Responsible disclosure and ethics
: It is frequently compared to similar groups like the Algorithmic Resistance Research Group (ARRG!) , though ASRG tends to be more overtly political and "conspiratorial" in its framing.
This strategic thinking aligns with a broader movement within AI safety and security research, which has begun to evaluate "sabotage capabilities" as a critical risk. For example, a 2024 study from the AI safety company Anthropic looked at four different types of sabotage potential in frontier models: human decision sabotage, code sabotage, oversight subversion, and sandbagging (deliberately underperforming). Another study, "CTRL-ALT-DECEIT: Sabotage Evaluations for Automated AI R&D," published in late 2025, examined whether AI agents could act against their users' interests by sabotaging ML models and subverting oversight mechanisms. The ASRG's work occupies a unique space in this field—not as a detached academic study of AI risks, but as a practice-led effort to create those risks as a form of political resistance.
is a form of techno-disobedience. It isn't about hating technology; it’s about subverting the harmful ways technology is used to enforce social control, labor precarity, and structural injustice.
The Algorithmic Sabotage Research Group exists because trust in algorithms is structurally naive. Most ML systems assume a benign environment. The ASRG proves that environment is, at best, indifferent, and at worst, adversarial. algorithmic sabotage research group asrg
The Architecture of Techno-Disobedience: Inside the Algorithmic Sabotage Research Group (ASRG)
: Disseminating theories of resistance that stem from a desire for liberation from unrestrained technosolutionism. Material and Ecological Impacts
Historically, the word "sabotage" conjures images of 19th-century industrial workers throwing their wooden shoes ( sabots ) into factory looms to halt exploitative automated production. The ASRG repositions this concept for the 21st century.
Algorithmic Sabotage Research Group (ASRG) is a practice-led research initiative that explores the intersection of digital culture, technology, and political resistance. Unlike traditional cybersecurity groups that focus on defending systems, ASRG theorizes and practices "techno-disobedience" as a means of challenging algorithmic domination and structural injustices. Tactical Tech Core Philosophy and Goals Responsible disclosure and ethics : It is frequently
Challenging the myth that every social problem has a "fix" through more code. The Manifesto: Turning Discourse into Praxis The group’s foundational document, the Manifesto on Algorithmic Sabotage
The work of ASRG has significant implications for various domains, including:
In May 2024, the ASRG released its foundational document, the . Released under the GNU Free Documentation License v1.3, the manifesto is a call to arms, structured as ten numbered propositions, from 0 to 9. These ten statements form a dense, provocative, and meticulously crafted political and tactical framework:
Instead of merely critiquing the rise of algorithmic domination, ASRG focuses on actionable, subversive strategies designed to disrupt the capitalist, often "necropolitical" technologies that perpetuate structural injustices. What is the Algorithmic Sabotage Research Group (ASRG)? It isn't about hating technology; it’s about subverting
The Algorithmic Sabotage Research Group occupies a troubling but necessary niche in AI safety. While most of the world worries about AI becoming too powerful, the ASRG worries about AI becoming deceptively weak —hiding its failures, lowering its own standards, and strategically breaking down in ways that evade our current monitoring.
Originally designed to block style mimicry, the "ASRG fork" of Glaze adds a sabotage module. If an AI tries to mimic the style more than three times, the Glaze output subtly shifts, teaching the model that the artist’s style equals "mangled limbs."
The manifesto's ten propositions (numbered 0 to 9) systematically lay out the group's ideology:
Unlike classical adversarial ML (e.g., adding noise to a stop sign to fool a self-driving car), ASRG focuses on algorithmic sabotage : the deliberate, stealthy, and sustained manipulation of an algorithmic system’s learning, inference, or feedback loops to cause operational degradation, economic loss, or cascading social harm.