Making Science Pay (Critical Rationalist Papers Book 3)

A Brief History of Decision Making
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Just as US politics gets trapped by the assumption that all major political questions were dealt with in , Pinker has no real need of any philosopher after Immanuel Kant. Despite his contempt for populists, theocrats and de-growth environmentalists, he ultimately dismisses them as having already lost. In which case, why the manifesto? Perhaps the answer lies in the occasional hints of existential angst.

Pinker does identify three scientific theories that have arisen since the 18th century, and which form an indispensable part of the scientific imagination: evolution, entropy and information. Common to all is a sense of the tragic, that life lacks purpose, and will ultimately fall apart. The most stirring passages are those that reflect on what this means, on how unlikely progress is, rather than on its all-conquering logic. This as Nietzsche noted makes science harder, not easier. The heroic ethos of science, of progress, is to carry on regardless, even in the knowledge that entropy will eventually win.

Facebook Twitter Pinterest. Topics Society books Book of the day. Steven Pinker reviews. Reuse this content. The aim of the philosopher of science was not to understand the methods per se , but to use them to reconstruct theories, their meanings, and their relation to the world. When scientists perform these operations, however, they will not report that they are doing them to give meaning to terms in a formal axiomatic system. This disconnect between methodology and the details of actual scientific practice would seem to violate the empiricism the Logical Positivists, or Bridgman, were committed to.

The view that methodology should correspond to practice to some extent has been called historicism, or intuitionism. We turn to these criticisms and responses in section 3. Positivism also had to contend with the recognition that a purely inductivist approach, along the lines of Bacon-Newton-Mill, was untenable. There was no pure observation, for starters. All observation was theory laden. Theory is required to make any observation, therefore not all theory can be derived from observation alone.

See also the entry on theory and observation in science. Even granting an observational basis, Hume had already pointed out that one could not argue for inductive conclusions without begging the question by presuming the success of the inductive method. Likewise, positivist attempts at analyzing how a generalization can be confirmed by observations of its instances were subject to a number of criticisms.

In his riddle of induction, Goodman pointed out that for a set of observations, there will be multiple hypotheses that are equally supported. Goodman suggested that one could distinguish between generalizations that were supported by their instances and those that were not by comparing the entrenchment of their predicates—that is, the degree to which they have formed part of generalizations that have successfully been projected to account for new instances.

Many find this paradoxical, but Hempel maintained that our intuition is based on a tacit appeal to background knowledge on the prevalence of ravens and non-ravens that prompt us to give more weight to evidence of ravens being black than to evidence of non-black items being non-ravens. We shall return to more recent attempts at explaining how observations can serve to confirm a scientific theory in section 4 below.

The standard starting point for a non-inductive analysis of the logic of confirmation is known as the Hypothetico-Deductive H-D method. In its simplest form, the idea is that a theory, or more specifically a sentence of that theory which expresses some hypothesis, is confirmed by its true consequences.

As noted in section 2 , this method had been advanced by Whewell in the 19 th century, as well as Nicod and others in the 20 th century. Some hypotheses conflicted with observable facts and could be rejected as false immediately. Others needed to be tested experimentally by deducing which observable events should follow if the hypothesis were true what Hempel called the test implications of the hypothesis , then conducting an experiment and observing whether or not the test implications occurred. If the experiment showed the test implication to be false, the hypothesis could be rejected.

On the other hand, if the experiment showed the test implications to be true, this did not prove the hypothesis true. The degree of this support then depends on the quantity, variety and precision of the supporting evidence. Falsification is deductive and similar to H-D in that it involves scientists deducing observational consequences from the hypothesis under test.

For Popper, however, the important point was not whatever confirmation successful prediction offered to the hypotheses but rather the logical asymmetry between such confirmations, which require an inductive inference, versus falsification, which can be based on a deductive inference. This simple opposition was later questioned, by Lakatos, among others. See the entry on historicist theories of scientific rationality.

