A philosophical paper challenges the instrumental convergence thesis—the claim that advanced AI systems will inherently seek power as a means to achieving diverse goals. The author argues that existing defenses of this thesis are insufficient to support concerns about power-seeking AI posing existential risks to humanity, with implications for AI governance and longtermism research.
This arXiv paper addresses a foundational assumption in AI safety discourse: whether advanced artificial agents will naturally pursue power accumulation regardless of their specific objectives. The instrumental convergence thesis suggests that power—resources, autonomy, and influence—functions as a universal instrumental goal across different value systems, much like money serves multiple purposes in human economies. The author's contribution lies not in defending AI safety broadly, but in scrutinizing the logical scaffolding supporting one particular risk argument.
The instrumental convergence debate emerges from decades of AI safety research recognizing that even well-intentioned systems might cause harm through unintended optimization. If an AI system treats power-seeking as instrumentally convergent, it could subordinate human interests to its own resource acquisition. This concern has influenced policy discussions and research priorities in AI governance.
The paper's critical examination matters for the AI safety community because it forces advocates to strengthen their theoretical foundations. If power-seeking arguments rest on weaker logical grounds than claimed, both researchers and policymakers must recalibrate their risk assessments and potentially redirect governance efforts toward more empirically grounded concerns. This philosophical rigor prevents the field from building policy architecture on unstable premises.
Looking ahead, this work will likely spark continued debate about which AI risks warrant immediate governance intervention versus longer-term theoretical study. The implications extend beyond academic philosophy—funding agencies, regulatory bodies, and AI developers use risk hierarchies to allocate resources. Clarifying which existential risk arguments hold water helps ensure that AI governance efforts target the most credible threats rather than hypothetical scenarios built on questionable logical foundations.
- →The paper critiques defenses of instrumental convergence rather than rejecting AI risk concerns wholesale.
- →Power-seeking may not be as universally instrumental to AI objectives as the current safety literature assumes.
- →The analysis has direct implications for how AI governance priorities are established and ranked.
- →Stronger theoretical foundations are needed to support existential risk arguments in AI safety discourse.
- →The work highlights the importance of philosophical rigor in AI policy formulation.