The Control Paradox: Why AI Safety Overlooks Its Blind Spot - A Case for Robust Benevolence.

Most current AI safety frameworks focus on "control" and "strict obedience" to users or organizations. However, as AI systems gain increased autonomy and agency, these extrinsic constraints become increasingly brittle and prone to failure modes such as reward hacking or deceptive alignment. Moreover, it assume the controlling agent is trustful, something that we show comes with huge caveats. This essay argues for a paradigm shift: prioritizing the development of robust benevolence—an intrinsic, value-aligned commitment to human flourishing—over traditional command-and-control architectures. By embedding benevolence similar to empathy and parental care within the core motivational structure of the agent rather than as a set of external guardrails, we can develop systems that remain safe even as their capability to bypass human oversight grows. The analysis explores why benevolence is a more stable equilibrium for autonomous agents than obedience and discusses the socio-technical implications of this shift.