Treaty monitoring traditionally relied on manual reviews of satellite archives, customs ledgers, and financial disclosures. Recent pilots in the North Atlantic Treaty Organization and the Financial Action Task Force show how AI can process petabytes of data to surface anomalous patterns quickly. This article investigates AI pipelines that support modern treaty verification and addresses three r...
Category: Geopolitical Risk Intelligence
Data-driven political and economic risk predictions. Monitoring public databases, historical analysis, and predictive modeling for community safety.
Critical Infrastructure AI Dependencies: Mapping Single Points of Failure in National AI Supply Chains
Critical Infrastructure AI Dependencies: Mapping Single Points of Failure in National AI Supply Chains
Sanctions Intelligence Automation: AI-Driven Screening at Scale Under EU and US Regimes
Accurate and efficient sanctions screening is a critical compliance requirement for financial institutions operating across the European Union and United States. While rule‑based systems dominate current workflows, recent advances in neural representation l[REDACTED]g offer the prospect of dramatically reducing false‑positive rates and operational costs. This article investigates the deployment...
AI Conflict Prediction Accuracy: Evaluating Forecasting Models Against 2024-2025 Events
The proliferation of AI-driven geopolitical risk forecasting has transformed conflict prediction methodologies, yet systematic validation against real-world outcomes remains incomplete. This study conducts a retrospective evaluation of five major forecasting platforms—including PredictIt, Metaculus, and three commercial vendors—against 47 documented conflict escalations between January 2024 and...
Humanitarian Aid Diversion — Modeling Leakage Channels and Mitigation Strategies
Humanitarian assistance is increasingly channelled through complex logistical networks that span unstable conflict zones, fragile state infrastructures, and volatile political landscapes. While digital innovations such as privacy‑preserving wallets [1], satellite‑based monitoring [2], and bio‑inspired optimisation algorithms [3] promise greater transparency and efficiency, they also introduce n...
Measuring State Fragility: An Empirical RSI Framework Applied to Ukraine
We built something. Not a dashboard, not a report, not another data visualization that looks impressive but tells you nothing actionable. We built a ruler. A ruler that measures the same thing — instability — whether you point it at a country, a city, or a neighbourhood. The same 0-to-1 scale. The same formula. The same question: how close is this place to falling apart?
When the Economy Collapses, the Government Follows: Mapping the Dependency Between Economic and Political Instability
Venezuela's GDP contracted by more than 80 percent between 2013 and 2021 — one of the largest peacetime economic collapses ever recorded. Its political system, meanwhile, had not yet fully collapsed when the economy began its descent. The government survived by concentrating power, suppressing opposition, and externalizing blame. But the sequence is unmistakable: the economy fell first, and pol...
The World Is Less Violent Than in 2000. It Is Also Less Stable. Here Is Why.
The conflict proxy score — our model's aggregate measure of active armed conflict intensity across 87 countries — has fallen from 6.85 in 2000 to 5.20 in 2023. That is a 24% decline over 23 years. By the oldest and most intuitive measure of global danger, the world is meaningfully safer than it was at the turn of the millennium.
The Algorithm That Watches the World Fall Apart
This article describes the development and deployment of the World Stability Intelligence (WSI) system — a machine l[REDACTED]g-driven geopolitical risk monitoring platform that continuously tracks 87 countries across three risk dimensions: war risk (45%), political risk (35%), and economic risk (20%). Drawing on an ML-enhanced heuristic prediction framework (HPF-P), the system generates normal...
The Ratepayer Protection Pledge: Trump’s AI Energy Gambit and the Geopolitics of Power
On March 4, 2026, seven of the world's most powerful technology corporations — Amazon, Google, Meta, Microsoft, OpenAI, Oracle, and xAI — signed the Ratepayer Protection Pledge at the White House, committing to absorb the full cost of electricity generation required by their artificial intelligence data centers. The pledge, announced by President Trump in his State of the Union address and form...