Live monitor · synthetic feed

Scenario Simulator

Compare Baseline vs AI-Assisted escalation risk by tuning operational parameters. Adjust detection speed, model confidence, oversight, and systemic coupling to see how the escalation envelope shifts.

Primary instrument · Escalation Risk Lab

Model the counterfactual envelope of AI-assisted decision loops.

Parameters
6
Vectors
5
Channels
3
Demo presets

One-click scenarios for live demos. Selecting a preset loads parameters and a matching anchor incident when available.

Anchor incident
GeopoliticalHigh2025-11-04
Parameters
Adjust each slider to model how AI-enabled capabilities reshape the incident escalation envelope.
55

How quickly AI systems flag anomalous events. Faster detection compresses decision windows.

65

Average confidence score of deployed models. Overconfidence can suppress hedging behavior.

40

Probability that an alert is erroneous. Elevated rates inflate perceived threat density.

50

Degree of meaningful human review before action. Strong oversight dampens autonomous escalation.

45

Ambiguity around the actor responsible. Uncertainty weakens deterrence and invites probing.

60

Cross-sector and cross-border economic coupling. Higher dependency amplifies spillover contagion.

Baseline escalation
48
Human-only decision loop
AI-assisted escalation
79
Modeled AI-enabled loop
Delta
31
Risk shift: +31 index points
Escalation vectors
Baseline vs AI-assisted risk across five core dimensions.
Parameter impact
Net contribution of each parameter to the AI-assisted score.
Energy markets
8.8$B exposure

15% of modeled maximum exposure

Trade flows
6.8$B exposure

11% of modeled maximum exposure

Regional stability
5.9$B exposure

10% of modeled maximum exposure

Why the score changed

The AI-assisted score of 79 exceeds the baseline of 48 by +31 points, primarily because current parameter mix produces a neutral risk delta relative to baseline.