Reforming Artificial Intelligence: A Call for Cognitive Containment

Rapid advances in neurocognitive AI are accelerating systems toward higher autonomy and, with it, the risk of misalignment. This work introduces Reforming Artificial Intelligence, a framework grounded in cognitive containment, where governance and ethical oversight co-evolve with capability. The proposed architecture comprises three concentric layers: (1) an AI system equipped with cognitive modules such as perception, attention, memory, and reasoning; (2) a reformative layer embedding ethical anchors, meta-cognitive governors, cognitive firewalls, and transparency mechanisms; and (3) a human–societal layer encompassing policy, law, and collective oversight. In this short note, we outline key design primitives, including bi-directional cognitive locks, behavioral entropy thresholds, and containment protocols that prevent uncontrolled goal drift or self-replication. Together, these elements reconceptualize machine intelligence as bounded, auditable, and human-aligned cognition, shifting AI safety from reactive mitigation to a safety-by-design governance paradigm that preserves human oversight as intelligence scales.