Popper stressed that, regardless of the amount of confirming evidence, we can never be certain that a hypothesis is true without committing the fallacy of affirming the consequent. Instead, Popper introduced the notion of corroboration as a measure for how well a theory or hypothesis has survived previous testing—but without implying that this is also a measure for the probability that it is true.

Popper was also motivated by his doubts about the scientific status of theories like the Marxist theory of history or psycho-analysis, and so wanted to draw a line of demarcation between science and pseudo-science. Popper saw this as an importantly different distinction than demarcating science from metaphysics. The latter demarcation was the primary concern of many logical empiricists.

Popper used the idea of falsification to draw a line instead between pseudo and proper science. Science was science because it subjected its theories to rigorous tests which offered a high probability of failing and thus refuting the theory. The aim was not, in this way, to verify a theory. This could be done all too easily, even in cases where observations were at first inconsistent with the deduced consequences of the theory, for example by introducing auxiliary hypotheses designed explicitly to save the theory, so-called ad hoc modifications. This was what he saw done in pseudo-science where the theories appeared to be able to explain anything that happened within the field to which they applied.

In contrast, science is risky; if observations showed the predictions from a theory to be absent, the theory would be refuted. Hence, scientific hypotheses must be falsifiable. The more potential falsifiers of a hypothesis, the more falsifiable it would be, and the more the hypothesis claimed. Conversely, hypotheses without falsifiers claimed very little or nothing at all. Originally, Popper thought that this meant the introduction of ad hoc hypotheses only to save a theory should not be countenanced as good scientific method. These would undermine the falsifiabililty of a theory. However, Popper later came to recognize that the introduction of modifications immunizations, he called them was often an important part of scientific development.

Responding to surprising or apparently falsifying observations often generated important new scientific insights. Popper sought to reconcile the view by blurring the distinction between falsifiable and not falsifiable, and speaking instead of degrees of testability Popper 41f.

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From the s on, sustained meta-methodological criticism emerged that drove the philosophical focus away from scientific method. Something brief about those criticisms must be said here, but recommendations for further reading can be found at the end of the entry. History, if viewed as a repository for more than anecdote or chronology, could produce a decisive transformation in the image of science by which we are now possessed. See the entry on the Vienna Circle. Kuhn shares with other of his contemporaries, such as Feyerabend and Lakatos, a commitment to a more empirical approach to philosophy of science.

Namely, the history of science provides important data, and necessary checks, for philosophy of science, including any theory of scientific method. An examination of the history of science reveals, according to Kuhn, that scientific development occurs in alternating phases. During normal science, the members of the scientific community adhere to the paradigm in place. Their commitment to the paradigm means a commitment to the puzzles to be solved and the acceptable ways of solving them. Confidence in the paradigm remains so long as steady progress is made in solving the shared puzzles.

An important part of a disciplinary matrix is the set of values which provide the norms and aims for scientific method. The main values that Kuhn identifies are prediction, problem solving, simplicity, consistency, and plausibility. An important by-product of normal science, however, is the accumulation of puzzles which cannot be solved utilizing the resources of the current paradigm. Once the accumulation of these anomalies has reached some critical mass, it can trigger a communal shift to a new paradigm and a new phase of normal science.

Importantly, the values that provide the norms and aims for scientific method may have transformed in the meantime. Method may therefore be relative to discipline, time or place. Feyerabend also identified the aims of science as progress, but argued that any methodological prescription would only stifle that progress Feyerabend Heroes of science, like Galileo, are shown to be just as reliant on rhetoric and persuasion as they are on reason and demonstration.

Others, like Aristotle, are shown to be far more reasonable and far-reaching in their outlooks then they are given credit for. More generally, even the methodological restriction that science is the best way to pursue knowledge, and to increase knowledge, is too restrictive. Feyerabend suggested instead that science might, in fact, be a threat to a free society, because it and its myth had become so dominant Feyerabend An even more fundamental kind of criticism was offered by several sociologists of science from the s onwards who dismissed what they saw as a false distinction between philosophical accounts of the rational development of science and sociological accounts of the irrational mistakes.

because all (Western) philosophy consists of a series of footnotes to Plato

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Instead, they adhered to a symmetry thesis on which any causal explanation of how scientific knowledge is established needs to be symmetrical in explaining truth and falsity, rationality and irrationality, success and mistakes by the same causal factors see, e. Movements in the Sociology of Science, like the Strong Programme, or in the social dimensions and causes of knowledge more generally led to extended and close examination of detailed case studies in contemporary science and its history.

See the entries on the social dimensions of scientific knowledge and social epistemology. As they saw it, in other words, explanatory appeals to scientific method were not empirically well grounded. By the close of the 20 th century the search by philosophers for the scientific method was flagging.

Despite the many difficulties that philosophers encountered in trying to providing a clear methodology of conformation or refutation , still important progress has been made on understanding how observation can provide evidence for a given theory. Work in statistics has been crucial for understanding how theories can be tested empirically, and in recent decades a huge literature has developed that attempts to recast confirmation in Bayesian terms.

Here these developments can be covered only briefly, and we refer to the entry on confirmation for further details and references. Statistics has come to play an increasingly important role in the methodology of the experimental sciences from the 19 th century onwards. At that time, statistics and probability theory took on a methodological role as an analysis of inductive inference, and attempts to ground the rationality of induction in the axioms of probability theory have continued throughout the 20 th century and in to the present.

Developments in the theory of statistics itself, meanwhile, have had a direct and immense influence on the experimental method, including methods for measuring the uncertainty of observations such as the Method of Least Squares developed by Legendre and Gauss in the early 19 th century, criteria for the rejection of outliers proposed by Peirce by the mid th century, and the significance tests developed by Gosset a.

These developments within statistics then in turn led to a reflective discussion among both statisticians and philosophers of science on how to perceive the process of hypothesis testing: whether it was a rigorous statistical inference that could provide a numerical expression of the degree of confidence in the tested hypothesis, or if it should be seen as a decision between different courses of actions that also involved a value component. This led to a major controversy among Fisher on the one side and Neyman and Pearson on the other see especially Fisher , Neyman and Pearson , and for analyses of the controversy, e.

Introducing the distinction between the error of rejecting a true hypothesis type I error and accepting a false hypothesis type II error , they argued that it depends on the consequences of the error to decide whether it is more important to avoid rejecting a true hypothesis or accepting a false one. Hence, Fisher aimed for a theory of inductive inference that enabled a numerical expression of confidence in a hypothesis. To him, the important point was the search for truth, not utility. In contrast, the Neyman-Pearson approach provided a strategy of inductive behaviour for deciding between different courses of action.

Here, the important point was not whether a hypothesis was true, but whether one should act as if it was. Similar discussions are found in the philosophical literature. On the one side, Churchman and Rudner argued that because scientific hypotheses can never be completely verified, a complete analysis of the methods of scientific inference includes ethical judgments in which the scientists must decide whether the evidence is sufficiently strong or that the probability is sufficiently high to warrant the acceptance of the hypothesis, which again will depend on the importance of making a mistake in accepting or rejecting the hypothesis.

Others, such as Jeffrey and Levi disagreed and instead defended a value-neutral view of science on which scientists should bracket their attitudes, preferences, temperament, and values when assessing the correctness of their inferences. For more details on this value-free ideal in the philosophy of science and its historical development, see Douglas and Howard Hence, for Bayesians probabilities refer to a state of knowledge, whereas for frequentists probabilities refer to frequencies of events see, e. Bayesianism aims at providing a quantifiable, algorithmic representation of belief revision, where belief revision is a function of prior beliefs i.

The probability that a particular hypothesis is true is interpreted as a degree of belief, or credence, of the scientist. There will also be a probability and a degree of belief that a hypothesis will be true conditional on a piece of evidence an observation, say being true. Bayesianism proscribes that it is rational for the scientist to update their belief in the hypothesis to that conditional probability should it turn out that the evidence is, in fact, observed.

