by Alexandre Gefen and Philippe Huneman
Philosophical reflection on artificial intelligence (AI) has been a feature of the early days of cybernetics, with Alan Turing’s famous proposals on the notion of intelligence in the 1950s rearming old philosophical debates on the man-system or man-machine and the possibly mechanistic nature of cognition. However, AI raises questions on spheres of philosophy with the contemporary advent of connectionist artificial intelligence based on deep learning through artificial neural networks and the prodigies of generative foundation models. One of the most prominent examples is the philosophy of mind, which seeks to reflect on the benefits and limits of a computational approach to mind and consciousness. Other spheres of affected philosophies are ethics, which is confronted with original questions on agency and responsibility; political philosophy, which is obliged to think afresh about augmented action and algorithmic governance; the philosophy of language; the notion of aesthetics, which has to take an interest in artistic productions emerging from the latent spaces of AIs and where its traditional categories malfunction; and metaphysics, which has to think afresh about the supposed human exception or the question of finitude.
In this text we want to indicate what are the new frontiers of philosophical speculation about artificial intelligence, now that GPT and other kinds of LLMs went public.
Knowing and Thinking: What Do AIs Tell Us?
If the currently established link between AI, cognitive science, and philosophy of mind is new, then philosophically questioning artificial intelligence requires us to place many questions in the long term. The project to improve human life by automating cognitive tasks, as radically original as it seems to us since the arrival of ChatGPT, develops one of Aristotle’s old intuitions about automata that would solve our routine tasks and replace our slaves. The milestones are famous automata such as Vaucanson’s duck and the mechanical Turk, right up to the exuberant robots of Boston Dynamics. To take just two examples, the congruences between the pragmatic philosophy of language proposed by Wittgenstein and how Large Language Models (LLMs) synthesize usages to generate thought probabilistically is patent, as is the link between modern cybernetics, which separates software and hardware, and the idea that thought is realizable in multiple ways, a notion formulated in the 1950s by Hilary Putnam and Jerry Fodor (sometimes called functionalism). One of these realizations would be human thought, often located “inside of” the brain, while the other would be a machine-implemented thought. Modern artificial intelligence has its roots in a long history of formalizing thought and logic. Read more »

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