Algorithmic Sabotage Research Group Asrg -

In a world where algorithms decide who gets a loan, what news you read, and even which military targets are engaged, a quiet but radical resistance is brewing. Enter the Algorithmic Sabotage Research Group (ASRG)

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Disrupts the model's training integrity; invalidates unauthorized scraping. algorithmic sabotage research group asrg

Look up focusing on critical technology studies.

The ASRG operates within a broader ecosystem of resistance to surveillance and AI extraction. It has been featured in prestigious European research projects like "Figure It Out," supported by the Creative Europe program, alongside partners such as Drugo More (Croatia), Labomedia (France), and the Unfinished Foundation (Malta). These collaborations help ground the group's radical tactics within the context of transdisciplinary workshops exploring art, science, and technology. In a world where algorithms decide who gets

The core philosophy of the ASRG is rooted in the concept of "algorithmic sabotage"—deliberate actions taken to confuse, slow down, or break automated systems. Drawing inspiration from historical labor movements, particularly the Luddites who smashed machinery not out of technophobia, but to protect their livelihoods, the ASRG updates this resistance for the digital age.

For example, consider a predictive policing algorithm. A conventional audit might measure racial bias in arrest predictions. An ASRG experiment, however, might feed the system thousands of false emergency reports from a wealthy neighborhood, forcing police resources to be misallocated until the algorithm’s risk model collapses. The resulting chaos would reveal not just a statistical bias, but the political economy of attention: who gets to be visible to the state, and who remains invisible until they become a threat. I'll perform multiple searches to cover various aspects

Corrupting the datasets used to train AI to prevent the development of harmful predictive tools.

The real-world consequences of the ASRG's research are far-reaching. For example: