Open Knowledge
Original framing: “Trust Is Infrastructure: Raju Narisetti with Sanjay Puri on the RegulatingAI Podcast” — bing news
Indigenous knowledge systems, such as Māori data sovereignty and African Ubuntu ethics, offer frameworks for trust that prioritize communal consent and spiritual alignment over corporate-driven 'transparency.' These perspectives challenge the Western assumption that trust can be engineered through technical fixes alone. Indigenous critiques of AI highlight how colonial extraction patterns are replicated in data harvesting, undermining trust at a systemic level.
The RegulatingAI Podcast's discussion on trust as infrastructure reveals a critical gap in AI governance: the failure to address systemic inequities rooted in colonialism, corporate power, and cultural erasure.
While the conversation touches on language equity and open knowledge, it lacks a deep historical and cross-cultural analysis of how trust in AI is shaped by power imbalances. Indigenous and Global South perspectives, such as Māori data sovereignty and Ubuntu ethics, offer frameworks for trust that prioritize communal consent and spiritual alignment, challenging Western individualistic notions. The absence of marginalized voices in the discussion underscores how AI governance remains dominated by corporate and Western institutions. To build trust in AI, we must decolonize its governance, integrating artistic, spiritual, and Indigenous knowledge into AI design. This requires redistributing power through decentralized AI models and enforcing data sovereignty laws that prevent corporate exploitation. Without such systemic reforms, AI will continue to replicate colonial hierarchies, undermining trust at a fundamental level.