Philosophy of science

The philosophy of science is the branch of philosophy which studies the philosophical foundations, assumptions, and implications of science, including the natural sciences such as physics and biology, and the social sciences, such as psychology and economics. In this respect, the philosophy of science is closely related to epistemology and ontology. It seeks to explain such things as: the nature of scientific statements and concepts; the way in which they are produced; how science explains, predicts and, through technology, harnesses nature; the means for determining the validity of information; the formulation and use of the scientific method; the types of reasoning used to arrive at conclusions; and the implications of scientific methods and models for the larger society, and for the sciences themselves.

This article, as any, is not exhaustive, yet covers arguably the most common ground in the Philosophy of Science.

Contents

1 Nature of scientific statements and concepts

1.1 Empiricism
1.2 Scientific realism and instrumentalism
1.3 Social constructivism
1.4 Analysis and reductionism

2 The justification of scientific statements

2.1 Induction
2.2 Falsifiability
2.3 Coherentism
2.4 Occam's Razor

3 Social accountability

3.1 Scientific infallibility
3.2 Critiques of science

4 Sociology and Anthropology of Science

7 Philosophy of science topics

8 References

9 External links

Nature of scientific statements and concepts

Science draws conclusions about the way the world is and the way in which scientific theory relates to the world. Science draws upon evidence from experimentation, logical deduction, and rational thought in order to examine the world and the individuals that exist within society. In making observations of the nature of individuals and their surroundings, science seeks to explain the concepts that are entwined with everyday lives.

Empiricism

A central concept in the philosophy of science is empiricism, or dependence on evidence. Empiricism is the view that knowledge derives from experience of the world. In this sense, scientific statements are subject to and derived from our experiences or observations. Scientific hypotheses are developed and tested through empirical methods consisting of observations and experiments. Once reproduced widely enough, the information resulting from our observations and experiments counts as the evidence upon which the scientific community develops theories that purport to explain facts about the world.

Observations involve perception, and so are themselves cognitive acts. That is, observations are themselves embedded in our understanding of the way in which the world works; as this understanding changes, the observations themselves may apparently change.

Scientists attempt to use induction, deduction and quasi-empirical methods, and invoke key conceptual metaphors to work observations into a coherent, self-consistent structure.

Scientific realism and instrumentalism

Scientific realism, or naïve empiricism, is the view that the universe really is as explained by scientific statements. Realists hold that things like electrons and magnetic fields actually exist. It is naïve in the sense of taking scientific models at face value, and is the view that most scientists adopt.

In contrast to realism, instrumentalism holds that our perceptions, scientific ideas and theories do not necessarily reflect the real world accurately, but are useful instruments to explain, predict and control our experiences. To an instrumentalist, electrons and magnetic fields are convenient ideas that may or may not actually exist. For instrumentalists, the empirical method is used to do no more than show that theories are consistent with observations. Instrumentalism is largely based on John Dewey's philosophy and, more generally, pragmatism, which was influenced by philosophers such as William James and Charles Sanders Peirce.

Social constructivism

One area of interest among historians, philosophers, and sociologists of science is the extent to which scientific theories are shaped by their social and political context. This approach is usually known as social constructivism. Social constructivism is in one sense an extension of instrumentalism that incorporates the social aspects of science. In its strongest form, it sees science as merely a discourse between scientists, with objective fact playing a small role if any. A weaker form of the constructivist position might hold that social factors play a large role in the acceptance of new scientific theories.

On the stronger account, the existence of Mars the planet is irrelevant, since all we really have are the observations, theories and myths, which are all themselves constructed by social interaction. On this account, scientific statements are about each other, and an empirical test is no more than checking the consistency between different sets of socially constructed theories. This account rejects realism. It becomes difficult, then, to explain how science differs from any other discipline; equally, however, it becomes difficult to give an account of the extraordinary success of science in producing usable technology.

On the weaker account, Mars the planet might be said to have a real existence, separate and distinct from our observations, theories and myths about it. Although theories and observations are socially constructed, part of the construction process involves ensuring a correspondence of some sort with this reality. On this account, scientific statements are about the real world. The crucial issue for this account is explaining this correspondence. What justification is there for claiming that photos from the latest probe are in some sense more real than the Roman myths about Mars? It is important, therefore, for Social Constructivists to consider how scientific statements are justified.

Analysis and reductionism

Analysis is the activity of breaking an observation or theory down into simpler concepts in order to understand it. Analysis is as essential to science as it is to all rational enterprises. It would be impossible, for instance, to describe mathematically the motion of a projectile without separating out the force of gravity, angle of projection and initial velocity. Only after this analysis is it possible to formulate a suitable theory of motion.