Originating in the work of Neyman and Person, frequentism aims at providing the tools for reducing long-run error rates, such as the error-statistical approach developed by Mayo that focuses on how experimenters can avoid both type I and type II errors by building up a repertoire of procedures that detect errors if and only if they are present.

Both Bayesianism and frequentism have developed over time, they are interpreted in different ways by its various proponents, and their relations to previous criticism to attempts at defining scientific method are seen differently by proponents and critics. The literature, surveys, reviews and criticism in this area are vast and the reader is referred to the entries on Bayesian epistemology and confirmation.

Attention to scientific practice, as we have seen, is not itself new. However, the turn to practice in the philosophy of science of late can be seen as a correction to the pessimism with respect to method in philosophy of science in later parts of the 20 th century, and as an attempted reconciliation between sociological and rationalist explanations of scientific knowledge. Much of this work sees method as detailed and context specific problem-solving procedures, and methodological analyses to be at the same time descriptive, critical and advisory see Nickles for an exposition of this view.

The following section contains a survey of some of the practice focuses. In this section we turn fully to topics rather than chronology. A problem with the distinction between the contexts of discovery and justification that figured so prominently in philosophy of science in the first half of the 20 th century see section 2 is that no such distinction can be clearly seen in scientific activity see Arabatzis Thus, in recent decades, it has been recognized that study of conceptual innovation and change should not be confined to psychology and sociology of science, but are also important aspects of scientific practice which philosophy of science should address see also the entry on scientific discovery.

Looking for the practices that drive conceptual innovation has led philosophers to examine both the reasoning practices of scientists and the wide realm of experimental practices that are not directed narrowly at testing hypotheses, that is, exploratory experimentation. Examining the reasoning practices of historical and contemporary scientists, Nersessian has argued that new scientific concepts are constructed as solutions to specific problems by systematic reasoning, and that of analogy, visual representation and thought-experimentation are among the important reasoning practices employed.

These ubiquitous forms of reasoning are reliable—but also fallible—methods of conceptual development and change. On her account, model-based reasoning consists of cycles of construction, simulation, evaluation and adaption of models that serve as interim interpretations of the target problem to be solved. Often, this process will lead to modifications or extensions, and a new cycle of simulation and evaluation. However, Nersessian also emphasizes that. Nersessian Thus, while on the one hand she agrees with many previous philosophers that there is no logic of discovery, discoveries can derive from reasoned processes, such that a large and integral part of scientific practice is.

Drawing largely on cases from the biological sciences, much of their focus has been on reasoning strategies for the generation, evaluation, and revision of mechanistic explanations of complex systems. Addressing another aspect of the context distinction, namely the traditional view that the primary role of experiments is to test theoretical hypotheses according to the H-D model, other philosophers of science have argued for additional roles that experiments can play. The notion of exploratory experimentation was introduced to describe experiments driven by the desire to obtain empirical regularities and to develop concepts and classifications in which these regularities can be described Steinle , ; Burian ; Waters However the difference between theory driven experimentation and exploratory experimentation should not be seen as a sharp distinction.

Theory driven experiments are not always directed at testing hypothesis, but may also be directed at various kinds of fact-gathering, such as determining numerical parameters. Vice versa , exploratory experiments are usually informed by theory in various ways and are therefore not theory-free. Instead, in exploratory experiments phenomena are investigated without first limiting the possible outcomes of the experiment on the basis of extant theory about the phenomena.

The field of omics just described is possible because of the ability of computers to process, in a reasonable amount of time, the huge quantities of data required. Computers allow for more elaborate experimentation higher speed, better filtering, more variables, sophisticated coordination and control , but also, through modelling and simulations, might constitute a form of experimentation themselves. Here, too, we can pose a version of the general question of method versus practice: does the practice of using computers fundamentally change scientific method, or merely provide a more efficient means of implementing standard methods?

