Rathgeber Benjamin

Whether Generative AI (GenAI) is creative is a question that has generated considerable philosophical debate yet remains unresolved. We argue that this impasse is not accidental but symptomatic of a wrong concep-tualization: The dominant question – is GenAI a creative agent? – presupposes that creativity is a property residing in a system. Instead, we propose to ask the question: what role does GenAI play as a medium of creative practice? This means that GenAI is neither a passive tool, nor an autonomous system, but a tech-nology that actively structures the possibility space of creative expression. We propose five “dimensions of creativity” – modal, expressive, disruptive, reflexive, and integrated – understood as a process in which each dimension generates a tension that the next takes up and transforms. Applying this framework to GenAI, we show that the creative process itself changes under the new technical conditions GenAI introduces, and that the central risk is a drift toward pure reproduction – the collapse of creative practice into the recombination of what the medium has already mapped. We argue that resisting this drift requires bringing the medium to its own limits: making the technological conditions of creative practice visible and transparent, thereby transforming reproductivity back into creativity.

Each technology advances at its own pace, often indifferent to theoretical and philosophical-scientific conceptualizations. In the case of technologies like artificial intelligence (AI), and especially generative AI (GenAI), developments are so rapid that conceptual and epistemological reflections struggle to keep up, even at the level of basic definitions. Yet these definitions carry significant non-theoretical implications, including social, legal, and policy-related consequences. In this paper, I offer some reflections on the definition of GenAI proposed by Ronge et al. (2025), using it as an opportunity to highlight the most relevant aspects of the ongoing debate sparked by these new AI systems. In doing so, we will seek to explore the implications of generative AI systems in the context of human interaction, particularly in light of their role as active supports rather than passive tools. This shift, coupled with the increasingly anthropomorphic perception of their capabilities, sets GenAI systems apart from any previous technologies, not only in terms of technical features but also in how they are perceived by everyday users.

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.

Die aktuellen Entwicklungen Künstlicher Intelligenz vermitteln den Eindruck grenzenloser Möglichkeiten. Sie strahlen dabei in alle gesellschaftlichen Bereiche aus und bestimmen unsere lebensweltlichen Praxen maßgeblich mit. Wie bei allen großen technologischen Transformationen stellt sich dabei die Frage nach deren zukünftigen Potentialen, umgekehrt aber auch nach ihren prinzipiellen Grenzen. In diesem Spannungsverhältnis kann philosophische Reflexion durch begriffliche Klarheit für Orientierung sorgen und einen (auf-)klärenden Beitrag leisten, welcher dabei hilft ernstzunehmende technische Möglichkeiten von unvernünftigen Spekulationen sinnvoll unterscheiden zu können. Der vorliegende Band trägt damit zu einem übergreifenden Diskurs über die Beurteilung von Möglichkeiten und Grenzen Künstlicher Intelligenz bei.

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.

Mirror neurons are a particular class of visumotorical neurons, originally discovered in area F5 of the monkey premotorical cortex. They discharge both (1) when the animal performs a specific action and (2) when it observes a similar action. Actually, it is often assumed that this unique functioning could explain different abilities ranging from imitation behaviour to faculty of speech. In this article, we discuss the question what is meant by the expression: The neuron x mirrors the action y by perception z . The problem resulted from the fact, that neurons cannot mirror anything—except in the light of a metaphorical description. How can this metaphorical description be dissolved for a distinct and explicit scientific terminology? The basic steps of our argumentation are as follows. (1) The expression to mirror can be defined in mutual relation between different types of actions in respect of at least two participants: the proponent A, who conducts a special action x (e.g. grapping a peanut (A(x)) and the opponent B who observes these actions y (B(y)) and vice versa. (2) In order to detect different tokens as a type of action and to guarantee the changes of the participants there must be constituted a speech act in a dialogue, in which types of actions are defined by the invariance of special equivalence. (3) The change of the participants represents and defines the metaphorical expression to mirror in the light of a non-metaphorical and reproducible schema. (4) Then, the invariance of the type of action can be identified in different speech acts. Three of them (called narratives) were defined paradigmatically: (4.1) the ethological-narrative; (4.2) the neurophysiological-narrative; (4.3) the language-narrative. (5) These narratives are the modelling and explicit formulations of the primarily metaphorical expression: The neuron x mirrors the action y by perception z

Metaphors, allegories and other kinds of indirect speech-acts and catachretical phrases are usually considered to be the very opposite of scientific theories. An alternative can be identified in the constructivists’ approach, dealing with catachretical expressions as a starting point for the explication of scientific language games. The aim of this paper is to demonstrate such an alternative point of view, dealing with metaphorical applications of the term information within biological narratives