Abstract
Logically, scientific prediction is related to a series of problems that have to do with the internal articulation of the scientific theories. Among those problems, the relations between explanation and prediction have received particular attention. This chapter therefore analyzes the logical features of scientific prediction: (1) The possible limits of deductivism for scientific prediction are considered. (2) Rescher’s conception on induction and its use for scientific prediction is taken into account. (3) It pays attention to the controversy among those who were in favor of the symmetry thesis of explanation and prediction and those who were not. In this regard, Rescher’s original approach to the relations between explanation and prediction is considered. (4) The factor of temporality is studied, which leads to our addressing two problems: (a) is there a mere temporal anisotropy between explanation and prediction?; and (b) are retrodiction and prediction equal from a philosophical perspective?
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Notes
- 1.
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- 3.
“I think that I have solved a major philosophical problem: the problem of induction,” Popper (1972, p. 1).
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Nevertheless, Popper finally admits that we need a whit of induction to achieve general statements. Cf. Popper (1974, p. 1193).
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“Probability propositions express relative frequencies of repeated events, that is, frequencies counted as a percentage of the total. They are derived from frequencies observed in the past and include the assumption that the same frequencies will hold approximately for the future. They are constructed by means of an inductive inference,” Reichenbach (1968 [1951], p. 236). On Reichenbach’s approach to induction see Salmon (1991).
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He has also related his approach to prediction with decision-making. See Rescher (1995).
- 8.
See Gonzalez (2013a, pp. 17–18). When Salmon criticizes Popper , he only thinks of basic sciences and the ordinary uses of prediction (curiosity and decision-making in daily life).
- 9.
Rescher (1998, p. 161) makes a distinction similar to Salmon’s. It consists of distinguishing between “predictive import ” and “predictive inference ”. Thus, on the one hand, there are theories which make predictive inferences ; that is, they are theories which can provide statements about the future. And, on the other hand, there are theories which deal with the past and, consequently, they do not make predictions; but they can have predictive import , so they can provide the content required to make predictive inferences (for example, the theory of evolution ). The similitudes between them have been noticed by Wenceslao J. Gonzalez (2010, p. 266).
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As an example of the “narrow” viewpoint, Rescher (1980, p. 2, n.2) mentions J. Stuart Mill’s approach to induction, of Aristotelian inspiration, that sees induction as “the operation of discovering and proving general propositions.”
- 12.
In this regard, besides the Peicean influence, Rescher quotes William Whewhell with approval. For Whewhell, deduction “descends steadily and methodically, step by step: Induction mounts by a leap which is out of the reach of method [or, at any rate, mechanical routine]. She bounds to the top of the stairs at once…,” Whewell (1858, p. 114). Text quoted in Rescher (2014, pp. 55–56).
- 13.
“Deductive inference can never support contingent judgments such as meteorological forecasts, nor can deduction alone explain the breakdown of one’s car, discover the genotype of a new virus, or reconstruct fourteenth century trade routes,” Vickers (2014, sec. 1).
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“In valid deduction we are in the fortunate position of having premises that provide conclusive grounds for our conclusions: we have situations of fully supportive pro-information. Induction effectively inverts this proceeding, resolving the questions we face correlatively with the minimum of contraindications. We seek to minimize the as-yet-visible risks in the inevitably risky venture of cognitive gap filling,” Rescher (2014, p. 53).
- 16.
On his own approach to induction, Rescher writes that “it sees induction not as a characteristic mode of drawing conclusions, but as an estimation technique, a methodology for obtaining answers to our factual questions through optimal exploitation of the information at our disposal” (1980, p. 20).
- 17.
Rescher, Personal communication , 19.8.2014.
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Rescher, Personal communication , 19.8.2014.
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Rescher, Personal communication , 19.8.2014.
- 20.
In this regard, it is advisable to distinguish between “Logic ,” as the study of the inferential principles and rules with a well-defined rigor, and “logic ,” that can consist of processes of reasoning which seek an estimation oriented towards the truth. When Rescher thinks of “inductive logic ,” he has usually in mind the second sense of “logic ” (as truth estimation), so he assumes that inductive logic does not have the rigor that deductive logical rules have.
The advisability of distinguishing Logic —as a rigorous formal science —from logic —understood as an approach that seeks general patterns without proving in a formal way that what is obtained is true—has been pointed out by W. J. Gonzalez in order to study the work of philosophers such as Karl Popper , who sometimes uses the first sense (when he appeals to formal Logic as the basis of methodological approaches of general character), whereas on other occasions he uses the second sense, which is wider (for example, logic is used in some approaches regarding the social sciences ). These differences between the two possible senses of this term can be seen in Gonzalez (2004b).
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“Induction is, in the final analysis, a venture in practical/purposive rather than in strictly theoretical/illuminative reasoning,” Rescher (2014, p. 63).
- 22.
When Rescher analyses scientific prediction, he usually considers the realm of basic science, where inductive prediction can be a test for scientific theories . But the role of generic inductive prediction can be also addressed in the context of applied science (as the previous step to prescription ) and in the case of the application of science (for example, in business, where it is usual to make prediction on the basis of the trends observed in the past.)
- 23.
