Control Theory - Bryant McGill

# Control Theory **Entity class:** Concept or analytic term **Domain:** Systems Engineering, Electrical Engineering, Mathematics **Doc Type:** Concept Node **Classification:** Infrastructure Concept **Maturity:** Foundational **Related:** [[Feedback Systems]], [[Equilibrium Theory]], [[Coordination Systems]], [[Data Assimilation]] --- ## Definition The **mathematical and engineering discipline concerned with designing systems that maintain specified outputs (targets) despite disturbances or variations in inputs**. Control theory uses feedback mechanisms, error correction, and adjustment algorithms to keep dynamic systems operating within desired ranges. --- ## General Context Control theory originated in engineering (thermostats, cruise control, aircraft autopilots) where the goal is to maintain system variables within acceptable ranges despite environmental fluctuations. Controllers use sensors to measure current state, compare it to desired state, and generate corrective actions. --- ## Governance Context Climate governance increasingly uses control theory language: targets (2°C, net-zero), monitoring systems (satellites, sensors), and adjustment mechanisms (carbon pricing, adaptation measures). But governance differs from engineering: targets are politically contested, measurement is disputed, and adjustment authority is fragmented. --- ## Computational Governance Context Computational governance systems that implement closed-loop control require continuous sensing, rapid processing, and actuators capable of system-wide adjustment. This concentrates power in whoever controls the feedback mechanism. --- ## Nash Equilibrium Context Nash equilibrium in strategic interaction differs from control theory's equilibrium: Nash equilibrium is a point of mutual stability where no actor wants to unilaterally deviate. Control theory equilibrium is maintained through external correction. --- ## Key Insight Control systems require feedback (measurement of actual state), comparison to targets, and authority to adjust system variables. Applied to governance, control theory raises critical questions: who sets the targets, who has measurement authority, who controls adjustments? --- ## Simple Reminders, Quotations, and Thoughts  > "Our 10-year mission is to build semi-autonomous AIs for scientific research" > **— Samuel G. Rodriques**, *2023, FutureHouse launch essay* [[reminders/AI Control/Building Semi-Autonomous AI Scientists by Samuel G. Rodriques|Building Semi-Autonomous AI Scientists by Samuel G. Rodriques]] > "when we get things more intelligent than ourselves, no one really knows whether we’re going to be able to control them." > **— Geoffrey Hinton**, *2024, post-Nobel University of Toronto interview* *Verification Status: Editorially quarantined — `things` and `them` stand in for the advanced AI systems under discussion. Recover a complete, self-contained passage before promotion.* [[reminders/unverified/More Intelligent Than Ourselves by Geoffrey Hinton|More Intelligent Than Ourselves by Geoffrey Hinton]] > "I’m concerned that powerful tools can also have negative uses, and society is not ready to deal with that." > **— Yoshua Bengio**, *March 2023, Mila press conference* [[reminders/AI Control/Society Is Not Ready for AI’s Power by Yoshua Bengio|Society Is Not Ready for AI’s Power by Yoshua Bengio]] > "super intelligence will be a new situation that never happened before" > **— Geoffrey Hinton**, *2023, Collision conference remarks* [[reminders/AI Control/Superintelligence Is a Situation Humanity Has Never Faced by Geoffrey Hinton|Superintelligence Is a Situation Humanity Has Never Faced by Geoffrey Hinton]] > "When technology gets sufficiently powerful, we either win together or we all lose together." > **— Max Tegmark**, *Future of Life Institute discussion* [[reminders/AI Control/Win Together or Lose Together by Max Tegmark|Win Together or Lose Together by Max Tegmark]]  ## See Also [[Computational Architecture]], [[Nash Equilibrium]], [[Continuous Adaptive Management]] ## Russia and Prussia Kybernetiks Context [[Russia and Prussia Kybernetiks]] uses control theory to read schooling as a loop of [[Setpoint|setpoints]], measurement, [[Error Signal|error signals]], [[Feedback Channel|feedback channels]] and institutional [[Actuator|actuators]].  ## Austin research connections [[wiki/Sensor-to-Action Loop|Sensor-to-Action Loop]] gives the Austin cluster’s operational sequence, while [[wiki/Center for Autonomy|Center for Autonomy]] and [[wiki/Center for Computational Medicine|Center for Computational Medicine]] supply different application settings. The inferred state, action objective, timing, and uncertainty jointly determine whether feedback can support a useful intervention. **Research map:** [[wiki/Austin Executable Loop|Austin Executable Loop]] · [[research/The Austin Executable Loop|Master document]]  ## Relationships  This entry's documented connections are expressed in its definition and related-work routes, with provenance retained in the source-linked material.