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Beschreibung
How the concept of a pattern, as understood in information science and applied in contemporary AI, can address deep questions in science and philosophy.
The explosive growth of AI and machine learning in recent decades is predicated on the recognition and exploitation of patterns in data. Of course, scientists have engaged in their own—less automated—processes of pattern recognition since the birth of science itself, and biological organisms evolved their own neural networks for pattern recognition long before people and their technology came along.
In his seminal work, “Real Patterns,” philosopher and cognitive scientist Daniel Dennett laid out a road map for connecting the idea of “patterns” as understood by information theory to the practices of scientists and to our own cognitive capacity to model and predict the world around us. In this book—the first dedicated to the topic of real patterns—Tyler Millhouse, Steve Petersen, and Don Ross follow this road map. They explore the relevance of patterns to important aspects of both science and nature, including the emergence of high-level structure in physics, the nature of biological species, the measurement of welfare in economics, the evaluation of causal models, and the possibility of understanding in large neural networks.
The explosive growth of AI and machine learning in recent decades is predicated on the recognition and exploitation of patterns in data. Of course, scientists have engaged in their own—less automated—processes of pattern recognition since the birth of science itself, and biological organisms evolved their own neural networks for pattern recognition long before people and their technology came along.
In his seminal work, “Real Patterns,” philosopher and cognitive scientist Daniel Dennett laid out a road map for connecting the idea of “patterns” as understood by information theory to the practices of scientists and to our own cognitive capacity to model and predict the world around us. In this book—the first dedicated to the topic of real patterns—Tyler Millhouse, Steve Petersen, and Don Ross follow this road map. They explore the relevance of patterns to important aspects of both science and nature, including the emergence of high-level structure in physics, the nature of biological species, the measurement of welfare in economics, the evaluation of causal models, and the possibility of understanding in large neural networks.
How the concept of a pattern, as understood in information science and applied in contemporary AI, can address deep questions in science and philosophy.
The explosive growth of AI and machine learning in recent decades is predicated on the recognition and exploitation of patterns in data. Of course, scientists have engaged in their own—less automated—processes of pattern recognition since the birth of science itself, and biological organisms evolved their own neural networks for pattern recognition long before people and their technology came along.
In his seminal work, “Real Patterns,” philosopher and cognitive scientist Daniel Dennett laid out a road map for connecting the idea of “patterns” as understood by information theory to the practices of scientists and to our own cognitive capacity to model and predict the world around us. In this book—the first dedicated to the topic of real patterns—Tyler Millhouse, Steve Petersen, and Don Ross follow this road map. They explore the relevance of patterns to important aspects of both science and nature, including the emergence of high-level structure in physics, the nature of biological species, the measurement of welfare in economics, the evaluation of causal models, and the possibility of understanding in large neural networks.
The explosive growth of AI and machine learning in recent decades is predicated on the recognition and exploitation of patterns in data. Of course, scientists have engaged in their own—less automated—processes of pattern recognition since the birth of science itself, and biological organisms evolved their own neural networks for pattern recognition long before people and their technology came along.
In his seminal work, “Real Patterns,” philosopher and cognitive scientist Daniel Dennett laid out a road map for connecting the idea of “patterns” as understood by information theory to the practices of scientists and to our own cognitive capacity to model and predict the world around us. In this book—the first dedicated to the topic of real patterns—Tyler Millhouse, Steve Petersen, and Don Ross follow this road map. They explore the relevance of patterns to important aspects of both science and nature, including the emergence of high-level structure in physics, the nature of biological species, the measurement of welfare in economics, the evaluation of causal models, and the possibility of understanding in large neural networks.
Über den Autor
Tyler Millhouse is Assistant Professor of Practice in the College of Information Science at the University of Arizona. His work has appeared in leading journals, such as the Australasian Journal of Philosophy, The British Journal for the Philosophy of Science, and Philosophy of Science.
Steve Petersen is Professor of Philosophy at Niagara University. His work has appeared in journals like Philosophical Studies and Synthese, and in collections like The Ethics of Artificial Intelligence. He has been supported by the Survival and Flourishing Fund, the Center for Effective Altruism’s Long-Term Future Fund, the Future of Life Institute, and the Center for AI Safety.
