Acceleration into Chaos? A Systemic Critique of Sector-Neutral AI Acceleration and the X^∞-Model as an Ethical-Mathematical Counterproposal

This paper critiques the assumptions of the "AI Acceleration: A Solution to AI Risk Policy-" paper, which argues that sector-wide acceleration of technological progress is suitable for risk mitigation. We demonstrate that this assumption, particularly in the context of Artificial Intelligence (AI), is dangerously oversimplified due to recursive self-optimization, feedback loops, and chaotic transitions. Drawing on mathematical models, systems theory, and ethical principles embedded in the X^∞-Model (an accountability-based governance model with cap logic, feedback obligation, and auditable delegation; project status and preliminary information at: https://github.com/Xtothepowerofinfinity/Philosophie_der_Verantwortung), we advocate for a feedback-based, responsibility-oriented approach to AI development. Sector-wide acceleration without specific AI risk modeling demonstrably increases the risk of a "wild singularity" rather than reducing it. Available under CC BY-SA 4.0.