David Gunkel

This response engages the special issue on the mind–technology problem in the age of generative AI by situating its central concerns within a longer philosophical genealogy. While the editors productively frame contemporary debates about large language models and GenAI as successors to the Cartesian mind–body problem, this commentary argues that the underlying structure of the problem emerges much earlier, most notably in Plato’s Phaedrus. Plato’s reflection on writing as a disruptive cognitive technology already articulates the key tensions that animate current discussions of AI: whether technologies extend or undermine cognition, how they transform knowledge practices, and how they reconfigure agency and responsibility. More importantly, the Phaedrus destabilizes the opposition between mind and technology by reinscribing writing within thought itself, revealing cognition as dependent on technical inscription. Drawing on Derrida’s reading of Plato, this response suggests that the mind–technology problem is not simply about how technologies affect minds, but about how the concept of mind has always been constituted through technological metaphors and practices. Seen in this light, GenAI intensifies—rather than inaugurates—a longstanding philosophical entanglement.

Philosophers love a hierarchy. Nothing seems to fit the needs and desires of the moral imagination more than the promise of a clean, orderly ladder of moral worth with (not surprisingly) humans at the top, a few “higher” animals somewhere beneath, plants and rocks at the bottom, and now, far outside the frame, artificial agents politely waiting their turn. In addition, it is in the context of AI that this impulse to police the moral boundary has returned with renewed urgency. Many commentators, including Adrianna de Ruiter in her recently published essay ‘Dangerous Liaisons’ (2025), warn that relational approaches to AI moral status are dangerous, misleading, or lacking philosophical rigor. They insist that we must firmly anchor moral considerability in some intrinsic, scientifically respectable property (i.e., sentience, consciousness, phenomenal experience, and vulnerability) and that anything less—especially when it comes to AI—is dangerous.

This essay argues that large language models (LLMs), such as GPT-type transformer architectures, actualize Jacques Derrida’s concept of différance. Originally introduced within the context of poststructuralist theory and semiotics, différance designates the way meaning is produced through a system of differences and deferrals, rather than stable reference. Drawing on this framework, the essay examines how LLMs generate meaningful content by calculating statistical differences across massive textual corpora—foregrounding processes of spacing, temporalization, and trace. It proposes that LLMs can be understood as “différance engines” that computationally enact the very mechanisms Derrida theorized. In addition to tracing these points of intersection, the essay reflects on the philosophical consequences of this alignment, including challenges to logocentrism, authorship, and the metaphysics of presence. It then addresses three potential criticisms of this approach, arguing that the use of Derrida’s work in this context is not a misappropriation, but a continuation and reiteration of its logic. And it concludes by identifying three systemic limitations and by charting opportunities for future research in this domain. The essay thus shows, on the one hand, how LLMs can be read through poststructuralist theory, and on the other, how poststructuralist theory can be clarified and rendered accessible through the technical operations of contemporary AI.

Large Language Models (LLMs), like OpenAI’s ChatGPT and Google’s LaMDA, are not only the most disruptive and controversial technologies of our time, but also offer an unprecedented opportunity to examine human cognition and philosophically question the very nature of language, communication, and intelligence. What is consciousness? What is language? Are LLMs authors? Are LLMs the end of writing as we know it? In _Communicative AI_, Mark Coeckelbergh and David J. Gunkel offer a critical introduction to LLMs, investigating the philosophical significance of this technology and its practical ramifications. Mobilizing resources from contemporary philosophy, history of ideas, linguistics, and communication theory, the book invites us to re-think some long-standing philosophical issues concerning language, consciousness, truth, authorship, and writing. Through a blend of theoretical analysis, accessible explanations, and practical examples, the book provides readers with a comprehensive overview of the role that this powerful new technology is already playing in our lives. This is a must-read for students and scholars across the humanities and the social sciences, as well as for anyone intrigued by the intersection of technology, language, and human thought.

Robots as social companions in close proximity to humans have a strong potential of becoming more and more prevalent in the coming years, especially in the realms of elder day care, child rearing, and education. As human beings, we have the fascinating ability to emotionally bond with various counterparts, not exclusively with other human beings, but also with animals, plants, and sometimes even objects. Therefore, we need to answer the fundamental ethical questions that concern human-robot-interactions per se, and we need to address how we conceive of »good lives«, as more and more of the aspects of our daily lives will be interwoven with social robots.

In both law and ethics, we typically distinguish between persons, who are subjected to and the subjects of the law, from things, which are nothing more than objects or property owned by persons. This way of dividing up and categorizing all that exists has been useful and expedient, even if we have, at various times in our history, mistakenly and unfortunately categorized as things that which later came to be seen as other persons. The question that now confronts us in the face of artificial intelligence is whether this new kind of being is to be classified as a thing or instrument that we can use and even abuse as we see fit, whether it should be classified as another person or another kind of person with its own set of rights and responsibilities, or whether it might be something other that is both/and or neither/nor. This chapter will present and evaluate the costs and benefits of all three options and conclude by proposing a moral and legal ontology suitable for responding to and taking responsibility for artificial intelligence.