Don Ross is Professor in the School of Society, Politics, and Ethics at University College Cork, Ireland; Professor in the School of Economics at the University of Cape Town, South Africa; and Program Director for Methodology at the Center for the Economic Analysis of Risk, Robinson College of Business, Georgia State University, Atlanta. He is an author or editor of 20 books, including Every Thing Must Go (with James Ladyman) and most recently The Gambling Animal (with Glenn Harrison).
Steve Petersen is Professor of Philosophy at Niagara University. His work has appeared in journals like Philosophical Studies and Synthese, and in collections like The Ethics of Artificial Intelligence. He has been supported by the Survival and Flourishing Fund, the Center for Effective Altruism’s Long-Term Future Fund, the Future of Life Institute, and the Center for AI Safety.
Don Ross is Professor in the School of Society, Politics, and Ethics at University College Cork, Ireland; Professor in the School of Economics at the University of Cape Town, South Africa; and Program Director for Methodology at the Center for the Economic Analysis of Risk, Robinson College of Business, Georgia State University, Atlanta. He is an author or editor of 20 books, including Every Thing Must Go (with James Ladyman) and most recently The Gambling Animal (with Glenn Harrison).
Inhaltsverzeichnis
Contents
Dedication
Acknowledgments
1 An Introduction to Real Patterns - Tyler Millhouse, Steve Petersen, and Don Ross
2 Real Patterns - Daniel C. Dennett
3 Patterns All The Way Up: Prolegomena to a Future Naturalized Metaphysics - James Ladyman
4 Abstractions by Patterns - Steve Petersen
5 The Problem of Platonic Codes - Tyler Millhouse
6 What Emergence Can Possibly Mean Sean M. Carroll and Achyuth Parola
7 Is Any Pattern Nonreal? - James W. McAllister
8 Real Patterns in Physics and Beyond - David Wallace
9 Disinterested Taxonomic Pluralism: Biological Classifications Track Real Patterns - Margarida Hermida
10 Deciphering the Noise: Real Patterns in Welfare From Incentivized Choice - Aleksandr Alekseev, Glenn W. Harrison, Morten Lau and Don Ross
11 Real Patterns Analysis and Causality Neutrality - Harold Kincaid and Ryan M. Nefdt
12 The Scientist in the Machine - Rosa Cao
Dedication
Acknowledgments
1 An Introduction to Real Patterns - Tyler Millhouse, Steve Petersen, and Don Ross
2 Real Patterns - Daniel C. Dennett
3 Patterns All The Way Up: Prolegomena to a Future Naturalized Metaphysics - James Ladyman
4 Abstractions by Patterns - Steve Petersen
5 The Problem of Platonic Codes - Tyler Millhouse
6 What Emergence Can Possibly Mean Sean M. Carroll and Achyuth Parola
7 Is Any Pattern Nonreal? - James W. McAllister
8 Real Patterns in Physics and Beyond - David Wallace
9 Disinterested Taxonomic Pluralism: Biological Classifications Track Real Patterns - Margarida Hermida
10 Deciphering the Noise: Real Patterns in Welfare From Incentivized Choice - Aleksandr Alekseev, Glenn W. Harrison, Morten Lau and Don Ross
11 Real Patterns Analysis and Causality Neutrality - Harold Kincaid and Ryan M. Nefdt
12 The Scientist in the Machine - Rosa Cao
Details
| Erscheinungsjahr: | 2026 |
|---|---|
| Genre: | Importe, Politikwissenschaft & Soziologie |
| Rubrik: | Wissenschaften |
| Medium: | Taschenbuch |
| Inhalt: | Einband - flex.(Paperback) |
| ISBN-13: | 9780262052030 |
| ISBN-10: | 0262052032 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Petersen, Stephen D.
Millhouse, Tyler |
| Redaktion: |
Tyler Millhouse
Steve Petersen Don Ross |
| Hersteller: | MIT Press Ltd |
| Verantwortliche Person für die EU: | Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de |
| Maße: | 224 x 150 x 24 mm |
| Von/Mit: | Stephen D. Petersen (u. a.) |
| Erscheinungsdatum: | 31.03.2026 |
| Gewicht: | 0,378 kg |