Techno-politics must begin with political intent, not just technical solutions. Resistance as Creativity:
The foundational theory of the group shifts the critique of technology away from passive observation and toward direct, active intervention.
The Art of Techno-Disobedience: Inside the Algorithmic Sabotage Research Group (ASRG) algorithmic sabotage research group asrg
Aiming for social autonomy and opposing the "predations of hegemonic technology" through direct, hands-on intervention. Conceptualizing "Algorithmic Sabotage"
: A cohort of artists engaged in "cultural red teaming" and creative misuse of AI, which presented at events like DEFCON 31. Anti-Spam Research Group (ASRG) Techno-politics must begin with political intent, not just
Encouraging "slow-downs" in automated environments. In the gig economy, for example, this might involve collective actions that trick dispatch algorithms into providing better rates or more humane schedules.
The group routinely publishes open-source documents and print media to democratize the philosophy of tech resistance. A prime example is the Manifesto on Algorithmic Sabotage , which serves as a rallying cry for the militancy missing from modern digital ethics. Conceptualizing "Algorithmic Sabotage" : A cohort of artists
While ASRG has made significant progress in uncovering the hidden dangers of AI-powered systems, several challenges remain:
Rather than advocating for passive avoidance, the ASRG outlines a prefigurative techno-political strategy . This means using direct technical friction to imagine alternative futures where automation does not inherently lead to exploitation. Key Pillars of the ASRG Framework
In the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML), ensuring the reliability and security of algorithms has become a paramount concern. The Algorithmic Sabotage Research Group (ASRG) is at the forefront of this challenge, focusing on the critical examination and enhancement of ML systems' resilience against adversarial attacks. This article provides an in-depth look at the ASRG's mission, methodologies, and contributions to the field of adversarial machine learning.