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Philosophy of science

Branch of philosophy

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Through Philosophy, Methodology and Science

Many of the central problems concerned with the philosophy of science lack contemporary consensus, including whether science can infer truth about unobservable entities and whether inductive reasoning can be justified as yielding definite scientific knowledge. Philosophers of science also consider philosophical problems within particular sciences (such as biology, physics and social sciences such as economics and psychology). Some philosophers of science also use contemporary results in science to reach conclusions about philosophy itself.

While philosophical thought pertaining to science dates back at least to the time of Aristotle, the general philosophy of science emerged as a distinct discipline only in the 20th century following the logical positivist movement, which aimed to formulate criteria for ensuring all philosophical statements' meaningfulness and objectively assessing them. Karl Popper criticized logical positivism and helped establish a modern set of standards for scientific methodology. Thomas Kuhn's 1962 book The Structure of Scientific Revolutions was also formative, challenging the view of scientific progress as the steady, cumulative acquisition of knowledge based on a fixed method of systematic experimentation and instead arguing that any progress is relative to a "paradigm", the set of questions, concepts, and practices that define a scientific discipline in a particular historical period.

Subsequently, the coherentist approach to science, in which a theory is validated if it makes sense of observations as part of a coherent whole, became prominent due to W. V. Quine and others. Some thinkers such as Stephen Jay Gould seek to ground science in axiomatic assumptions, such as the uniformity of nature. A vocal minority of philosophers, and Paul Feyerabend in particular, argue against the existence of the "scientific method", so all approaches to science should be allowed, including explicitly supernatural ones. Another approach to thinking about science involves studying how knowledge is created from a sociological perspective, an approach represented by scholars like David Bloor and Barry Barnes. Finally, a tradition in continental philosophy approaches science from the perspective of a rigorous analysis of human experience.

Philosophies of the particular sciences range from questions about the nature of time raised by Einstein's general relativity, to the implications of economics for public policy. A central theme is whether the terms of one scientific theory can be intra- or intertheoretically reduced to the terms of another. Can chemistry be reduced to physics, or can sociology be reduced to individual psychology? The general questions of philosophy of science also arise with greater specificity in some particular sciences. For instance, the question of the validity of scientific reasoning is seen in a different guise in the foundations of statistics. The question of what counts as science and what should be excluded arises as a life-or-death matter in the philosophy of medicine. Additionally, the philosophies of biology, psychology, and the social sciences explore whether the scientific studies of human nature can achieve objectivity or are inevitably shaped by values and by social relations.

Introduction

Defining science

Distinguishing between science and non-science is referred to as the demarcation problem. For example, should psychoanalysis, creation science, and historical materialism be considered pseudosciences? Karl Popper called this the central question in the philosophy of science. However, no unified account of the problem has won acceptance among philosophers, and some regard the problem as unsolvable or uninteresting. Martin Gardner has argued for the use of a Potter Stewart standard ("I know it when I see it") for recognizing pseudoscience.

Early attempts by the logical positivists grounded science in observation while non-science was non-observational and hence meaningless. Popper argued that the central property of science is falsifiability. That is, every genuinely scientific claim is capable of being proven false, at least in principle.

An area of study or speculation that masquerades as science in an attempt to claim a legitimacy that it would not otherwise be able to achieve is referred to as pseudoscience, fringe science, or junk science. Physicist Richard Feynman coined the term "cargo cult science" for cases in which researchers believe they are doing science because their activities have the outward appearance of it but actually lack the "kind of utter honesty" that allows their results to be rigorously evaluated.

Scientific explanation

A closely related question is what counts as a good scientific explanation. In addition to providing predictions about future events, society often takes scientific theories to provide explanations for events that occur regularly or have already occurred. Philosophers have investigated the criteria by which a scientific theory can be said to have successfully explained a phenomenon, as well as what it means to say a scientific theory has explanatory power.

One early and influential account of scientific explanation is the deductive-nomological model. It says that a successful scientific explanation must deduce the occurrence of the phenomena in question from a scientific law. This view has been subjected to substantial criticism, resulting in several widely acknowledged counterexamples to the theory. It is especially challenging to characterize what is meant by an explanation when the thing to be explained cannot be deduced from any law because it is a matter of chance, or otherwise cannot be perfectly predicted from what is known. Wesley Salmon developed a model in which a good scientific explanation must be statistically relevant to the outcome to be explained. Others have argued that the key to a good explanation is unifying disparate phenomena or providing a causal mechanism.

Justifying science

Although it is often taken for granted, it is not at all clear how one can infer the validity of a general statement from a number of specific instances or infer the truth of a theory from a series of successful tests.

One approach is to acknowledge that induction cannot achieve certainty, but observing more instances of a general statement can at least make the general statement more probable. So the chicken would be right to conclude from all those mornings that it is likely the farmer will come with food again the next morning, even if it cannot be certain. However, there remain difficult questions about the process of interpreting any given evidence into a probability that the general statement is true. One way out of these particular difficulties is to declare that all beliefs about scientific theories are subjective, or personal, and correct reasoning is merely about how evidence should change one's subjective beliefs over time.