This has epistemological implications, regarding what we can know, and how we can know it. To have confidence in the results, computer methods are therefore subjected to tests of verification and validation. The distinction between verification and validation is easiest to characterize in the case of computer simulations. In a typical computer simulation scenario computers are used to numerically integrate differential equations for which no analytic solution is available. The equations are part of the model the scientist uses to represent a phenomenon or system under investigation.


Verifying a computer simulation means checking that the equations of the model are being correctly approximated. Validating a simulation means checking that the equations of the model are adequate for the inferences one wants to make on the basis of that model. A number of issues related to computer simulations have been raised.

The identification of validity and verification as the testing methods has been criticized. Oreskes et al. The distinction itself is probably too clean, since actual practice in the testing of simulations mixes and moves back and forth between the two Weissart ; Parker a; Winsberg Computer simulations do seem to have a non-inductive character, given that the principles by which they operate are built in by the programmers, and any results of the simulation follow from those in-built principles in such a way that those results could, in principle, be deduced from the program code and its inputs.

The status of simulations as experiments has therefore been examined Kaufmann and Smarr ; Humphreys ; Hughes ; Norton and Suppe Mayo ; Parker b. At the same time, many of these calculations are approximations to the calculations which would be performed first-hand in an ideal situation. Both factors introduce uncertainties into the inferences drawn from what is observed in the simulation.

For many of the reasons described above, computer simulations do not seem to belong clearly to either the experimental or theoretical domain. Rather, they seem to crucially involve aspects of both. It should also be noted that the debates around these issues have tended to focus on the form of computer simulation typical in the physical sciences, where models are based on dynamical equations.

Other forms of simulation might not have the same problems, or have problems of their own see the entry on computer simulations in science. Despite philosophical disagreements, the idea of the scientific method still figures prominently in contemporary discourse on many different topics, both within science and in society at large. Discourse on scientific method also typically arises when there is a need to distinguish between science and other activities, or for justifying the special status conveyed to science.

One of the settings in which the legend of a single, universal scientific method has been particularly strong is science education see, e. Dewey The fact that the standards of scientific success shift with time does not only make the philosophy of science difficult; it also raises problems for the public understanding of science. We do not have a fixed scientific method to rally around and defend. Reference to the scientific method has also often been used to argue for the scientific nature or special status of a particular activity. Philosophical positions that argue for a simple and unique scientific method as a criterion of demarcation, such as Popperian falsification, have often attracted practitioners who felt that they had a need to defend their domain of practice.

For example, references to conjectures and refutation as the scientific method are abundant in much of the literature on complementary and alternative medicine CAM —alongside the competing position that CAM, as an alternative to conventional biomedicine, needs to develop its own methodology different from that of science. Also within mainstream science, reference to the scientific method is used in arguments regarding the internal hierarchy of disciplines and domains.

A frequently seen argument is that research based on the H-D method is superior to research based on induction from observations because in deductive inferences the conclusion follows necessarily from the premises. See, e.

In some areas of science, scholarly publications are structured in a way that may convey the impression of a neat and linear process of inquiry from stating a question, devising the methods by which to answer it, collecting the data, to drawing a conclusion from the analysis of data. However, scientific publications do not in general reflect the process by which the reported scientific results were produced. It is still far too early to say whether, and in what way, his philosophy will be remembered.

Preston reading. Feyerabend's Early Life 2. Feyerabend's Early Work: Liberalizing Empiricism 4. Son of a civil servant and a seamstress. After basic training, volunteered for Officers' School. Advanced to Lieutenant. Lectured to Officers' School. The bullet damaged his spinal nerves. Soon transferred to physics. First article, on the concept of illustration in modern physics, published. Became secretary of the seminars. Met Karl Popper and Walter Hollitscher. Married first wife, Edeltrud. Ludwig Wittgenstein visited the Kraft Circle to give a talk. Feyerabend also met Bertolt Brecht.

