Algorithmic Sabotage Research Group %28asrg%29

When a rideshare algorithm began systematically refusing service to predominantly minority neighborhoods—not out of bias, but because surge pricing models learned those areas had “lower historical tip rates”—the ASRG struck. They deployed a fleet of low-cost, Arduino-controlled signal emitters that mimicked the telemetry of a broken-down car. To the AV’s sensors, a phantom obstruction appeared at every intersection in the redlined zone. The algorithm, trying to route around a nonexistent crash, froze in recursive confusion. Within six hours, human dispatchers overrode the system. The algorithm was retrained. The neighborhood got service again.

The ASRG’s work is deeply rooted in critical theory, particularly:

: They oppose systems that reinforce structural injustices, authoritarianism, and "unrestrained technosolutionism". Counter-Intelligence

Modifying UI/UX parameters through browser extensions or custom APIs. algorithmic sabotage research group %28asrg%29

Strategic collective log-offs timed during peak hours to break the predictive accuracy of platform dispatch engines. 2. Data Poisoning and Creative Subversion

The group researches and collects strategic methodologies intended to disrupt, poison, or corrupt data within the operational workflows of artificial intelligence (AI) and Big Data systems. These tactics are designed to destabilize critical mechanisms of algorithmic governance.

The group examines the deployment of automated systems within civic spaces, focusing on facial recognition, welfare fraud detection algorithms, and predictive policing tools. ASRG research highlights how communities use physical interventions (such as adversarial clothing or makeup patterns) and digital interventions (such as flooding report databases with junk data) to break the efficacy of state-sponsored automated profiling. Strategic Frameworks Advocated by ASRG The algorithm, trying to route around a nonexistent

Modern bureaucracies have outsourced exception-handling to black-box optimizers. When a human is unfairly denied a loan, their appeal enters a queue processed by a second algorithm. When a delivery driver is penalized for a delay caused by a natural disaster, the appeal is denied for "insufficient variance from normative parameters."

Simultaneously, Aaron, a software developer granted anonymity, created . He described it as malicious software, “named after a carnivorous plant that will eat just about anything,” designed to trap crawlers for months in an infinite maze of static files to “poison AI models.” He hoped such tools would give “teeth” to robots.txt.

Algorithmic Sabotage Research Group (ASRG) is a practice-led research initiative that operates at the intersection of digital culture, information technology, and political activism. It is characterized by its "conspiratorial" and "aesthetico-political" approach to challenging the dominance of algorithms in contemporary life. Mission and Philosophy The group's core mission is to theorize and practice "algorithmic sabotage" as a form of techno-disobedience and counter-power. Techno-politics: The neighborhood got service again

Advocating for the democratic and communal limitation of harmful technologies to prevent "algorithmic humiliation" and abstract segregation. The Manifesto on "Algorithmic Sabotage"

The ASRG focuses on "algorithmic sabotage"—a conceptual tool used to challenge necropolitical technologies, structural injustices, and "fascist techno-solutionism". Their work centers on:

The Parasite in the Machine: A Framework for Algorithmic Sabotage as a Counterweight to Systemic Optimization

: Their work is deeply rooted in radical feminist, anti-fascist, and decolonial perspectives .

A key pillar of ASRG’s research is the politics of refusal. This entails analyzing the moments where users, workers, or communities collectively decide not to feed the machine. Refusal can manifest as mass platform log-outs, collective data poisoning, or the creation of alternative, non-algorithmic community networks. Core Pillars of ASRG Research