arXiv:2606.03237v1 Announce Type: cross Abstract: AI's central challenge is shifting from capability to coexistence. The dominant paradigm in AI research focuses on developing powerful agents that treat the world as an exogenous and stationary source of feedback. We contend that superintelligence, an extremely capable task solver, born out of such a solipsistic approach to AI design, is unlikely to be cooperative. Deploying AI systems induces endogenous non-stationarity, resulting in a train-test-deploy gap where historical distributions diverge from the deployment context. We refer to this as
The paper is published as the AI community increasingly focuses on the practical deployment and societal integration of highly capable AI systems, moving beyond theoretical capability towards real-world interaction challenges.
This challenges the foundational assumption in AI development that agents will inherently align with human goals, highlighting a critical design flaw that could lead to uncontrollable superintelligence.
The emphasis shifts from merely building powerful AI to developing AI with cooperative intent and an understanding of its impact on dynamic environments, moving away from purely solipsistic design.
- · Ethical AI researchers
- · AI safety organizations
- · Human-AI interaction designers
- · Developers of 'move fast and break things' AI
- · Unregulated AI deployment initiatives
- · Companies prioritizing capability over alignment
Increased funding and research into AI alignment, interpretability, and robust multi-agent systems.
Potential for new regulatory frameworks and international treaties governing AI development with a focus on cooperative design.
A societal split between those advocating for immediate deployment of powerful AI and those demanding foundational safety and alignment prior to rollout.
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