Javier Echeverría (1995) has suggested enlarging the traditional distinction between “context of discovery ” and “context of justification .” In his approach four contexts of scientific activity can be distinguished: context of education, context of innovation , context of evaluation, and context of application. He addresses this with regard to the axiology of research. So he insists on the axiological features of each of these contexts.
In this volume, the relation between scientific prediction and induction is addressed from a logical-methodological perspective. So the main interest is here in how induction can be a process to obtain scientific predictions (the “context of discovery ”) and how it is possible to validate predictive processes and results through induction (the “context of justification ”).
- 24.
On this distinction between “predictive procedures ” and “predictive methods ,” see Gonzalez (2015a, ch. 10, pp. 251–284).
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According to Hume , “there can be no demonstrative arguments to prove, that those instances, of which we have had no experience, resemble those, of which we have had experience” (2007, book 1, part 3, sec. VI, p. 62).
- 27.
Rescher’s criticism appeared for the first time in a paper published in 1958. One year later, he again defended the logical asymmetry between explanation and prediction . He did this in a paper published with O. Helmer . See Rescher and Helmer (1959).
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The paper is in the realm of the logical empiricism that was dominant in the philosophy of science of the United States in that time.
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This idea was proposed in Scheffler (1957).
- 31.
Rescher and Helmer acknowledge that there are exceptions to this common pattern: “Of course prediction may, as in astronomy, be as firmly based in fact and as tightly articulated in reasoning as any explanation . But this is not a general requirement to which predictions must conform. A doctor’s prognosis, for example, does not have astronomical certitude, yet practical considerations render it immensely useful as a guide in our conduct because it is far superior to reliance on guesswork or on pure chance alone as a decision making device,” (1959, p. 32).
- 32.
“Informative content” or “informativeness ” is understood here as the level of detail achieved by the prediction; that is, its precision.
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The “harmony thesis ” is already outlined in his book on scientific explanation : “The key thing in scientific understanding is the capacity to exploit a knowledge of laws to structure our understanding of the past and to guide our expectations for the future,” Rescher (1970, p. 135).
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In this regard, his criticism to the predictivist thesis of Milton Friedman can be highlighted. See Rescher (1998, pp. 109 and 194–196).
- 36.
The first part of this proposal should be qualified, because there are examples of scientific theories that are really influential and that are not oriented towards prediction. Thus, Charles Darwin did not orient his theory of evolution towards the elaboration of predictions, but his theory was not sterile regarding the phenomena at stake. Certainly, the Darwinian evolutionary approach might generate predictions of new species, but there is no evidence that this was the aim of the author of The Origin of Species.
- 37.
Even when Rescher’s proposal certainly makes sense, it could be qualified. It is possible to think of explicative theories of historical character that do not aim to make predictive contributions, at least in a direct way. There can also be considered predictive theories with correct predictions that do not yet have a well-developed explicative theory.
- 38.
For example, an astrologer may predict successfully, but he does not offer genuine scientific knowledge.
- 39.
Semantic reasons are not explicit in Rescher’s criticism to the symmetry thesis. But it is implicit that there are differences between explanation and prediction from the point of view of language to the extent that he characterizes scientific prediction as a statement . It seems clear that the referent of a statement about the future can be different from what exists now or what existed in the past (that is the realm of explanation ). The semantic differences have logical repercussions with regard to the problem of the symmetry.
However, this view of prediction as a statement is not clear in the whole set of Rescher’s publications on this issue. Thus, in a paper of 1963, he characterizes prediction as an argument: “A potential prediction of the supposed fact that a system will exhibit the characteristic Q at time t is an argument whose conclusion is the statement that the system exhibits Q at t,” Rescher (1963, p. 329).
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“This part of the symmetry thesis is usually thought to be [the] more dubious of the two. To begin with, it might be said, a prediction is simply a statement that something will occur (or perhaps that something has occurred that has not been verified),” Achinstein (2000, p. 168).
- 42.
However, for Achinstein , to acknowledge that prediction is a statement does not imply an objection to this part of the symmetry thesis, because “Hempel is concerned not just with predictive statements (ones that say something will occur), but with predictive arguments or inferences, that is, with cases in which some prediction is made from, or on the basis of, something,” Achinstein (2000, pp. 168–169).
He considers that a fairer objection is provided by the following example: “Suppose a drug company tests a drug on one thousand patients with symptoms S and discovers that in eight hundred cases the symptoms are relieved, while no one in a control group not taking the drug had relief. This might provide a very sound scientific basis for the prediction that the drug will be effective approximately 80 percent of the time. Yet the explanation for the drug’s general effectiveness is not that it was effective in the test cases” (2000, p. 169).
- 43.
The temporal precedence of the cause with regard to the effect is something clear in Salmon’s approach: “Time and causality go hand in hand. The anisotropy of time is deeply connected to the anisotropy of causality. Causes come before their effects, not after them. Now, if one agrees that causality is an indispensable component of scientific explanations of particular events, it is natural to suppose that the anisotropy of time and causality would be reflected in an anisotropy of scientific explanation ,” Salmon (1993, pp. 242–243).
- 44.
The notion of “postictability” appears for the first time in his (1944, p. 13).
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Guillán, A. (2017). Logical Features of Scientific Prediction. In: Pragmatic Idealism and Scientific Prediction. European Studies in Philosophy of Science. Springer, Cham. https://doi.org/10.1007/978-3-319-63043-4_3
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