Governments can’t agree on what AI actually is

Global Calls for Coordination: Most countries advocate for international engagement or governance of AI, yet significant international action remains elusive.
Defining AI: Different actors define AI variably, from mainstream machine learning to superintelligent systems, creating confusion in policy discussions.
Epistemic Disagreements: There are deep disagreements on the speed and scale of AI’s transformative impact, impacting governmental policy.
Government Views and Foreign Policies: Governments’ perceptions of AI’s transformation and perceived self-sufficiency influence their foreign policy approaches, resulting in varied strategies and alliances.
International Coordination Challenges: Diverging views on AI’s pace and capability self-sufficiency prevent a shared agenda, leading to incompatible policy proposals in global discussions.
National Dependencies and Strategies: Countries like the UAE seek collaborations with the U.S. or China due to perceived rapid advancement and dependency, while others, like India, focus on domestic AI development due to differing views.
Lack of Incentives for Coordination: Countries with self-sufficient AI ecosystems have little reason to cede control to international bodies, hindering collaborative efforts.
Implications for the Future: A lack of convergence on these epistemic differences will continue to stall international coordination on AI, leaving serious global issues unaddressed.