1.1. Scientific Methodology
It is evident that science has existed since time immemorial. History bears record of great scientific accomplishments that humans have achieved in past three millenia. However, the modern generation has witnessed a greater rapidity of scientific progress than previous generations. Moreover, there has also been considerations about scientific research and methodology. This has also given rise to several problems in the epistemology of science.
1.1.1. The Problem of Induction. Francis Bacon (1561-1626), regarded as one of the pioneers of modern scientific thought, in his Novum Organum, laid down principles for an empirical method of science that emphasized induction through observation and experimentation.[1] According to Bacon, hypothesis follows empirical observation and determines the method of experiment which in turn verifies the hypothesis giving rise to ‘axioms’ that guide further research.[2] Bacon’s inductivism greatly influenced the development of empiricism. However, philosophers soon saw the problems therein.
1.1.1.1. In his An Enquiry Concerning Human Understanding (1748), David Hume (1711-1776) questioned the assumptions of induction. According to Hume, all induction is based on a presupposition of the notion of causality. Predictions are made on the assumption that all reality is connected and causally related. In all reasonings related to fact, ‘it is constantly supposed that there is a connection between the present fact and that which is inferred from it.’[3] Causal relations are either near or remote, direct or collateral. For instance, heat and light are collateral effects of fire, and the one effect may justly be inferred from the other. However, Hume goes on, the knowledge of causal relation is not a priori but ‘arises entirely from experience, when we find that any particular objects are constantly conjoined with each other.’ Thus, causal relations are not necessary relations but only arbitrary ones. One sees a succession of things and by custom and habit imposes causal relation between them. There is no reason to suppose that a particular effect will always of necessity follow a particular event, eventhough experience shows that as happening. Thus, there are no rational grounds for induction. Hume further questions the assumption of induction that all nature is uniform. But, one’s observation of a succession of events in the past may not guarantee the same if the belief in the uniformity of nature turns to be false. In fact, there is no a priori basis for assuming the uniformity of nature apart from some probable psychological inclination.[4] Can one be sure that induction itself will continue to be reliable in the future? According to Peter Lipton, ‘The nub of the problem is that the claim that induction will be reliable in future is itself a prediction, and so could only be justified inductively, which would beg the question.’[5] Thus, scientific prediction on the basis of induction has no absolute grounds.
Several attempts to solve Hume’s challenge have been made. However, the only possible answers seem to be those in which it has been attempted to demonstrate the scientific method as not being inductive but deductive. In other words, the problem of induction is solved by doing away with induction itself. Two chief answers suggested were by Immanuel Kant (1724-1804)and Karl Popper (1902-1994).
1.1.1.2. In his Critique of Pure Reason (1781), Kant attempted to ground the scientific method rationally in his theory of the categories of understanding. According to Kant, the mind is not a blank slate on which experience writes information. For if that is true then no geometrical or scientific knowledge would be guaranteed. According to him, the forms of intuition, viz., space and time and the categories of understanding, like quality, quantity, and relation, are the means by which the mind arranges the influx of random data to facilitate understanding. Thus, some knowledge is always innate. The fundamental principles of science, like the law of conservation and causality, which are assumed in any scientific research are not obtained from experience but constitute the a priori knowledge of human understanding.[6] Therefore, causal relations, according to Kant, are necessarily imposed by the human mind and constitute the rational basis of scientific research. Thus, causal relations are not induced but deduced from the fundamental principles of human understanding. Without such fundamental principles no scientific research could be possible.
1.1.1.3. Karl Popper’s deductive interpretation of the scientific method proposes the falsification principle according to which scientific theories are hypothesis from which can be deduced statements testable by observation. if the appropriate experimental observations falsify these statements, the hypothesis is refuted. If a hypothesis survives efforts to falsify it, it may be tentatively accepted.[7] Thus, a good theory, according to Popper, would make a number of predictions that could in principle be disproved or falsified by observation.[8] However, no scientific theory can be conclusively established for there always remains the probability of falsification. This probability, however, doesn’t undermine the value of a scientific theory, for it is no longer seen as derived from experience but logically deduced from a hypothesis.
