arXiv:2606.12923v1 Announce Type: cross Abstract: AI alignment, interpretability, steering, and neural perturbation studies identify order-inducing objects. We argue that order is not control. Control requires a receiver-gated response law: a denominator-indexed operator mapping material state, action/drive, bath, and receiver state to response displacement, sinks, effort, and basin projection. We identify it across biological, LLM, adapter, and stochastic-operator panels. The laws are local: an intervention can be admitted, saturated, sign-changing, leaky, or overdriven depending on medium, b
The rapid development and deployment of AI systems necessitate deeper understanding of control mechanisms to ensure safety and alignment.
This research provides a fundamental re-evaluation of AI control, moving beyond superficial notions of order to define true control based on receiver-gated response laws, crucial for robust AI development.
The conceptual framework for AI control shifts from focusing on 'order-inducing objects' to demanding 'receiver-gated response laws,' impacting future research and development in AI alignment and safety.
- · AI safety researchers
- · Developers of robust AI systems
- · Academic AI research institutions
- · Developers of brittle or poorly controlled AI
- · Approaches to AI alignment based solely on 'order'
- · Theories of control lacking granular feedback mechanisms
New theoretical frameworks for AI control and alignment will emerge, emphasizing dynamic, context-dependent response laws.
This could lead to the development of more resilient and predictable AI systems, reducing unexpected behaviors and improving safety.
The enhanced understandability and controllability of complex AI could accelerate adoption in high-stakes environments, potentially reducing regulatory friction.
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Read at arXiv cs.CL