An Introduction to Technological Forecasting

Joseph P. Martino

• Publisher: Taylor & Francis
• Year: 2018
• Print ISBN: 9780815364870
• eBook ISBN: 9781351106436
• Edition: 1
• Topic: Economics
• Subtopic: Business General
• Index: Economics

Originally published in 1972 this book examines technological forecasting and assesses its merits and limitations and possible uses for society, government, industry and the military. Although technological forecasting was in its infancy when this book was originally published, it has now become part of mainstream social and economic planning.

What is the philosophical basis behind technological forecasting? In what way does it differ from any other kind of forecasting? Can it really claim to be a science, or to have a scientific basis? These are some of the questions Mr. Hacke addresses in the following essay.

A METHODOLOGICAL PREFACE TO TECHNOLOGICAL FORECASTING

JAMES E. HACKE, JR.*

Stanford Research Institute, Menlo Park, Cal., U.S.A.

ABSTRACT

To regard induction as less dependable or “logical” than deduction is a fallacy. Only when empirical, inductive methods were applied to natural phenomena did a powerful body of natural science develop. Empirical science is subject to some ambiguities and limitations; but they are characteristic of all human thought. Three unique elements in the methods of empirical science give it its power: the deliberate design of experiments seeking to disprove a hypothesis; the systematic assessment and measurement of precision; and the erection of a general body of theory “explaining” particular facts and laws.

The success of empirical science has led to adaptation of its methods in a variety of disciplines, despite objections that these methods were inappropriate in these disciplines. Although scientific statements have in themselves a predictive connotation, use of scientific facts and laws for prediction is most conspicuous in such arts as medicine and engineering.

Forecasting shares many of the limitations and ambiguities of empirical science, and many of the objections raised to forecasting stem from these limitations and ambiguities. To some extent, the forecaster may be able to adapt the testing of hypotheses, the measurement of precision, and the erection of general theories that have made empirical science so powerful. As empirical science has moved from the relatively tractable to the relatively intractable, despite objections, so has forecasting. But forecasting is not a science in itself; it is an art like medicine or engineering. Like these arts, it draws most of its facts and laws from the empirical sciences.

INTRODUCTION

This paper is an attempt to state concisely and precisely some necessary methodological antecedents to the task of forecasting technological change. In another age or culture, our starting point might have been different: Aristotelian metaphysics in the Middle Ages, or the Hegelian dialect in the Soviet Union. Here and now, however, we can hardly start with anything other than the methods of empirical science.

Section II, therefore, is a methodological consideration of empirical science. It sets forth some of its limitations and ambiguities, and seeks to show why empirical science is nevertheless our most powerful tool for learning about the phenomenal universe. We apply the findings of empirical science for their predictive value in such fields as medicine or engineering.

Section III is a methodological consideration of forecasting. It shows the close parallel between the methods of empirical science and those of forecasting, and suggests that, as science shares some of the limitations and ambiguities for which forecasting is faulted, perhaps forecasting can share some of the more powerful elements in scientific method. Forecasting is, indeed, an application of the findings of empirical science just as medicine and engineering are.

The concluding Section IV draws some inferences from these methodological considerations for the task of the technological forecaster today.

This section contains an exposition in five parts:

A. Natural science became powerful only when it adopted empirical, inductive methods.

B. These methods entail some important limitations and ambiguities.

C. But the methods of empirical science embrace other elements that assure its power.

D. The methods of empirical science have been adapted to fields of study in which some at first thought them not applicable.

E. The results of empirical science are useful for prediction, especially in medicine and engineering.

A. Induction and Deduction

Most of us tend to assume, without fully realizing it, that deduction is somehow more “logical” than induction, particularly the kind of induction known as empirical inference. In fact, the deductive syllogism itself is an axiom arrived at by empirical inference, and is as much a description of the way we think as it is a rule for being logical.

The deductive syllogism has the status of an axiom in formal logic. This is the same status that the parallel postulate has in Euclidian geometry. Euclid regarded his axioms as self-evident truths; but we have come to be distrustful of self-evident truths! Indeed, if Eistein’s Theory of General Relativity be true, the parallel postulate is neither self-evident nor so.

The most we can say about the deductive syllogism as an axiom of logic is that it leads to no logical inconsistencies. Lewis Carroll wrote a delightful fable [1] demonstrating that, if an individual refuses to accept the validity of a syllogism, one cannot force him to.

As a habit of thought, the deductive syllogism is the way we tend to state propositions that we have arrived at empirically. Take, for instance, the old exemplar syllogism: “All men are mortal; Socrates is a man; Socrates is mortal.” If this be regarded as a statement of fact, its meaning is this: We are in the habit of classifying all objects as either human or not human. The object named Socrates offers every evidence of being human. We therefore attribute mortality to Socrates, too. If he were to remain alive for an unreasonably long time, we are likely to say, “He cannot be a mere man!” We tend to put exceptions to the rule into special categories – Man-with-a-Difference – in order to keep the syllogisms inviolate.

So impressed were natural philosophers from Aristotle to Descartes with the power of syllogistic logic that they tried to derive the laws of nature from general principles conceived of as self-evident. In short, they tried to make physical science a deductive system like syllogistic logic or Euclidian geometry. But we can arrive at “self-evident” principles in science, or in anything else, only by intuitive induction! Not surprisingly, therefore, when natural scientists, beginning with Sir Francis Bacon, began self-consciously to use induction in order to discover the general principles of science, they triumphed rapidly over deductive natural philosophy.