Reductionism in science can have several different senses. One type of reductionism is the belief that all fields of study are ultimately amenable to scientific explanation. Perhaps an historical event might be explained in sociological and psychological terms, which in turn might be described in terms of human physiology, which in turn might be described in terms of chemistry and physics. The historical event will have been reduced to a physical event. This might be seen as implying that the historical event was 'nothing but' the physical event, denying the existence of emergent phenomena.

Daniel Dennett invented the term greedy reductionism to describe the assumption that such reductionism was possible. He claims that it is just 'bad science', seeking to find explanations which are appealing or eloquent, rather than those that are of use in predicting natural phenomena. He also says that:

There is no such thing as philosophy-free science; there is only science whose philosophical baggage is taken on board without examination. —Daniel Dennett, Darwin's Dangerous Idea, 1995.

Arguments made against greedy reductionism through reference to emergent phenomena rely upon the fact that self-referential systems can be said to contain more information than can be described through individual analysis of their component parts. Examples include systems that contain strange loops, fractal organisation and strange attractors in phase space. Analysis of such systems is necessarily information-destructive because the observer must select a sample of the system that can be at best partially representative. Information theory can be used to calculate the magnitude of information loss and is one of the techniques applied by Chaos theory.

The justification of scientific statements

The most powerful statements in science are those with the widest applicability. Newton's Third Law — "for every action there is an opposite and equal reaction" — is a powerful statement because it applies to every action, anywhere, and at any time.

But it is not possible for scientists to have tested every incidence of an action, and found a reaction. How is it, then, that they can assert that the Third Law is in some sense true? They have, of course, tested many, many actions, and in each one have been able to find the corresponding reaction. But can we be sure that the next time we test the Third Law, it will be found to hold true?

Induction

One solution to this problem is to rely on the notion of induction. Inductive reasoning maintains that if a situation holds in all observed cases, then the situation holds in all cases. So, after completing a series of experiments that support the Third Law, one is justified in maintaining that the Law holds in all cases.

Explaining why induction commonly works has been somewhat problematic. One cannot use deduction, the usual process of moving logically from premise to conclusion, because there is simply no syllogism that will allow such a move. No matter how many times 17th Century biologists observed white swans, and in how many different locations, there is no deductive path that can lead them to the conclusion that all swans are white. This is just as well, since, as it turned out, that conclusion would have been wrong. Similarly, it is at least possible that an observation will be done tomorrow that shows an occasion in which an action is not accompanied by a reaction; the same is true of any scientific law.

One answer has been to conceive of a different form of rational argument, one that does not rely on deduction. Deduction allows one to formulate a specific truth from a general truth: all crows are black; this is a crow; therefore this is black. Induction somehow allows one to formulate a general truth from some series of specific observations: this is a crow and it is black; that is a crow and it is black; therefore all crows are black.

The problem of induction is one of considerable debate and importance in the philosophy of science: is induction indeed justified, and if so, how?

Falsifiability

Another way to use logic to justify scientific statements, first formally discussed by Karl Popper, is falsifiability. This principle states that in order to be useful (or even scientific at all), a scientific statement ('fact', theory, 'law', principle, etc) must be falsifiable, i.e. able to be proven wrong. Without this property, it would be difficult (if not impossible) to test a scientific statement against the evidence. Falsification's aim is to re-introduce deductive reasoning into the debate. It is not possible to deduce a general statement from a series of specific ones, but it is possible for one specific statement to prove that a general statement is false. Finding a black swan might be sufficient to show that the general statement 'all swans are white' is false.

Falsifiability neatly avoids the problem of induction, because it does not make use of inductive reasoning. However, it introduces its own difficulties. When an apparent falsification occurs, it is always possible to introduce an addition to a theory that will render it unfalsified. So, for instance, ornithologists might have simply argued that the large black bird found in Australia was not a member of the genus Cygnus, but of some other, or perhaps some new, genus.

The problem with falsificationism is that scientific theories are simply never falsifiable. That is, it is always possible to add ad hoc hypotheses to a theory to save it from falsification. A value judgment is therefore involved in the rejection of any theory.

Coherentism

Induction and Falsification both attempt to justify scientific statements by reference to other specific scientific statements. Both must avoid the problem of the criterion, in which any justification must in turn be justified, resulting in an infinite regress. The regress argument has been used to justify one way out of the infinite regress, foundationalism. Foundationalism claims that there are some basic statements that do not require justification. Both induction and falsification are forms of foundationalism in that they rely on basic statements that derive directly from observations.

