Deductive and Inductive Logic

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1 Inductive Logic Deductive and Inductive Logic What is Reasoning? Example: The first theorem Euclid s Elements provides a good example of the kind of reasoning that people admire. Suppose we construct a triangle in the following way: 1. Draw a circle centered at point A. Mark a point B on the circumference and draw a line from A to B. Draw a second circle centered at B that passed through A. Mark one of the points at which the circles intersect as B and draw lines from C to A and from C to B. Theorem: All the sides of the triangle ABC are of equal length. Proof: Let AB denote the length of the line segments AB, and so on. Step 1: AB = AC because they are radii of the circle centered at A. Step 2: BA = BC because they are radii of the circle centered at B. Step 3: AB = BA because AB and BA denote the same line. Step 4: AC = BC because they are each equal to the same thing (viz. AB ). Step 5: Therefore, AB = AC = BC by steps 1 and 4. Definition: An argument is a list of statements, one of which is the conclusion and the rest of which are the premises. The conclusion states the point being argued for and the premises state the reasons being advanced in support the conclusion. They may not be good reasons. There are good and bad arguments. Tip: To identify arguments look for words that introduce conclusions, like "therefore", "consequently", "it follows that". These are called conclusion indicators. Also look for premise indicators like "because" and "since". Remark: Each of the five steps in the proof to Euclid s first theorem is an argument. The conclusions in steps 1 to 4 are called intermediate conclusions, while the conclusion in step 5 is the main conclusion. (1 of 6) [ :07:55]

2 Inductive Logic Question: All arguments, or sequences of arguments, are examples of reasoning, but is every piece of reasoning an argument? A perceptual judgment such as "I see a blue square", or the conclusions of scientific experts reading in X-rays, or looking through a microscope, may be examples of reasoning that are not arguments. They are derived from what Kuhn called tacit knowledge, acquired through training and experience (e.g., knowing how to ride a bicycle). It is not easily articulated, and is not stated in any language. The Difference between Good and Bad Arguments In logic, we assume that any reasoning is represented as an argument, and the evaluation of an argument involves two questions: 1. Are the premises true? 2. Supposing that the premises are true, what sort of support do they give the conclusion? Answers to question 2: Compare the following arguments. 1. All planets move on ellipses. Pluto is a planet. Therefore, Pluto moves on an ellipse. 2. Mercury moves on an ellipse. Venus moves on an ellipse. Earth moves on an ellipse. Mars moves on an ellipse. Jupiter moves on an ellipse. Saturn moves on an ellipse. Uranus moves on an ellipse. Neptune moves on an ellipse. Therefore, Pluto moves on an ellipse. Definition: An argument is deductively valid if and only if it is impossible that its conclusion is false while its premises are true. Examples: Argument 1 is deductively valid, while argument 2 is not. Remark on terminology: The notion of deductively validity is such a central and important concept in philosophy, that is goes by several names. When an argument is deductively valid, we say that the conclusion follows from the premises, or the conclusion is deduced from, or inferred from, or proved from the premises. Or we may say that the premises imply, or entail, or prove the conclusion. We also talk of deductively valid arguments as being demonstrative. All these different terms mean exactly the same thing, so the situation is far simpler than it appears. What s possible? The sense of "impossible" needs clarification. Consider the example: 3. George is a human being. George is 100 years old. George has arthritis. Therefore, George will not run a four-minute mile tomorrow. (2 of 6) [ :07:55]

3 Inductive Logic Suppose that the premises are true. In logic, it is possible that George will run a four-minute mile tomorrow. It is not physically possible. But logicians have a far more liberal sense of what is "possible" in mind in their definition of deductive validity. Argument 3 is not deductively valid on their definition. So, argument 3 is invalid. Key idea: In any deductively valid argument, there is a sense in which the conclusion is contained in premises. Deductive reasoning serves the purpose of extracting information from the premises. In a non-deductive argument, the conclusion goes beyond the premises. Inferences in which the conclusion amplifies the premises is sometimes called ampliative inference. Therefore, whether an argument is deductively valid or not, depends on what the premises are. Missing premises?: We can always add a premise to turn an invalid argument into a valid argument. For example, if we add the premise "No 100-year-old human being with arthritis will run a four-minute mile tomorrow" to argument 3, then the new argument is deductively valid. (The original argument, of course, is still invalid). Definition: An argument is inductively strong if and only if it is improbable that its conclusion is false while its premises are true. Remember: This definition is the same as the definition of "deductively valid" except that "impossible" is replaced by "improbable." The degree of strength of an inductive argument may be measured by the probability of that the conclusion is true given that all the premises are true. The probability of the conclusion of a deductively valid argument given the premises is one, so deductively valid arguments may be thought of as the limiting case of a strong inductive arguments. Ampliative arguments have an inductive strength less than one. The probability of the conclusion given the premises can change from person to person, as it depends on the stock of relevant knowledge possessed by a given person at a given time. Summary: In response to question 2, we may give answers like "the argument is valid", "the arguments is inductively strong" or "the argument is inductively weak." Exercise: Discuss the following examples (all statements are understood to refer to the year 1998): 4. There are multi-celled organisms living on Mars. Therefore, there is intelligent life on (3 of 6) [ :07:55]

