Most alignment discussion focuses on the AI's objective function or the encoding of human values. I want to discuss the operator's signal-to-noise ratio.
If we model the Human-in-the-Loop (HITL) not as a 'ground truth' oracle, but as a noisy channel subject to thermodynamic variance (entropy), we can quantify how much 'alignment' is lost simply due to human biological jitter.
In the linked post, I propose a theoretical framework where Cognitive Coherence (Hc)—measurable via EEG variance—acts as a limiting factor for control efficacy in high-stakes systems. This is an attempt to formalize "lucidity" as an engineering constraint rather than a qualitative state.
The Core Mechanism
I model the "Semantic Filter" efficiency (Fsem) of the operator as inversely proportional to their internal neural noise:
Fsem≈11+αHc
Where:
* Hc is the temporal variance of the operator's neural attention (Cognitive Entropy).
* α is the coupling coefficient of the interface.
The Hypothesis
The proposal suggests that safety in hybrid systems isn't just about constraining the AI (Agent), but about thermodynamically cooling the operator (Principal).
If Hc is high (distracted/reactive state), the control vector U diverges from the intent X, creating a specific class of failure mode I call "Informational Divergence."
Epistemic Status & Cruxes
This is a speculative architectural proposal, not a verified result. My central cruxes are:
* Metric Validity: Whether Gamma-band synchrony (40Hz) is a sufficiently robust proxy for semantic coherence in complex decision-making, or if it merely measures arousal/focus.
* Scale: Whether minimizing operator entropy matters in regimes where the AI's processing speed outpaces biological latency by orders of magnitude (i.e., does the noisy human channel just become irrelevant?).
I am not claiming privileged access to insight here; this is an attempt to compress a set of intuitions into falsifiable variables. I am interested in feedback from the control theory and cybernetics community on the experimental setup proposed in Section IV.
Most alignment discussion focuses on the AI's objective function or the encoding of human values. I want to discuss the operator's signal-to-noise ratio.
If we model the Human-in-the-Loop (HITL) not as a 'ground truth' oracle, but as a noisy channel subject to thermodynamic variance (entropy), we can quantify how much 'alignment' is lost simply due to human biological jitter.
In the linked post, I propose a theoretical framework where Cognitive Coherence (Hc)—measurable via EEG variance—acts as a limiting factor for control efficacy in high-stakes systems. This is an attempt to formalize "lucidity" as an engineering constraint rather than a qualitative state.
The Core Mechanism
I model the "Semantic Filter" efficiency (Fsem) of the operator as inversely proportional to their internal neural noise:
Fsem≈11+αHc
Where:
* Hc is the temporal variance of the operator's neural attention (Cognitive Entropy).
* α is the coupling coefficient of the interface.
The Hypothesis
The proposal suggests that safety in hybrid systems isn't just about constraining the AI (Agent), but about thermodynamically cooling the operator (Principal).
If Hc is high (distracted/reactive state), the control vector U diverges from the intent X, creating a specific class of failure mode I call "Informational Divergence."
Epistemic Status & Cruxes
This is a speculative architectural proposal, not a verified result. My central cruxes are:
* Metric Validity: Whether Gamma-band synchrony (40Hz) is a sufficiently robust proxy for semantic coherence in complex decision-making, or if it merely measures arousal/focus.
* Scale: Whether minimizing operator entropy matters in regimes where the AI's processing speed outpaces biological latency by orders of magnitude (i.e., does the noisy human channel just become irrelevant?).
I am not claiming privileged access to insight here; this is an attempt to compress a set of intuitions into falsifiable variables. I am interested in feedback from the control theory and cybernetics community on the experimental setup proposed in Section IV.