Wittgenstein and AI (Volume I): Mind and Language. This is the first of two edited collections, exploring Wittgensteinian themes in AI. The issues covered by the various chapters of this volume range over a number of topics, with a specific focus on mind and language.
Wittgenstein and AI (Volume I): Mind and Language. This is the first of two edited collections, exploring Wittgensteinian themes in AI. The issues covered by the various chapters of this volume range over a number of topics, with a specific focus on mind and language.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Brian Ball is Associate Professor in Philosophy at Northeastern University London. His research spans a range of areas, notably the philosophy of mind, language and artificial intelligence, and he has taught the early history of analytic philosophy, including Wittgenstein. Alice Helliwell is Assistant Professor in Philosophy at Northeastern University London. Her research is focused on computational creativity and AI art, including questions of aesthetics and ethics. Alessandro Rossi is Assistant Professor in Philosophy at Northeastern University London. His work focuses on logic, metaphysics and the areas in which they intersect.
Inhaltsangabe
Introduction Brian Ball, Alice C. Helliwell and Alessandro Rossi Chapter 1. Wittgenstein and Turing on AI: Myth Versus Reality, Diane Proudfoot Chapter 2. Between Wittgenstein and Turing: Enactive Embodied Thinking Machines, Tomi Kokkonen and Ilmari Hirvonen Chapter 3. Wittgenstein, Psychological Language and AI, Arturo Vázquez Hernández Chapter 4. The Metonymical Trap, Éloïse Boisseau Chapter 5. The Forms of Artificially Intelligent Life: Brandom, Chomsky and Wittgenstein on the Possibility of Strong-AI, Laith Abdel-Rahman Chapter 6. Black Boxes, Beetles and Beasts, Ian Ground Chapter 7. Language Models and the Private Language Argument: A Wittgensteinian Guide to Machine Learning, Giovanni Galli Chapter 8. Simplification without Falsification: The Problem of Relevance in Logic and AI, Oskari Kuusela Chapter 9. Modelling Analogical Reasoning: One-Size-Fits-All?, Ioannis Votsis Notes on Contributors Index
Introduction Brian Ball, Alice C. Helliwell and Alessandro Rossi Chapter 1. Wittgenstein and Turing on AI: Myth Versus Reality, Diane Proudfoot Chapter 2. Between Wittgenstein and Turing: Enactive Embodied Thinking Machines, Tomi Kokkonen and Ilmari Hirvonen Chapter 3. Wittgenstein, Psychological Language and AI, Arturo Vázquez Hernández Chapter 4. The Metonymical Trap, Éloïse Boisseau Chapter 5. The Forms of Artificially Intelligent Life: Brandom, Chomsky and Wittgenstein on the Possibility of Strong-AI, Laith Abdel-Rahman Chapter 6. Black Boxes, Beetles and Beasts, Ian Ground Chapter 7. Language Models and the Private Language Argument: A Wittgensteinian Guide to Machine Learning, Giovanni Galli Chapter 8. Simplification without Falsification: The Problem of Relevance in Logic and AI, Oskari Kuusela Chapter 9. Modelling Analogical Reasoning: One-Size-Fits-All?, Ioannis Votsis Notes on Contributors Index
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