Project Maven

Algorithmic Warfare Cross-Functional Team Analysis

Project Evolution

From identifying objects in drone video to coordinating all-domain command chains.

Development Scaling

Relative complexity and data ingestion volume (2017-2025)

Milestone Explorer

⚖️

The Responsibility Gap

When AI identifies a target, the "Human in the Loop" often becomes a "Rubber Stamper" due to cognitive speed mismatches. This shifts moral agency from commander to code.

🏛️

Corporate Complicity

The transition from Google to Anduril/Palantir signifies a shift from "general tech" to "dedicated defense tech," reducing public oversight but increasing mission alignment.

🌫️

Algorithmic Opacity

Neural networks are "black boxes." If Maven misidentifies a civilian vehicle, the mathematical weights that led to that error are nearly impossible to audit in real-time.

📉

The Slippery Slope

Maven is the infrastructure for Lethal Autonomous Weapons Systems (LAWS). Today it is surveillance; tomorrow it is an autonomous strike capability.

Capability Roadmap

2018 Base

Object Classification

Manual tagging of Full Motion Video (FMV).

2024 Current

Multi-INT Sensor Fusion

Fusing radar, SIGINT, and satellite imagery for real-time recommendations.

2030 Forecast

Autonomous Swarm Orchestration

Self-organizing drone fleets and predictive enemy maneuver analysis.

The Security Dilemma Matrix

Opponent Choice

US Choice

ADOPT

REJECT

Arms Race (-3, -3)

Dominance (+5, -5)

Defeat (-5, +5)

Stability (0, 0)

Payoff Analysis

Click a quadrant in the matrix to explore the strategic logic of military AI development.