More-than-human history: Describing the future as a repeating update of Artificial Intelligence

Abstract

This article examines artificial intelligence systems as temporalizing agents in a more-than-human history. It engages in an interdisciplinary discussion across the sociology of algorithms, informational ethics, and philosophy of mind, informed by historical theory, to assess how automation's ubiquity adds new dimensions to the study of the contemporary historical condition. The central argument is that artificial temporalization stems from natural language simulation via learning algorithms. The article clarifies this through a code description and a technical image demonstration, illustrating the 'rendering' or 'digitization' of human experiences into data patterns, further replicated or updated by artificial agents. This process highlights the vectorization of human experience and stands for what I term 'necessary computation'. In contrast, the piece also argues that 'contingent computation', capable of novel outputs, transcends mere technical discourse. It emphasizes the role of ethics and transparency in data management and AI system training, crucial for comprehending Artificial Intelligence as a historical field open to diverse, potentially non-human, cognitive form.

Keywords:
artificial Intelligence; updatism; historical futures