The Nihilist’s Dictionary

  • 2025/08/27 01:43


From back cover:

“Those who still say that technology is “neutral,” “merely a tool,” have not yet begun to consider what is involved…Today we experience control as a steady reduction of our contact with the living world, a speeded-up Information Age emptyness drained by computerization and poisoned by the dead, domesticating imperialism of high-tech method. Never before have people been so infantalized, made so dependant on the machine for everything; as the earth rapidly approaches its extinction due to technology, our souls are shrunk and flattened by its pervasive rule. Any sense of wholeness and freedom can only return by the undoing of the massive division of labour at the heart of technological progress. This is the liberatory project in all its depth.”

The Nihilists Dictionary pdf

Memory Loss: Collected Communiques from CLODO

  • 2024/06/16 08:34

“Memory Loss” presents a history of the French group CLODO, which attacked and sabotaged computers in the 1980s. The zine contains a timeline of action, two communiques, and an interview of the group. Along with these items, there is a helpful introduction which contextualizes the group and its activities and situations them in relation to other anti-technology groups. The zines comes at a good time, coinciding with the release of a new film titled Machines in Flames that documents the group.

memory_loss-boo pdf

Artificial Intelligence and Machine Learning

  • 2023/10/01 19:23

From back cover:

“The state will use machine learning to filter surveillance footage for criminals and potential criminals; capitalism will use machine learning to identify ways to appropriate resources and maximize profits…This doesn’t mean, though, that anarchists could appropriate machine learning systems for our own goals. Quite the contrary! For machine learning systems are not only at the beck and call of the forces of order through their emergence from prompts, but far more importantly, remain tethered to these forces through the models they create. The sources on which machine learning systems feed are the troughs of ‘big data’: billions of statistical, lexicographical, literary, medicinal, military and civilian, surveillance-based and contractually obligated, creative or robotic, data points.

…To sabotage a machine learning system, then, it must be fed content that is in itself coherent, very likely meets evaluation criteria, and yet leads the system’s propagations into a feedback frenzy from which they can’t escape. The machine learning system must be fed text that coherently self-destructs. And the text must directly concern the concept(s) that the machine learning system is modelling, to meet its evaluation criteria.”

Artificial Intelligence and Machine Learning pdf