The way in which basic statements are derived from observation complicates the problem. Observation is a cognitive act; that is, it relies on our existing understanding, our set of beliefs. An observation of a transit of Venus requires a huge range of auxiliary beliefs, such as those that describe the optics of telescopes, the mechanics of the telescope mount, and an understanding of celestial mechanics. At first sight, the observation does not appear to be 'basic'.

Coherentism offers an alternative by claiming that statements can be justified by their being a part of a coherent system. In the case of science, the system is usually taken to be the complete set of beliefs of an individual or of the community of scientists. W. V. Quine argued for a Coherentist approach to science. An observation of a transit of Venus is justified by its being coherent with our beliefs about optics, telescope mounts and celestial mechanics. Where this observation is at odds with one of these auxiliary beliefs, an adjustment in the system will be required to remove the contradiction.

Occam's Razor

Occam's Razor is a useful rule for science. William of Occam (Ockham, or several other spellings) suggested that the simplest account which 'explains' the phenomenon is to be preferred. Occam's razor is often phrased as "entities should not be multiplied beyond necessity."

This is generally used when choosing between two theories which fit the data equally well. Consider the ubiquitous situation of two theories A and B, where A is the most basic version of the theory that fits the data, and B is a version of A augmented with additional elements which neither improve nor harm the fit. The principle of Occam's Razor advises us to "shave" away the additional elements of B leaving us with the more basic version A.

Because, generally for every theory there are an infinite number of variations which are equally consistent with the current data, but which predict very different outcomes in some circumstances, Occam's razor is used implicitly in every instance of scientific research. As an example, consider Newton's famous theory that "for every action there is an equal and opposite reaction." An alternative theory would be that "for every action there is an equal and opposite reaction, except on the 12 of January 2055 when the reaction will be of half intensity." This seemingly absurd addition violates the Occam's Razor principle because it is a gratuitous addition, along with an infinite number of other alternative theories. Indeed without a rule like Occam's Razor there would never be any philosophical or practical justification for scientists to advance any theory over its infinite competitors, and science would have no predictive power at all.

Although Occam's Razor is a widely used extra-evidentary theory selection rule, in itself it expresses nothing more than an aesthetic preference for simplicity. There are related mathematical approaches from Bayesian analysis and information theory that balance explanatory power with simplicity. One such is minimum message length inference.

Occam's Razor is often abused and cited where it is inapplicable. It does not say that the simplest account is to be preferred regardless of its capacity to explain outliers, exceptions, or other phenomena in question. The principle of falsifiability requires that any exception that can be reliably reproduced should invalidate the simplest theory, and that the next-simplest account which can actually incorporate the exception as part of the theory should then be preferred to the first. As Albert Einstein puts it, "The supreme goal of all theory is to make the irreducible basic elements as simple and as few as possible without having to surrender the adequate representation of a single datum of experience."

Social accountability

Scientific infallibility

A critical question in science is, to what degree the current body of scientific knowledge can be taken as an indicator of what is actually 'true' about the physical world in which we live. The acceptance of knowledge as if it were absolutely 'true' and unquestionable (in the sense of theology or ideology) is called scientism.

However, it is common for members of the public to have the opposite view of science — many lay people believe that scientists are making claims of infallibility. Science serves in the process of consensus decision making by which people of varying moral and ethical views come to agree on 'what is real'. In secular and technological societies, without any stronger conception of reality based on other shared ethical or moral or religious grounds, science has come to serve as the primary arbiter in disputes. This leads to the abuse of scientific dialogue for political or commercial ends.

Concerned about the wide disparity between how scientists work, and how their work is perceived has led to public campaigns to educate lay people about scientific skepticism and the scientific method.

Critiques of science

Paul Feyerabend argued that no description of scientific method could possibly be broad enough to encompass all the approaches and methods used by scientists. Feyerabend objected to prescriptive scientific method on the grounds that any such method would stifle and cramp scientific progress. Feyerabend claimed, "the only principle that does not inhibit progress is: anything goes."

Sociology and Anthropology of Science

A major development in recent decades has been the study of the formation, structure, and evolution of scientific communities by sociologists and anthropologists including Michel Callon, Elihu Gerson, Bruno Latour, John Law, Susan Leigh Star, Anslem Strauss, Lucy Suchman, etc. Some of their work has been previously loosely gathered in actor network theory. Here the approach to the philosophy of science is to study how scientific communities actually operate.

Researchers in Information Science have also made contributions, e.g., Scientific Community Metaphor.

Major contributors to the philosophy of science