Some argue that what scientists do is not inductive reasoning at all but rather abductive reasoning, or inference to the best explanation. In this account, science is not about generalizing specific instances but rather about hypothesizing explanations for what is observed. As discussed in the previous section, it is not always clear what is meant by the "best explanation". Occam's razor, which counsels choosing the simplest available explanation, thus plays an important role in some versions of this approach. To return to the example of the chicken, would it be simpler to suppose that the farmer cares about it and will continue taking care of it indefinitely or that the farmer is fattening it up for slaughter? Philosophers have tried to make this heuristic principle more precise regarding theoretical parsimony or other measures. Yet, although various measures of simplicity have been brought forward as potential candidates, it is generally accepted that there is no such thing as a theory-independent measure of simplicity. In other words, there appear to be as many different measures of simplicity as there are theories themselves, and the task of choosing between measures of simplicity appears to be every bit as problematic as the job of choosing between theories.

Nicholas Maxwell has argued for some decades that unity rather than simplicity is the key non-empirical factor in influencing the choice of theory in science, persistent preference for unified theories in effect committing science to the acceptance of a metaphysical thesis concerning unity in nature. In order to improve this problematic thesis, it needs to be represented in the form of a hierarchy of theses, each thesis becoming more insubstantial as one goes up the hierarchy.

Observation inseparable from theory

When making observations, scientists look through telescopes, study images on electronic screens, record meter readings, and so on. Generally, on a basic level, they can agree on what they see, e.g., the thermometer shows 37.9 degrees C. But, if these scientists have different ideas about the theories that have been developed to explain these basic observations, they may disagree about what they are observing. For example, before Albert Einstein's general theory of relativity, observers would have likely interpreted an image of the Einstein cross as five different objects in space. In light of that theory, however, astronomers will tell you that there are actually only two objects, one in the center and four different images of a second object around the sides. Alternatively, if other scientists suspect that something is wrong with the telescope and only one object is actually being observed, they are operating under yet another theory. Observations that cannot be separated from theoretical interpretation are said to be theory-laden.

All observation involves both perception and cognition. That is, one does not make an observation passively, but rather is actively engaged in distinguishing the phenomenon being observed from surrounding sensory data. Therefore, observations are affected by one's underlying understanding of the way in which the world functions, and that understanding may influence what is perceived, noticed, or deemed worthy of consideration. In this sense, it can be argued that all observation is theory-laden.

The purpose of science

Should science aim to determine ultimate truth, or are there questions that science cannot answer? Scientific realists claim that science aims at truth and that one ought to regard scientific theories as true, approximately true, or likely true. Conversely, scientific anti-realists argue that science does not aim (or at least does not succeed) at truth, especially truth about unobservables like electrons or other universes. Instrumentalists argue that scientific theories should only be evaluated on whether they are useful. In their view, whether theories are true or not is beside the point, because the purpose of science is to make predictions and enable effective technology.

Realists often point to the success of recent scientific theories as evidence for the truth (or near truth) of current theories. Antirealists point to either the many false theories in the history of science, epistemic morals, the success of false modeling assumptions, or widely termed postmodern criticisms of objectivity as evidence against scientific realism. Antirealists attempt to explain the success of scientific theories without reference to truth. Some antirealists claim that scientific theories aim at being accurate only about observable objects and argue that their success is primarily judged by that criterion.

Real patterns

The notion of real patterns has been suggested, notably by philosopher Daniel C. Dennett, as an intermediate position between strong realism and eliminative materialism. This concept delves into the investigation of patterns observed in scientific phenomena to ascertain whether they signify underlying truths or are mere constructs of human interpretation. Dennett provides a unique ontological account concerning real patterns, examining the extent to which these recognized patterns have predictive utility and allow for efficient compression of information.

The discourse on real patterns extends beyond philosophical circles, finding relevance in various scientific domains. For example, in biology, inquiries into real patterns seek to elucidate the nature of biological explanations, exploring how recognized patterns contribute to a comprehensive understanding of biological phenomena. Similarly, in chemistry, debates around the reality of chemical bonds as real patterns continue.

Evaluation of real patterns also holds significance in broader scientific inquiries. Researchers, like Tyler Millhouse, propose criteria for evaluating the realness of a pattern, particularly in the context of universal patterns and the human propensity to perceive patterns, even where there might be none. This evaluation is pivotal in advancing research in diverse fields, from climate change to machine learning, where recognition and validation of real patterns in scientific models play a crucial role.

Values and science

Values intersect with science in different ways. There are epistemic values that mainly guide the scientific research. The scientific enterprise is embedded in particular culture and values through individual practitioners. Values emerge from science, both as product and process and can be distributed among several cultures in the society. When it comes to the justification of science in the sense of general public participation by single practitioners, science plays the role of a mediator between evaluating the standards and policies of society and its participating individuals, wherefore science indeed falls victim to vandalism and sabotage adapting the means to the end.

If it is unclear what counts as science, how the process of confirming theories works, and what the purpose of science is, there is considerable scope for values and other social influences to shape science. Indeed, values can play a role ranging from determining which research gets funded to influencing which theories achieve scientific consensus. For example, in the 19th century, cultural values held by scientists about race shaped research on evolution, and values concerning social class influenced debates on phrenology (considered scientific at the time).

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