1.1.1.4. Both Kant’s and Popper’s views seem only to advance the view that science has no method by which it can come to a certainty of scientific knowledge. Kant’s phenomenalistic interpretation of noetic-mechanics leads to the view that scientific research is more an idealistic one than a realistic one. Scientific investigation cannot go beyond the categories of the mind. Therefore, no matter what the external world is like, it will only be seen as the categories allow them to be seen and not as the things are in themselves. On the other hand, Popper’s view gives scientific research a pragmatic tinge. Nothing can be conclusive in science, since the probability of falsification always prevails. A science that assumes unfalsifiability is bad science. However, Popper’s theory cannot be ignored. History of science has shown that theories have to be regularly revisited to explain newer discoveries and problems. Science as an empirical study that seeks universal knowledge will always involve a high degree of probability for humans are not omniscient with relation to space and time.
1.2. Scientific Knowledge
By ‘scientific knowledge’ is meant the body of scientific theories, explanations, and laws. The problem of scientific knowledge is related to the nature of scientific knowledge and its relation to truth and reality.
1.2.1. Scientific Explanation. By ‘scientific explanation’ is meant a statement that explains phenomena in scientific terms, i.e., on the basis of scientific theories and assumptions. There have been mainly three approaches to scientific explanation: the inferential view, the causal view, and the pragmatic view.
1.2.1.1. The Inferential View. According to this view, an explanation is a type of argument, in which statements expressing laws of nature occurring form the premises, and the phenomenon to be explained forms the conclusion. The premises may also be statements that describe antecedent conditions.[9]
According to the deductive-nomological model of inference, advanced by Hempel and Openheim (1948), a scientific explanation is a deduction of a description of the phenomenon to be explained from a set of premises that includes at least one law of nature.[10] The content of the explanation must be empirical, meaning that it must be logically possible for an observation-statement to contradict it.[11]
There are at least two problems related to the inferential view: the problem of asymmetry and the problem of irrelevance. The problem of asymmetry is that, contrary to the postulation of the inferential view, scientific explanation and prediction are not symmetric. For example, using the laws governing weather patterns, storm formation, and the effect of air pressure on the behavior of barometers, one can predict that when a barometer falls a storm will soon follow. Similarly, one can also predict that when a storm is approaching, the barometer will fall. However, neither of these are explanatory, since both are explained by antecedent atmospheric conditions.[12] The problem of irrelevance is that this model permits irrelevant information to play the role of explanation. For example, from the premises ‘All men who take birth control pills do not get pregnant,’ and ‘John takes birth control pills,’ one can infer that ‘John will not get pregnant.’ However, the argument doesn’t constitute an explanation since John will not get pregnant whether he takes the pills or not. Though the former premise doesn’t appear to be a law, yet in science regular observation of phenomena lead to generalization of law; therefore, the use of such a premise to represent a law is not unjustified.
1.2.1.2. The Causal View. According to this view, an explanation is a body of information about the causes of a particular event,[13] which also involves the events causal history. However, the causal view faces the problem of sufficient causal explanation. For instance, in events where any of the available laws may be applicable, as in the expansion of a gas container to which Boyle’s or Charles’ or the Pressure law is applicable, any of the laws could be explanatory though not necessarily constituting a causal explanation. Further, in cases where certain laws are explained by other laws, for instance in Newton’s explanation of Kepler’s laws of ellipses by deriving them from his own laws of motion and gravitation, the inference model seems to better suited than the causal one.[14]
1.2.1.3. The Pragmatic View. According to this view, an explanation is a body of information that implies that the phenomenon is more likely than its alternatives, where the information is of the sort deemed ‘relevant’ in that context, and the class of alternatives to the phenomenon are also fixed by the context.[15] Accordingly, an explanation is an answer that provides relevant information that favors the event to be explained over its alternatives, as determined by the context, based on interests of those involved.[16] Subjective interests define the contextual requirements of explanation. Thus, explanation is something relative to the subjective interest; the explanation is ‘explanatory’ to someone. The explanation tells why a particular event is more likely than its alternatives. However, since the why-question is relative to the subject who asks it, the answer is only ‘explanatory’ relative to that subject. The subjective context of the why-question consists of the presuppositions of the subject, the criterion of relevance assumed by the subject, and the alternatives known to the subject. The scientific explanation only tells why one alternative is more likely to happen over the other alternatives. This assumes the contextual relativity and subjectivity of scientific explanations. Scientific explanations, thus, serve pragmatic cognitive interests of the subject.
1.2.2. Theory-Reality Connection. One problem of the epistemology of science is to ascertain in what way scientific theories are related to the objective world itself. Two main theories in this connection are realism and instrumentalism.
