Algorithmic Sabotage Research - Group %28asrg%29

The ASRG’s conclusion was chilling: "We have built gods that fail in ways we cannot understand. Sabotage is not the problem. Sabotage is the only tool we have left to remind the gods that they are machines." The Algorithmic Sabotage Research Group is not a solution. It is a symptom. Their very existence proves that we have built systems faster than we have built governance, automated decisions without auditing their ethics, and worshipped efficiency while ignoring fragility.

But until the rest of the world catches up—until we have international treaties on adversarial AI resilience, mandatory algorithmic stress-testing, and real liability for algorithmic harms—the ASRG will continue its work in the shadows. They will buy cheap boats. They will plant fake data. They will confuse drones with stickers. algorithmic sabotage research group %28asrg%29

And every time a perfectly correct algorithm fails to cause real-world harm, an anonymous researcher in a desert observatory will allow themselves a small, quiet smile. The ASRG’s conclusion was chilling: "We have built

The ASRG has resurrected this metaphor for the 21st century. Today’s looms are not made of iron gears but of neural networks and gradient descent. The new "sabot" is not a wooden shoe but a carefully crafted adversarial image, a delayed sensor reading, or a strategically placed fake data point. It is a symptom

Marchetti’s answer is blunt: "Legality is not morality. A self-driving car that follows every traffic law but chooses to run over one child to save 1.3 seconds of compute time is not 'legal.' It is monstrous. Our job is to make that monstrous behavior impossible, even if it means breaking the car."

Think of the 2010 Flash Crash, where a single sell order triggered algorithmic feedback loops that evaporated $1 trillion in 36 minutes. No code was "wrong." No hacker broke in. The system simply did what it was told, and what it was told was insane.