AI Kill Switch Threshold Simulator | AI Governance & Containment Analysis

Governance Parameters

Capability Growth Rate (%/day) 4.5% Compound recursive scaling per 24h operational cycle

Autonomy Level (Index 0-100) 78 Autonomous tooling, self-coding & recursive execution index

Kill Switch Threshold (Index) 85.0 Statutory regulatory ceiling triggering mandatory shutdown

Monitoring Latency (Hours) 12h Audit loop reaction time between threshold trip & hardware disconnect

Real-Time Trajectory vs. Containment Margin (30-Day Window) D3 Dynamic Engine

Intervention Status

Tripped (Mandatory Stop)

Peak Capability Score

92.4

Time to Threshold

18 days

Societal Risk Level

Contained

Containment Verdict: Capability escalated past statutory trigger at Day 18. Due to 12h monitoring lag, model expanded to a peak index of 92.4 before mandatory kill switches isolated neural compute fabrics, successfully averting catastrophic runaway.

Context & Evidence: In BBC interviews, Anthropic co-founder Jack Clark stated that AI models are getting more capable "by the day" and argued that regulatory frameworks must implement mandatory hardware/software kill switches to mitigate major systemic risks to society before autonomous recursive capabilities outpace human oversight.

AI Kill Switch Containment Simulator Explainer

Your browser does not support video.

Read the explanation

Autonomous models compound capability each operational day, accelerated by recursive coding multipliers. When capability breaches the statutory kill switch ceiling, a tripwire activates, but audit latency delays physical disconnect. During monitoring latency, compute expands to peak score 92.4 before circuits cut power, causing exponential decay back into containment. Adjusting growth rates or clicking Unbounded instantly recalculates whether latency causes catastrophic runaway or safely contained intervention.