B. Limitations and Ambiguities

Being empirical and inductive, natural science is subject to some important limitations and ambiguities. In reality, it shares these with all human thought; but they are especially important to an understanding of scientific method.

1. The scientist has no more warrant than the rest of us for claiming that because events have hitherto occurred in a certain pattern they will continue to do so. No more; but, also, no less. The scientist is in the same predicament as the rest of us: he has no proof that the past is a guide to the future; but unless he assumes it, he can do nothing. He starts with the same naive realism with which we all start; but he goes on to investigate as precisely as he can the relation between a statement like “The sun has risen every day so far” and statements like “The sun will rise tomorrow.” In the process, he gets involved with inverse probabilities and attempts like Bayes’ Theorem [2] to assess the likelihood of a future event on the basis of past experience.

2. Empirical methods will work at all only to the extent that the laws of nature are in fact capable of being expressed in a form independent of location and time. There was some speculation, a few years ago, that the value of the velocity of light in a vacuum is a slowly-fluctuating function of time. If it were, we should never be able to detect it except by comparing it with something assumed unvarying with time. For another example: A really unique event would remain forever inexplicable as far as natural science is concerned. Others might call it a miracle or a fortuitous combination of circumstances, but science could never say.

3. The scientist begins his search for regularity in his environment where we all do: with the most obvious and compelling of his experiences. Through a continual exploration and refinement, he reaches far beyond the immediate data to the unsensed and the insensible. There is no a priori guarantee that his view of reality thus achieved is independent of his starting place. The scientist must take it on faith that his science is not overly distorted by his starting point, or by his subsequent decisions about what to study.

4. Similarly, the scientist must take it on faith that his view of reality is not overly distorted by his peculiar modes of thinking. We have, for example, a great propensity for adducing patterns where none in fact exist. Think of the constellations: people, beasts, and other terrestrial objects “seen” by men of old in the stars. How much of our body of “scientific” knowledge consists of patterns adduced where non in fact exist?

5. The regularities that natural science discovers are approximate both in form and in the precision with which their parameters are known. One of the most precisely verified laws of science is the inverse-square law of electrostatic attraction or repulsion. If, in fact, the force between two charged bodies varies precisely with the inverse of the square of their distance apart, then the field inside a charged hollow conductor must be precisely zero. This result has been verified at least as accurately as one part in a billion, by graduate assistants working inside the globes of Van de Graaf machines charged to a million volts as well as in other ways. But it has been verified only for charged bodies within a finite range of size, and within a finite range of gravitational fields. What about a charged body the size of the Milky Way out in intergalactic space?

6. Almost tautologically, the goal of empirical science is to replace brute facts with general laws. We have steam tables because water vapor is not a perfect gas; but the scientist is much happier with the situation obtaining with perfect gases. For them, he can substitute Van der Waal’s equation for all the tabulated data. Heaven, for the scientist, would be the state of blessedness in which everything is explicable in terms of a Most General Possible Law and of a Single Initial Fact. Everything else, including the scientist’s own name, address, and telephone number, would be deducible from that Fact in terms of that Law.

In this imperfect world, however, we have things like the Fine-Structure Constant. That constant is close to 1/137. It is because it is, as far as we know; and that is why it is. This is such an unsatisfactory condition for the scientist that he is forced to an act of faith: Some day scientists will know why it is 1/137 and not, say, 1/138.

7. As you know, scientists are supposed to use Occam’s Razor to “shave” their hypotheses down to the minimum possible, and the simplest possible, and still account adequately for the facts. One could claim for instance, that when God created the universe in 4004 B.C., he created it complete with fossils to mislead infidel scientists; but Occam’s Razor renders this an unscientific hypothesis.

Yet the problem of deciding which of two hypotheses is the simpler is not always trivial. Often there is an element of elegance, of symmetry, of appropriateness that leads a scientist to choose a novel approach to a problem. Conversely, it is an intuitive sense of inappropriateness that makes physicists unhappy with a fine structure constant of 1/137. The numbers 1, 1/2, 2, 3, or even ε or π, alone or in combination, might be considered appropriate; but not the reciprocal of a large prime number.

The principle of symmetry has been called “the principle of minimum astonishment.” Physical theory makes great use of this principle; and it is full of pitfalls for the unwary. Indeed, as the overthrow of parity shows, our most eminent scientists can misapply it. It is really nothing more than an appeal to the individual’s intuitive sense of the fitness of things.

8. A scientific law can be disproved; but it can never be proved. A single instance in which the law fails disproves it; but no number of instances in which it works will prove it. Such instances merely confirm it: that is, make firmer.

For example, Bode’s Rule gives the radii of the planetary orbits in astronomical units: Add 4 to the sequence 0, 3, 6, 12, 24, 48, …, and divide by 10. At first there was no known planet to occupy the fifth place in this series; then the asteroids were discovered. After the rule was formulated, Uranus and Neptune were discovered; their orbits fell acceptably near the predictions of Bode’s Rule. By then, the rule seemed well confirmed! But then Pluto was discovered, and Pluto’s orbit is not even within h...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• The Futurist Library
• Preface
• A Methodological Preface to Technological Forecasting
• Forecasting the Progress of Technology
• Delphi
• How to Plot a Breakthrough
• Technological Forecasting and Space Exploration
• Technological Forecasting for the Military Manager
• Industrial Implications of Technological Forecasting
• Prospects of Technological Progress
• The Triumph of Technology: “Can” Implies “Ought”
• Thinking About Future Social Development
• Futurism: Elitist or Democratic
• Index