Biennale Architettura 2025

Made in collaboration with: Laura Kurgan, Adam Vosburgh, Adeline Chum, Michael Krisch

Video projection, unreal engine, ACLED data, population data, javascript, Python

Full video coming soon.

Project description:

The Curse of Dimensionality explores predictive models of risk — computational models, built from Artificial Intelligence and machine learning methods —  that assess different kinds of threats present in both physical and virtual spaces. These predictive tools are deployed by governments, corporations, and civil society, and, in the name of safety and security, strike an unstable balance between protection and harm. The Curse of Dimensionality investigates how computational intelligence systems define threats, measure risk, and track conflict. By characterizing patterns of violence into categories, accelerating decision-making, and shaping public perception, these models influence not only how conflicts are understood but also how they unfold. Through simulations, the project draws attention to these overlooked junctures of power. The aim is to train the senses of the audience to see, hear, and confront the hidden complexities at the heart of this threat analysis — explaining those subtle, often invisible factors that increasingly shape conflict around the world.

In technical terms, the “curse of dimensionality” names a problem of scaling — as the number of features (dimensions) in training data increases, models require exponentially more data to be accurate, and interpretability is often sacrificed. Ideas are unpacked across three related algorithms visualized in an animation. Our work is divided into three scenes: (1) Models for Evaluation: global forecasts of conflict; (2) Models for Governance: algorithmic systems influence the flow of conflict-related information across social networks, affecting those conflicts; and (3) Models for Warfare: large-scale intelligence models identify threats and guide military operations, in spite of ever-increasing uncertainties (the curse of dimensionality).