Injecting adversarial or corrupted inputs into a machine learning dataset.
The ASRG is currently developing the first "sabotage-resistant transformer architecture"—a modified attention mechanism that logs and restricts any gradient update that would create delayed-action failure modes.
: Developing a collective mentality to resist algorithmic violence and "fascist techno-solutionism." Related Entities (Potential Confusion) algorithmic sabotage research group %28asrg%29
: Identifying aggressive AI web-scraping bots and trapping them in a "tarpit"—a web directory designed to load websites at a near-frozen pace. This forces scraping bots to waste massive amounts of computational time and expensive processing power on useless garbage data.
The ASRG is not a traditional scientific laboratory; rather, it functions as a hub for interdisciplinary inquiry, bringing together artists, hackers, writers, and theorists to examine how code influences society, labor, and human behavior. Injecting adversarial or corrupted inputs into a machine
: Promoting non-commercial, community-led IT infrastructures as alternatives to the "AI cloud". 📖 Recommended Resources
The ASRG is a collaborative initiative aimed at analyzing, conceptualizing, and, most importantly, creating tools for sabotage against modern technological systems. Key aspects of the group include: This forces scraping bots to waste massive amounts
The ASRG categorizes sabotage into three distinct orders, ranging from individual resistance to systemic recalibration.
As of 2026, the ASRG is pivoting hard toward large language models (LLMs) and agentic AI. The new frontier of sabotage is not just code, but prompts and context . The group recently published a preprint warning of "memory-layer sabotage"—where a generative AI tool is trained to appear helpful for 90 days, then gradually introduces subtle factual errors into a corporate knowledge base. Because the errors are plausible and distributed over time, no single user flags the sabotage.