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The AI alignment problem, which focusses on ensuring that artificialintelligence (AI), including AGI and ASI, systems act according to humanvalues, presents profound challenges. With the progression from narrow AI toArtificial General Intelligence (AGI) and Superintelligence, fears aboutcontrol and existential risk have escalated. Here, we investigate whetherembracing inevitable AI misalignment can be a contingent strategy to foster adynamic ecosystem of competing agents as a viable path to steer them in morehuman-aligned trends and mitigate risks. We explore how misalignment may serveand should be promoted as a counterbalancing mechanism to team up withwhichever agents are most aligned to human interests, ensuring that no singlesystem dominates destructively. The main premise of our contribution is thatmisalignment is inevitable because full AI-human alignment is a mathematicalimpossibility from Turing-complete systems, which we also offer as a proof inthis contribution, a feature then inherited to AGI and ASI systems. Weintroduce a change-of-opinion attack test based on perturbation andintervention analysis to study how humans and agents may change or neutralisefriendly and unfriendly AIs through cooperation and competition. We show thatopen models are more diverse and that most likely guardrails implemented inproprietary models are successful at controlling some of the agents' range ofbehaviour with positive and negative consequences while closed systems are moresteerable and can also be used against proprietary AI systems. We also showthat human and AI intervention has different effects hence suggesting multiplestrategies.

Neurodivergent Influenceability as a Contingent Solution to the AI Alignment Problem