: ASRG documents and critiques what it describes as "necropolitical technologies". These are algorithmic frameworks that reinforce structural racism, economic inequality, and digital authoritarianism. Key Tactics: Disrupting the AI Supply Chain
The ASRG's manifesto extends this tradition, shifting from the physical destruction of machinery to the . Where the original Luddites smashed mechanical looms, the ASRG aims to poison the algorithmic models of the digital era. This reclamation of Luddism as a positive political identity—not a mark of ignorance but a position of informed refusal—is central to ASRG's intellectual project.
┌────────────────────────────────────────────────────────┐ │ THE INDISCRIMINATE SCRAPING LOOP │ └───────────────────────────┬────────────────────────────┘ │ ▼ ┌────────────────────────────────────────────────────────┐ │ Mass Harvesting of Unconsented Web Data │ └───────────────────────────┬────────────────────────────┘ │ ▼ ┌────────────────────────────────────────────────────────┐ │ Algorithmic Consolidation (Corporate Models) │ └───────────────────────────┬────────────────────────────┘ │ ▼ ┌────────────────────────────────────────────────────────┐ │ ASRG Intervention: Sabotage / Poisoning / Tarpits │ └────────────────────────────────────────────────────────┘
: They oppose systems that reinforce structural injustices, authoritarianism, and "unrestrained technosolutionism". Counter-Intelligence algorithmic sabotage research group %28asrg%29
The Algorithmic Sabotage Research Group (ASRG) is a vital organization that shines a light on the dark side of algorithms. By understanding the threats and risks of algorithmic sabotage, we can take proactive steps to prevent, detect, and respond to these emerging threats. As algorithms continue to shape our world, the ASRG's work is crucial in ensuring that these powerful tools are used for the greater good, not for malicious purposes.
This paper provides a comprehensive framework for understanding algorithmic sabotage and its effects on optimization algorithms. The authors introduce a systematic approach to analyzing and mitigating the impact of adversarial manipulation on optimization algorithms.
While many advanced scraping defenses require deep control over server environments, ASRG pushes for democratized tools. Activists within these ecosystems develop lighter, open-source Python scripts and automated pipelines specifically designed to scramble metadata and secure static sites built on frameworks like Jekyll or Hugo. Art, Publishing, and Aesthetic Warfare : ASRG documents and critiques what it describes
The Algorithmic Sabotage Research Group (ASRG) represents a critical intervention in the modern discourse surrounding artificial intelligence, automated labor, and digital surveillance. As algorithms increasingly dictate the terms of economic and social life, the ASRG operates at the intersection of hacktivism, academic inquiry, and grassroots resistance. Their work focuses on "algorithmic sabotage"—the intentional disruption or subversion of automated systems to reclaim human agency and challenge the power structures embedded in code.
Our goal is friction , not fracture. We aim to lower the velocity of automated injustice until the human-in-the-loop can catch up.
The Algorithmic Sabotage Research Group does not seek to break machines. We seek to make them break safely . In a world where a line of code can deny a life-saving medical claim or approve a predatory loan, the ability to induce a graceful, reversible failure is a fundamental civic right. Where the original Luddites smashed mechanical looms, the
The consequences of algorithmic sabotage can be severe and far-reaching, with potential impacts on:
This article examines the philosophy, tactics, and aims of this research collective as outlined in their recent work, including the "Manifesto On Algorithmic Sabotage" (Drop #17) . What is the Algorithmic Sabotage Research Group?
The problem of looms large. Every tool released by ASRG becomes a potential data point for adversarial training. AI companies could theoretically train their models to detect and discard “poisoned” data points, or engineer crawlers that bypass tarpits entirely. Furthermore, the sheer scale of modern AI training—often involving trillions of tokens scraped from across the internet—means that isolated instances of data poisoning might be statistically insignificant. As one observer on Mastodon noted, “I have no idea if any of those scraped pages are finding their way into training data, but it seems likely with those numbers.”
Most human reviewers would ignore it. But not all. And the ASRG operated on the law of large numbers. Save 0.1% of the people the algorithm was quietly murdering, and you’ve saved thousands.
: Sabotage breaks the automatic progression of algorithmic decision-making, forcing human friction back into the system.