I’m an independent researcher proposing State Discrepancy, a public-domain metric to quantify how much an AI system changes a user’s intent (“the Ghost”).
The goal: replace vague legal and philosophical notions of “manipulation” with a concrete engineering variable. Without clear boundaries, AI faces regulatory fog, social distrust, and the risk of being rejected entirely.
Algorithm 1 (on pp.16–17 of the linked white paper) formally defines the metric:
1. D = CalculateDistance(VisualState, LogicalState)
2. IF D < α : optimization (Reduce Update Rate)
3. ELSE IF α ≤ D < β : warning (Apply Visual/Haptic Modifier proportional to D)
4. ELSE IF β ≤ D < γ : intervention (Modulate Input / Synchronization)
5. ELSE : security (Execute Defensive Protocol)
The full paper is available on Zenodo: https://doi.org/10.5281/zenodo.18206943
The goal: replace vague legal and philosophical notions of “manipulation” with a concrete engineering variable. Without clear boundaries, AI faces regulatory fog, social distrust, and the risk of being rejected entirely.
Algorithm 1 (on pp.16–17 of the linked white paper) formally defines the metric:
1. D = CalculateDistance(VisualState, LogicalState)
2. IF D < α : optimization (Reduce Update Rate)
3. ELSE IF α ≤ D < β : warning (Apply Visual/Haptic Modifier proportional to D)
4. ELSE IF β ≤ D < γ : intervention (Modulate Input / Synchronization)
5. ELSE : security (Execute Defensive Protocol)
The full paper is available on Zenodo: https://doi.org/10.5281/zenodo.18206943