Comparing AI with animals, aliens, and deities is highlighted, highlighting both the promise and the limits of extending the authors' concepts of mind and meaning beyond the human case.
Abstract
This volume, Communicating with AI: Philosophical Perspectives, examines a pressing question of our time: what does it mean to communicate with large language models (LLMs) such as ChatGPT, Claude, Gemini, and DeepSeek? With billions of human–AI interactions on the horizon, understanding whether these systems share our language, possess understanding, or function instead as novel instruments is an urgent theoretical and practical task. The essays collected here bring the tools of philosophy to bear on the distinctive challenges posed by AI. The contributions are organized into four parts. Part I probes the foundations of meaning, asking whether LLM outputs can be genuinely meaningful or whether they should be thought of as mere signals or measurements. Part II explores the possibility of alien semantics and externalist accounts of AI meaning, pushing the boundaries of how different from us an AI mind or language could be while still remaining intelligible. Part III investigates the social and normative dimensions of AI communication, focusing on trust, responsibility, and the risks of projecting human concepts onto machine outputs. Part IV turns to the future, considering the architectures of artificial minds and the unsettling ethical possibilities of superintelligent systems that may reason about values in ways inaccessible, or even hostile, to human interests. A central methodological theme runs throughout: the need to de-anthropomorphize our understanding of communication without emptying it of substance. By comparing AI with animals, aliens, and deities, the essays highlight both the promise and the limits of extending our concepts of mind and meaning beyond the human case. Collectively, the volume offers a rigorous philosophical framework for grappling with the metaphysical, epistemic, and ethical stakes of our emerging conversations with AI.
It is argued that consciousness is a sine qua non for understanding which is absent in the understanding of AI systems and that the age of AI demands a reformulation of the notion of understanding itself.
A unified vision is offered: intelligence arises from constrained architectures and emergent patterns, and as AI systems become more autonomous, they may require surrogate forms of consciousness to handle complex, real-world challenges—though these will never fully replicate the biological original.
John-Michael M. Kuczynski· Communication & Cognitio...· 0 citations
This work develops a conception of understanding fit for polyphonic AI that centres on sound circuitry that is reliably and correctly recruited and in control of outputs, and can do the work of guiding trust in AI.
It is argued that AI systems themselves will increasingly participate in the reconstruction of the authors' shared epistemic environment because they readily supply narrative material and personalised interpretive scaffolding at precisely the moment when users'conceptual assumptions may already be loosened.
T. Pollak, H. Morrin, Murray Shanahan· 0 citations
The Intellect-Emotion-Action Profile (IEAP), a purpose-built lexical framework featuring an inductively constructed dictionary from AI-generated text that decomposes any response into the proportional usage of intellectual, affective, and action words, is introduced.
William C. Kouns· Frontiers in Artificial Inte...· 0 citations
This study argues that AI embodies a calculative mode of thought that reduces knowledge to data, patterns, and predictive models, treating both the world and human subjects as resources for optimization, and proposes Heideggerian meditative thinking (Gelassenheit) as a framework for preserving human insight, reflection...
Ninio Sagucom· Dianoesis· 0 citations
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