Overview
This project investigates why traditional national security risk assessment frameworks—though critical for decision-making—have repeatedly failed to anticipate and mitigate major threats, and how artificial intelligence could transform this domain.
The Problem
Governments rely on risk assessments to guide defense strategy, allocate resources, and prepare for emerging threats. Yet history shows repeated failures:
- The inability to foresee or adequately prepare for the 9/11 attacks.
- Underestimating the risks of pandemics before COVID-19.
- Gaps in anticipating cyberwarfare, disinformation, and hybrid threats.
These failures are not just technical oversights—they reflect structural weaknesses in how information is gathered, processed, and acted upon. Traditional approaches rely heavily on qualitative judgments, bureaucratic consensus, and politicized processes that can obscure signals of looming dangers.
The Role of AI
Artificial intelligence offers new opportunities to strengthen national security risk assessment by:
- Processing qualitative data at scale: AI can extract patterns from vast sources of text, imagery, speech, and expert input.
- Supporting human judgment: Rather than replacing analysts, AI can highlight overlooked connections, contradictions, or weak signals.
- Improving scenario planning: Machine learning models can stress-test assumptions and simulate how risks evolve in interconnected systems.
- Reducing bias and blind spots: Properly designed, AI tools can help counteract institutional and cognitive biases that undermine traditional assessments.
Goals of the Project
- Explore the recurring failures in national security threat assessment
- Diagnose recurring causes behind these faiulres
- Identify where AI technology can address root cause of failure
- Develop pathways for using AI responsibly—ensuring it enhances, not replaces, human critical thinking - when assisting with threat assessment
- Assess cultural and organizational barriers that will determine whether AI adoption succeeds or fails.
Importance
National security environments are defined by uncertainty, complexity, and high stakes. Failures in risk assessment cost lives, waste resources, and erode trust in institutions. By exploring how AI can bridge the gap between human expertise and data-driven insight, this project points toward a future where risk assessments are more anticipatory, transparent, and resilient.
Outcomes
- A critical analysis of past assessment failures and their root causes.
- A framework for AI-assisted risk assessment in national security contexts.
- Recommendations for integrating AI into policy and practice without undermining accountability or human oversight.
