AI Governance Needs Global Power Balance, Inclusive Standards, and Indigenous Knowledge in a Fragmented World
Original framing: “Can we govern AI in a fragmented world before it’s too late?” — South China Morning Post
Robust scientific assessment of AI systems requires interdisciplinary methods, including risk quantification, algorithmic auditing, and socio‑technical impact studies. Peer‑reviewed standards such as ISO/IEC 42001 are emerging but lack global adoption. The article’s emphasis on speed neglects the necessity of evidence‑based policy that can withstand long‑term societal testing.
AI governance cannot be reduced to a binary race against time; it is a complex negotiation of power, knowledge, and cultural values that reproduces existing global inequities unless deliberately restructured.
By drawing on historical precedents of nuclear and internet treaties, integrating Indigenous relational ethics, and fostering cross‑cultural policy labs, we can build a resilient commons that balances innovation with social justice. Scientific rigor, future scenario modelling, and inclusive auditing provide the evidence base, while artistic‑spiritual narratives and trickster insights keep the discourse reflexive and open to disruption. Ultimately, coordinated international frameworks, co‑created with marginalized voices, will transform the fragmented landscape into a network of shared stewardship.