Science, Strategy and War The Strategic Theory of ... - Boekje Pienter

Paradigm shiftBeyond NewtonIn the past four decades such a Kuhnian scientific paradigm shift has occurred, according tovarious authors, or at least a novel conceptual framework has evolved to complement thereigning one in important ways, and Boyd was intimately aware of these views. This shift washighly visible in a much discussed and bestselling work such Douglas Hofstadter’s Gödel,Escher, Bach (1979), an influential book Boyd was familiar with, but Polanyi and Heisenbergalso explicitly alluded to the end of the Newtonian paradigm 70 , as well as a host of otherauthors featuring on the bibliography of Patterns of Conflict, who were among the first todiscuss the contemporary scientific changes in popular scientific works, such as FritjofCapra’s The Tao of Physics (1976), Richard Dawkins’ The Selfish Gene (1976), E.O. Wilson’s OnHuman Nature (1978) and Ilya Prigogine’s widely acclaimed book Order out of Chaos (1984).Together with other bestselling works like Capra’s The Turning Point: Science, Society and theRising Culture (1982), Stephen Hawking’s A Brief History of Time (1988), Dawkins’ The BlindWatchmaker, Stephen Jay Gould with a whole list of bestselling studies on paleontology andevolution theory, James Gleick’s Chaos (1987) and Mitchell Waldrop’s Complexity, TheEmerging Science at the Edge of Order and Chaos, these books marked the popular acceptance ofscience 71 .The shift can be described as a movement away from a scientific worldview entirelybased on what are often and variously labeled Cartesian, Newtonian, Linear, Analytical,Objectivistic, Reductionist, Deterministic or Mechanical concepts, towards a focus onchange, diversity, evolution, unpredictability, complexity, uncertainty, non-equilibrium andnon-linearity.The Newtonian paradigm rests firmly upon linear principles, whereas the recentemerging paradigm stresses non-determinism and non-linearity. Linear systems played animportant role in the development of science and engineering, as their behaviors are easilymodeled, analyzed, and simulated. A linear system has two defining mathematicalcharacteristics. First, it displays proportionality. If some input X to the system gives anoutput of Y, then multiplying the input by a constant factor A yields an output of AY. Thesecond characteristic of linear systems is superposition or additivity which means as much asthat the whole is equal to the sum of its parts. That is, if inputs X1 and X2 give outputs Y1and Y2 respectively, then an input equal to X1 + X2 gives an output of Y1 + Y2. Systemsthat do not display these characteristics are called nonlinear.Importantly, linear systems of equations can be solved analytically or numerically.Given a set of linear equations and initial conditions, we can calculate the future values ofthe variables. Consequently, if we can describe a system by a linear mathematical model, wecan determine its future states exactly from its given initial state. A large body ofmathematics has grown up around linear systems and techniques for their solution.Reductionism is an important consequence of the Newtonian paradigm.Reductionism is a methodology for solving problems. The analyst breaks the problem intoits constituent pieces, solves each piece separately, then sums the results from the pieces toobtain the overall solution to the problem. This is a natural consequence of superposition. Italso leads to the principle of replication which means that the same action or experiment70 Not only is it on the list of personal papers, other authors such as Paul Davies frequently referred toHofstädter.71 Watson, pp.740, 757.94