1.2.2.1. Realism. Scientific realism is the view that scientific theories reveal the hidden structure of the world.[17] Consequently, the acceptance of a scientific theory involves the belief that it is true.[18] Scientific realists do not claim that all current science is correct; however, they hold that scientific theories have approximate and substantial truthfulness and believe that future progress in science will lead to theories much closer to the truth. In other words, science is able to give a true and real picture of what reality is like in itself. Contrary to this assumption, Kant had argued that what reality is in itself cannot be known since all sense-impressions are acted upon by the forms and categories of the mind; consequently, space, time, causality, quantity, etc., are all mental impositions on reality. Therefore, nothing of reality can be known since one cannot go beyond one’s mind. However, to scientific realism such agnosticism and skepticism regarding knowledge is unacceptable. It sees in science an optimistic hope for progress of genuine knowledge regarding the world.
1.2.2.2. Instrumentalism. According to scientific instrumentalism, scientific theories are not descriptions of the invisible world but instruments for predictions about the observable world.[19] The relation of a scientific theory to objective reality is with reference to utility. What concerns a scientific theory is not to tell what reality is like, but to be able to make predictions about the observable world. Some instrumentalists believe that scientific theories are similar to the circuits in an electronic calculator; they help make predictions but tell nothing about the world. On the other hand, a modern school of instrumentalism, known as constructive empiricism, holds that scientific theories do purport to tell something about the world; however, the only goal such theories serve are to make predictions. Scientists are not required to believe those theories to be true reflections of reality as it is. What ultimately matters is utility.
Thus, it is evident that the epistemic problem of scientific knowledge is related to the wider problem of knowledge itself. Its solution depends on questions like: Can reality be known? Is knowledge rational or empirical? Is truth relative or absolute? To realists the predictive success of scientific theories demonstrate the genuineness of the theories; however, to instrumentalists the predictive successes only prove that the theories have been useful, and nothing else.
[1] “Francis Bacon, 1st Baron Verulam and Viscount St Albans,” Microsoft Encarta Encyclopedia (Microsoft Corporation, 2001)
[2] Will Durant, The Story of Philosophy, 2nd edn. (New York: Pocket Books, 1961), p. 133
[3] David Hume, “There Are No Possible Grounds For Induction,” Classic Philosophical Questions, 7th edn. (ed. James A. Gould; New York: Macmillan Publishing Company, 1992), p. 316
[4] Shyam Kishore Seth & Neelima Mishra, Gyan Darshan (Allahabad: Lokbharti Prakashan, 2000), p. 222
[5] “Philosophy of Science,” Microsoft Encarta Encyclopedia (Microsoft Corporation, 2001); also see Hume, “There Are No Possible Grounds For Induction,” p. 322
[6] Immanuel Kant, “The Copernican Revolution in Knowledge,” Introduction to Philosophy (ed. Louis Pojman; Belmont: Wadsworth Publishing Company, 1991), p. 145
[7] “Sir Karl Raimund Popper,” Microsoft Encarta Encyclopedia (Microsoft Corporation, 2001)
[8] Stephen Hawking, A Brief History of Time (London: Bantam Books, 1988), p. 11
[9] Lyle Zynda, Introduction to the Philosophy of Science: Lecture Notes (Princeton University, Spring 1994; http://socserver.soc.iastate.edu/sapp/phil_sci_lecture02.html)
[10] “Philosophy of Science,” Microsoft Encarta Encyclopedia (Microsoft Corporation, 2001)
[11] Lyle Zynda, Introduction to the Philosophy of Science, Lecture 2.
[12] Ibid.
[13] Lyle Zynda, Introduction to the Philosophy of Science, Lecture 4.
[14] Lyle Zynda, Introduction to the Philosophy of Science, Lecture 6.
[15] Lyle Zynda, Introduction to the Philosophy of Science, Lecture 2.
[16] Lyle Zynda, Introduction to the Philosophy of Science, Lecture 6.
[17] “Philosophy of Science,” Microsoft Encarta Encyclopedia (Microsoft Corporation, 2001)
[18] Lyle Zynda, Introduction to the Philosophy of Science, Lecture 17.
[19] “Philosophy of Science,” Microsoft Encarta Encyclopedia (Microsoft Corporation, 2001)
© Domenic Marbaniang, Philosophy of Science, 2006
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