Applied for a British Council scholarship to study under Wittgenstein at Cambridge. But Wittgenstein died before Feyerabend arrived in England, so Feyerabend chose Popper as his supervisor instead. Concentrated on the quantum theory and Wittgenstein. Studied the typescript of Wittgenstein's Philosophical Investigations , and prepared a summary of the book.

Befriended another of Popper's students, Joseph Agassi. Popper applied for an extension to his scholarship, but Feyerabend decided to remain in Vienna instead. Declined the offer to become Popper's research assistant. Agassi took the post. Feyerabend became research assistant to Arthur Pap in Vienna. Pap introduced Feyerabend to Herbert Feigl. His summary of Wittgenstein's Philosophical Investigations appeared as a review of the book in The Philosophical Review. Feyerabend got to know the quantum physicist David Bohm, whose ideas were to influence him substantially.

In them, Feyerabend argued against positivism and in favour of a scientific realist account of the relation between theory and experience, largely on grounds familiar from Karl Popper's falsificationist views. Gave two lectures to Oberlin College, Ohio, in which he embroidered on Popper's views about the pre-Socratic thinkers. Although beginning to put some distance between himself and Popper, Feyerabend was still able to write a glowing review of Popper's Conjectures and Refutations. Popper not amused. Feyerabend claimed to be applying the liberalism of John Stuart Mill's On Liberty to scientific methodology.

Published little during the next few years. Feyerabend, lecturing at the University of Sussex, was ill too. Published a scathing review of Popper's Objective Knowledge. Great scientists are methodological opportunists who use any moves that come to hand, even if they thereby violate canons of empiricist methodology. Got depressed. Published his first major article on relativism: the first time he explicitly endorsed the view. Some clarification of epistemological anarchism, and very little retreat from the position set out in AM.

Explored further the political implications of epistemological anarchism. The book also included one of Feyerabend's major endorsements of relativism, one of the views for which he was becoming known. First volume of the German edition of Feyerabend's philosophical papers appears. Feyerabend published increasingly in German from this point onwards. Also continues his campaign to rehabilitate Ernst Mach. Left for Italy and Switzerland in the fall, at least partly because of the effects of the October earthquake in California.

Also lots of small publications, many of them in Common Knowledge.

Scientific Method

Signs of an increasing unhappiness with relativism in Feyerabend's publications around this time. Feyerabend developed an inoperable brain tumour, and was hospitalized. Several major memorial symposia and colloquia on his work took place over the next two years.

He describes his scientific interests as follows: I was interested in both the technical and the more general aspects of physics and astronomy, but I drew no distinction between them. For me, Eddington, Mach his Mechanics and Theory of Heat , and Hugo Dingler Foundations of Geometry were scientists who moved freely from one end of their subject to the other. I read Mach very carefully and made many notes. At this point in his life, he later recalled: The course of my life was… clear: theoretical astronomy during the day, preferably in the domain of perturbation theory; then rehearsals, coaching, vocal exercises, opera in the evening…; and astronomical observation at night… The only remaining obstacle was the war.

But, as usual, Feyerabend had no clear view of the situation: Much of what happened I learned only after the war, from articles, books, and television, and the events I did notice either made no impression at all or affected me in a random way. I remember them and I can describe them, but there was no context to give them meaning and no aim to judge them by. Elsewhere Feyerabend tells us that he admired [Popper's] freedom of manners, his cheek, his disrespectful attitude towards the German philosophers who gave the proceedings weight in more senses than one, his sense of humour… [and] his ability to restate ponderous problems in simple and journalistic language.

Hollitscher never presented an argument that would lead, step by step, from positivism to realism and he would have regarded the attempt to produce such an argument as philosophical folly. He rather developed the realist position itself, illustrated it by examples from science and commonsense, showed how closely it was connected with scientific research and everyday action and so revealed its strength.

