The Evolution of Scientific Knowledge From Certainty to Uncertainty

About this book

The Evolution of Scientific Knowledge aims to provide scientists and engineers, and those interested in scientific issues, with a concise account of how the nature of scientific knowledge evolved from antiquity to a seemingly final form in the Twentieth Century that now strongly limits the knowledge that people would like to gain in the Twenty-first Century. Some might think that such issues are only of interest to specialists in epistemology (the theory of knowledge); however, today's major scientific and engineering problems – in biology, medicine, environmental science, etc. – involve enormous complexity, and it is precisely this complexity that runs up against the limits of what is scientifically knowable. To understand the issue, one must appreciate the radical break with antiquity that occurred with the birth of modern science in the Seventeenth Century, the problems of knowledge and truth engendered by modern science, and the evolution of scientific thinking through the Twentieth Century.

The Evolution of Scientific Knowledge concludes by considering the impact of scientific uncertainty on the translation of scientific knowledge into means to alter the course of Nature – that is, the effect of uncertainty in engineering. It proposes a course of action based on integrating existing partial knowledge with limited data to arrive at an optimal operation on some system, where optimality is conditioned on the uncertainty regarding the system. As for a new scientific epistemology in which valid knowledge can be defined, that awaits the bold efforts of fertile minds enriched with the mathematical, scientific, and philosophic education required for such a quest.

Contents

Acknowledgments
Preface

Introduction: Challenging Times
    Evolution of Galilean–Newtonian Scientific Thinkings
    A Radical Shift in the Narrative

1 Why Epistemology?
    1.1 The Desire to Know
    1.2 What is Epistemology?
    1.3 Modern Science
    1.4 The Crisis of Complexity

2 Pre-Galilean Science
    2.1 Deep Roots
    2.2 Aristotle: Causality as the Ground of Knowledge
          2.2.1 Plato: Allegory of the cave
          2.2.2 Aristotle's epistemology
    2.3 Evolution and the Argument from Design
    2.4 The Fall and Rise of Reason
          2.4.1 Believe that you may understand
          2.4.2 Islamic transition
          2.4.3 The Thirteenth Century: an age of reason
          2.4.4 William of Ockham: the razor
    2.5 Copernicus Moves Man from the Center of the Universe

3 The Birth of Modern Science
    3.1 The Seventeenth Century
    3.2 Francis Bacon: Empirical Method
          3.2.1 Idols of the mind
          3.2.2 Forms as law
          3.2.3 Experimental design
    3.3 Galileo: The Birth of Modern Science
          3.3.1 Trial of Socrates
          3.3.2 Trial of Galileo
    3.4 Isaac Newton: Hypotheses Non Fingo
    3.5 Determinism
    3.6 Dissenting Voices
          3.6.1 René Decartes: Cogito ergo sum
          3.6.2 Blaise Pascal: the eternal silence

4 Reflections on the New Science
    4.1 Critique of Knowledge
    4.2 John Locke: The Mind as White Paper
          4.2.1 Innate principles of thought
    4.3 George Berkeley: Esse Est Percipi
    4.4 David Hume: Reason Is Humbled
          4.4.1 The ghost in the Galilean brackets
          4.4.2 Modernity arrives
    4.5 Immanuel Kant: Critique of Reason
          4.5.1 Categories of the understanding
          4.5.2 The transformation of human reason
          4.5.3 The moral philosopher
    4.6 Jean-Jacques Rousseau: No to Science
          4.6.1 Kant and Rousseau
    4.7 Mill: Metaphysics through the Back Door
    4.8 Bertrand Russell: Causality, a Relic of a Bygone Age
    4.9 James Clerk Maxwell: Hoping for an Intelligible Theory

5 A Mathematical—Observational Duality
    5.1 The End of Intelligibility
    5.2 Quantum Mechanics
          5.2.1 The Bohr atom
          5.2.2 Wave–particle duality
          5.2.3 The uncertainty principle
    5.3 Epistemological Reflections on Quantum Theory
          5.3.1 The Copenhagen interpretation
          5.3.2 Knowledge depends on the questions asked
          5.3.3 Nature is absurd
    5.4 The Structure of Scientific Knowledge
    5.5 Scientific "Truth"
    5.6 A New Role for Reason
    5.7 Deterministic or Stochastic Models?

6 Complex Systems: A New Epistemological Crisis
    6.1 The Twenty-first Century: Starved for Data
    6.2 Gene Regulatory Networks
          6.2.1 Deterministic Boolean networks
          6.2.2 Probabilistic Boolean networks
    6.3 Validation of Complex Systems
          6.3.1 Validation of deterministic models
          6.3.2 Validation of stochastic models
    6.4 Model Uncertainty
    6.5 Data Mining
          6.5.1 Overfitting
          6.5.2 Asymptotic theory
    6.6 Limitations of Science

7 Translational Science under Uncertainty
    7.1 Translational Science
    7.2 Anatomy of Translational Science
          7.2.1 Structural intervention in gene regulatory networks
    7.3 Operator Design in the Presence of Model Uncertainty
          7.3.1 IBR structural intervention in gene regulatory networks
    7.4 Pattern Classification
          7.4.1 Optimal classification for a known feature-label distribution
          7.4.2 Intrinsically Bayesian robust classification
    7.5 Posterior Distribution
          7.5.1 Optimal Bayesian classification
          7.5.2 Distribution-free classification
          7.5.3 Detector selection
    7.6 Translational Science under Model Uncertainty
          7.6.1 Wiener filter
          7.6.2 IBR Wiener filter
          7.6.3 A more general synthesis protocol
    7.7 Objective Cost of Uncertainty
    7.8 Small-Data Epistemology

References
Index

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