Sabotage Research Group Asrg _top_: Algorithmic

: Instead of optimizing for a goal, ASRG researchers would navigate an algorithm’s latent space to find “dead zones”—inputs that produce nonsense, contradictions, or infinite loops. In a content moderation AI, this might reveal suppressed speech categories; in a medical diagnosis tool, it might uncover demographic blind spots.

The ASRG distinguishes itself by turning high-level theory into "praxis"—the practical application of ideas. They facilitate collaborative tools and workshops designed to help people "get their hands into the guts of systems". This "practice-led" research might involve scrambling image data to evade facial recognition or developing tactics for "techno-disobedience" that allow communities to reclaim digital spaces. algorithmic sabotage research group asrg

They believe the first step in addressing technological harm is political, not technical. Real change comes from social autonomy and mutual aid, not just better code. : Instead of optimizing for a goal, ASRG

Their published works and "how-to" guides often focus on . This involves creating tools that don't just "fix" a bug in a system, but render the system’s logic completely non-functional. For example, if a facial recognition system is being used for mass surveillance, ASRG-style sabotage focuses on making the environment "unreadable" through camouflage, infrared interference, or algorithmic "dazzle." Key Areas of Inquiry Real change comes from social autonomy and mutual