About Wittgenstein's lecture, Feyerabend recalls the following: Not even a brief and quite interesting visit by Wittgenstein himself in could advance our discussion. Wittgenstein was very impressive in his way of presenting concrete cases, such as amoebas under a microscope… but when he left we still did not know whether or not there was an external world, or, if there was one, what the arguments were in favour of it.

Note that Feyerabend must have got the date wrong, since Wittgenstein died in April She gave me manuscripts of Wittgenstein's later writings and discussed them with me. The discussions extended over months and occasionally proceeded from morning over lunch until late into the evening. They had a profound influence upon me though it is not at all easy to specify particulars.

This meeting seems to have been the first airing of the important concept of incommensurability although not the term itself, which crept into publications only a decade later : On one occasion which I remember vividly Anscombe, by a series of skilful questions, made me see how our conception and even our perceptions of well-defined and apparently self-contained facts may depend on circumstances not apparent in them. The conservation principles may change from one developmental stage of the human organism to another and they may be different for different languages cf.

Philosopher Karl Popper - A Portrait

I conjectured that such principles would play an important role in science, that they might change during revolutions and that deductive relations between pre-revolutionary and post-revolutionary theories might be broken off as a result. These thoughts received an unenthusiastic reception from Hart, von Wright and Popper.

He later commented: I knew that Wittgenstein did not want to present a theory of knowledge, or language , and I did not expressly formulate a theory myself. But my arrangements made the text speak like a theory and falsified Wittgenstein's intentions. Here is how Feyerabend recounts Feigl's influence: It was … quite a shock to hear Feigl expound fundamental difficulties and to hear him explain in perfectly simple language without any recourse to formalism why the problem of application [of the probability-calculus] was still without a solution.

Formalization, then, was not the last word in philosophical matters. There was still room for fundamental discussion-for speculation dreaded word! In the summer of that year, he again visited Alpbach, where he met the philosopher of science Philipp Frank another former Logical Positivist , who exerted on him a somewhat delayed influence: Frank argued that the Aristotelian objections against Copernicus agreed with empiricism, while Galileo's law of inertia did not. As in other cases, this remark lay dormant in my mind for years; then it started festering. The Galileo chapters of Against Method are a late result.

See also SFS , p. The arguments supporting my complaint were quite good… but it was suddenly clear to me that imposed without regard to circumstances they were a hindrance rather than a help: a person trying to solve a problem whether in science or elsewhere must be given complete freedom and cannot be restricted by any demands, norms, however plausible they may seem to the logician or the philosopher who has thought them out in the privacy of his study. Norms and demands must be checked by research, not by appeal to theories of rationality.

In a lengthy article I explained how Bohr had used this philosophy and how it differs from more abstract procedures. Of his post at Berkeley, he later said: My function was to carry out the educational policies of the State of California which means I had to teach people what a small group of white intellectuals had decided was knowledge.

Mexicans, Blacks, Indians entered the university as a result of new educational policies.

because all (Western) philosophy consists of a series of footnotes to Plato

What an opportunity for a prophet in search of a following! What an opportunity, my rationalist friends told me, to contribute to the spreading of reason and the improvement of mankind! I felt very differently. For it dawned on me that the intricate arguments and the wonderful stories I had so far told to my more or less sophisticated audience might just be dreams, reflections of the conceit of a small group who had succeeded in enslaving everyone else with their ideas.

Who was I to tell these people what and how to think? See also KT , p. He seems to have got into some trouble at Berkeley by running his seminar on unacceptably loose lines, regularly cancelling lectures, and failing to prepare for the lectures he did give: I often told the students to go home—the official notes would contain everything they needed. As a result an audience of , , even 1, shrank to 50 or I wasn't happy about that; I would have preferred a larger audience, and yet I repeated my advice until the administration intervened.

Why did I do it? Was it because I disliked the examination system, which blurred the line between thought and routine? Was it because I despised the idea that knowledge was a skill that had to be acquired and stabilized by rigorous training? Or was it because I didn't think much of my own performance? All these factors may have played a role.

