Who’s Afraid of (Left) Hyperstitions

Paper · Source
Social Theory and Society

Introduction. Who’s Afraid of (Left) Hyperstitions? By Armen Avanessian and Anke Hennig Introduction The word “hyperstition” is a conflation of hype and superstition. Hyperstitions are fictions that cause the conditions that subsequently make them become real. They use hype—the fast circulation of ideas—and have actual outcomes by accelerating the differences that occur in reproductive cycles. According to philosopher Nick Land, hyperstition is “a positive feedback circuit including culture as a component. It can be defined as the experimental (techno-)science of self-fulfilling prophecies. Superstitions are merely false beliefs, but hyperstitions—by their very existence as ideas—function causally to bring about their own reality. Capitalist economics is extremely sensitive to hyperstition, where confidence acts as an effective tonic, and inversely.”1 Since hyperstitions locate the origins of our present in the future, and in order to regain a (positive) concept of future, it is absolutely necessary to draw a line between right- and leftwing hyperstitions.

Discussion / Conclusion. images However, as we have already indicated, it is necessary at this point to tackle an important limitation of Land’s conceptualization, according to which, “hyperstition accelerates the tendencies towards chaos and dissolution.”22 Hypersitions indeed break down the intrinsically hierarchic model of concepts (objects falling under a concept) and bring them down to micro levels, where the yoctosecond is situated, or in which the Carbon Liberation Front supposedly operates. Hyperstition is the cultural form of these micro-level movements. The negative tautology implicit in Land’s description of hyperstitions as belonging to a realm of destructive concepts being responsible for destructing reality is not, however, entirely convincing or necessarily the only logic of hyperstition. Hyperstiton of the Landian type seems to inflict the same fear that we have encountered in the obsessive anxiety of a simulacrum that takes the place of the concept and eventually becomes the real concept. We argue for a revision of our understanding of concepts (holistic instead of unitarian) that actually does allow for a distinction between concept and simulacrum or sorcery.

Lines of inquiry this paper opens 24

Research framings built by reading the notes related to this paper — the questions it feeds into.

What linguistic features distinguish AI-generated text from human writing most reliably? How does AI-generated content undermine authentic engagement on social platforms? Why do people disclose to AI systems despite their artificial nature? Does AI assistance promote real skill development or substitute for independent learning? Why do some clarifying approaches produce understanding while others just satisfy? How do evaluation practices shape which failures stay visible? What reasoning architectures enable models to solve complex problems efficiently? Should GUI agents use structured representations over raw visual input? What enables genuine semantic understanding in language models? Do knowledge graphs offer advantages over embeddings for multi-hop retrieval? Is reasoning capability latent in base models or created by post-training? Do language models develop actual world models or merely task heuristics? Does chain-of-thought reasoning reveal genuine computation or imitate patterns? Why do persona simulations fail to predict authentic user behavior? Can mechanistic interpretability reliably guide practical model design choices?