Markus Maier

The concept of Generative Artificial Intelligence (GenAI) is ubiquitous in the public and semi-technical domain, yet rarely defined precisely. We clarify main concepts that are usually discussed in connection to GenAI and argue that one ought to distinguish between the technical and the public discourse. In order to show its complex development and associated conceptual ambiguities, we offer a historical-systematic reconstruction of GenAI and explicitly discuss two exemplary cases: the generative status of the Large Language Model BERT and the differences between protein structure predictions from AlphaFold 2 and 3. Our analysis shows that there is no unique and unambiguous definition of GenAI based on a purely technical account of the term. Following this conclusion, we argue that the public discourse is not simply a less complex way of speaking, but instead transcends its technical basis. As a means to structure this newly emerging discussion landscape we introduce a non-exhaustive list of four central aspects of GenAI: (multi-)modality, interaction, flexibility, and productivity. These dimensions constitute a first step towards defining GenAI beyond its technical basis.

Künstliche Intelligenz ist eine der Schlüsseltechnologien des 21. Jahrhunderts. Sie gewinnt einen immer größeren Einfluss in allen gesellschaftlich relevanten Bereichen und transformiert diese Felder maßgeblich. Dementsprechend ist die Frage naheliegend, ob Künstliche Intelligenz auch eine zentrale Rolle für ein gelingendes Anthropozän spielen kann - und soll. Im folgenden Beitrag versuchen wir dieser Fragestellung in Bezug auf die damit (inhärent) erhobenen Geltungsansprüche nachzugehen. Dazu analysieren wir die beiden Begriffe Künstliche Intelligenz und Anthropozän und arbeiten deren Verhältnis zur technologischen Rationalität heraus. Abschließend versuchen wir anhand unserer Rekonstruktion zu zeigen, wie ein gelingendes Anthropozän aussehen sollte, wenn es seinem eigenen Anspruch gerecht werden will.

In their anthology Everything Flows: Towards a Processual Philosophy of Biology, Daniel J. Nicholson and John Dupré argue that modern theories of biology imply that the fundamental structure of reality is processual at its core. In the present work, I first examine the implicit and explicit metaphysical presuppositions the editors make in order to allow for such an inference from scientific theory to ontology. After showing the difficulties of a naïve transfer of theoretical entities to fundamental ontology, I argue that the editors can nevertheless extend their claims beyond the mere articulation of different domain ontologies. This leads to the idea of a scientifically informed induction base for an ontology of processes.