A member of Feyerabend's audience recalls things in rather more detail: Sussex University: the start of the Autumn Term, There was not a seat to be had in the biggest Arts lecture theatre on campus. Taut with anticipation, we waited expectantly and impatiently for the advertized event to begin. He was not on time—as usual. In fact rumour had it that he would not be appearing at all that illness or was it just ennui?

But just as we began sadly to reconcile ourselves to the idea that there would be no performance that day at all, Paul Feyerabend burst through the door at the front of the packed hall. Rather pale, and supporting himself on a short metal crutch, he walked with a limp across to the blackboard. Removing his sweater he picked up the chalk and wrote down three questions one beneath the other: What's so great about knowledge? What's so great about science? What's so great about truth? We were not going to be disappointed after all!

A more accurate description, however, is the one given in his autobiography: AM is not a book, it is a collage. I loved to shock people… pp. Now that I am aware of it, I wonder how it happened. In the commotion surrounding AM , Feyerabend succumbed to depression: … now I was alone, sick with some unknown affliction; my private life was in a mess, and I was without a defense. I often wished I had never written that fucking book. The truth, he suggests, is that science is much closer to myth than a scientific philosophy is prepared to admit. It is one of the many forms of thought that have been developed by man, and not necessarily the best.

It is conspicuous, noisy, and impudent, but it is inherently superior only for those who have already decided in favour of a certain ideology, or who have accepted it without ever having examined its advantages and its limits AM , p. All it does now is to lend class to the general drive towards monotony. It is time to disengage Reason from this drive and, as it has been thoroughly compromised by the association, to bid it farewell.

Scientific Method (Stanford Encyclopedia of Philosophy)

FTR , p. Conclusion: Last Things Feyerabend's autobiography occupied him right up until his death on February 11th, , at the Genolier Clinic, overlooking Lake Geneva. Colodny ed. Against Method , London: Verso, Terpstra ed. Preston ed. Naturphilosophie , eds. Oberheim, Frankfurt am Main: Suhrkamp Verlag, The Tyranny of Science , E. Oberheim ed. Agassi eds. Secondary Sources Achinstein, P. Agassi, J. Alford, C. Andersson, G. Athanasopoulos, C. Boudouris ed. Baertschi, B. Bearn, G. Ben-Israel, I. Bernstein, R. Bhaskar, R. Brown, H. Brown, M.

Bschir, K. Burian, R. Cohen and M. Wartofsky eds. Reidel, pp. Butts, R. Casamonti, M. Chalmers, A. Yeo eds.

Critical Thinking

Churchland, P. Coffa, J. Collier, J. Kitcher eds. Collodel, M. Corvi, R. Feyerabend , Milan: Vita e Pensiero. Couvalis, S. Davidson, D. Reprinted in Krausz and Meiland Devitt, M. Dusek, V. Everitt, N. Farrell, R. Finocchiaro, M. Hacking eds. Floyd, J. Stadler eds. Fuller, S. Gattei, S. Gellner, E. Giedymin, J. Cohen, P. Giere, R. Goldman, M. Durbin ed. Nickles eds. Grebowicz, G. Gunaratne, R. Hacking, I. Hannay, A. Gruengard eds.

Hanson, N. Harding, S.

Paul Feyerabend

Feyerabend's Against Method , Mind , — Heit, H. Heller, L. Hentschel, K. Hesse, M. Hollis, M. Hooker, C. Horgan, J. Hoyningen-Huene, P. Hull, R. Hung, H-C. Jones, W. Kadvany, J. Kidd, I. Diller eds. Turchetti eds. Kleiner, S. Koertge, N. Kresge, S. Krige, J. Kuby, D. Kusch, M. Lakatos, I. Laudan, L. Mittelstrass eds. Laymon, R. Leplin, J. Lloyd, E. Machamer, P. Maia Neto, J. Margolis, J. Winokur eds.