4 Inductive Logic Mars. 5. There are multi-celled organisms living on Mars. Therefore, there are single-celled organisms living on Mars. 6. There are multi-celled organisms living in Lake Mendota. Therefore, there is intelligent life living in Lake Mendota. 7. There are multi-celled organisms living in Lake Mendota. Therefore, there are singlecelled organisms living in Lake Mendota. Nevertheless, in logic, it is assumed that the answer to question 1 is relevant to the evaluation of an argument. But it is a question that needs to be asked in addition to question 2. So, if the premises of an inductively strong argument are false, then logicians are forced to say that the argument is not a good one. It is confusing to say that an inductively strong argument is a weak argument, but this is how the terms are defined. Tip: Defined terms must be used as defined. You can t use the term differently just because you don t agree with the definition. Different Kinds of Ampliative Argument Definition: Any argument that is not deductively valid, or deductively invalid, is called an ampliative argument. The term refers to the fact that the conclusion of such argument goes beyond, or amplifies upon, the premises. Remark on terminology: Again the notion of invalid is so common and central, that it goes by many names. Other terms commonly used are inductive and non-demonstrative. I prefer ampliative because it reminds us that the conclusion goes beyond the premises, and it does not have the bad reputation that sometimes goes along with the word induction. Here are a variety of examples of ampliative arguments: Simple enumerative induction goes from a list of observations of the form "this A is a B" to the conclusion "All A s are B s". The example Hume made famous is like this: 8. Billiard ball 1 moves when struck. Billiard ball 2 moves when struck. Billiard ball 3 moves when struck Billiard ball 100 moves when struck. Therefore, all billiard balls move when struck. Some ampliative arguments go from general statements to general statements: (4 of 6) [ :07:55]

5 Inductive Logic 9. All bodies freely falling near the surface of the Earth obey Galileo s law. All planets obey Kepler s laws. Therefore, all material objects obey Newton s laws. Others go from general statements to specific statements: 10. All emeralds previously found have been green. Therefore, the next emerald to be found will be green. Conclusion: To understand empirical science we need to understand ampliative inference. Two Kinds of Science? A Priori and Empirical? 1. A priori science, like Euclid s geometry, is where the conclusions are deduced from premises that appear to be self-evidently true. 2. In empirical science, like physics, conclusions are based on observational data. This is similar to the distinction between pure mathematics and applied mathematics. The distinction is not always sharp. Ever since Einstein rejected the use of Euclidean geometry in his new physics at the turn of the 20 th century, it seems that a priori sciences cannot tell us anything about the real world. The focus of recent philosophy of science is on the empirical sciences. A priori sciences contain the strongest form of reasoning, at the expense of telling us less about the real world. Introduction to the Demarcation Problem Definition: In philosophy of science, we refer to what we already know directly through observation as the empirical evidence (we are open-minded about the possibility that some of these facts are mistaken). See Exercise 1. All of empirical science uses ampliative arguments. Hume made the same point in a different way. He pointed that in example 8, it is possible that the premises are true and the conclusion is false. No matter how many instances of a generalization we observe, it does not prove that the generalization is true. What is the difference between science and pseudoscience? You often hear that science is based on the facts while pseudoscience is not. Or you say that religious belief is based on faith, whereas scientific belief is not. Unfortunately, both scientific and non-scientific reasoning go beyond the facts. So, can we tell them apart? (5 of 6) [ :07:55]

6 Inductive Logic Argument: 1. The demarcation between science and pseudoscience depends only the nature of the reasoning used. 2. Genuine science involves ampliative inference. 3. Pseudoscience involves ampliative inference. 4. Therefore, there is no demarcation between science and pseudoscience. The problem of demarcation is to say what is wrong with this argument. (Question: what are the two things that can be wrong with an argument?) Review of Central Definitions and Remarks on Terminology Definition: An argument is deductively valid if and only if it is impossible that its conclusion is false while its premises are true. Remark: The notion of deductively validity is such a central and important concept in philosophy, that is goes by several names. When an argument is deductively valid, we say that the conclusion follows from the premises, or the conclusion is deduced from, or inferred from, or proved from the premises. Or we may say that the premises imply, or entail, or prove the conclusion. We also talk of deductively valid arguments as being demonstrative. All these different terms mean exactly the same thing, so the situation is far simpler than it appears. Definition: Any argument that is not deductively valid, or deductively invalid, is an ampliative argument. The term refers to the fact that the conclusion of such argument goes beyond, or amplifies upon, the premises. Remark: Again the notion of invalid is so common and central, that it goes by many names. Other terms commonly used are inductive and non-demonstrative. I prefer ampliative because it reminds us that the conclusion goes beyond the premises, and it does not have the bad reputation that sometimes goes along with the word induction. (6 of 6) [ :07:55]

7 Demarcation Demarcation: Popper, Kuhn and Lakatos Last modified on Friday, September 18, Malcolm R. Forster, 1998 The Problem The difference between science and non-science has practical ramifications for society: Parapsychology includes the study of such alleged phenomena as telepathy, clairvoyance, and precognition. In 1969 the American Association for the Advancement of Science (AAAS) admitted the Parapsychology association as an Affiliate member. Should they have done that? In Arkansas, U. S. A., there were attempts to have the biblical story of creation taught in schools alongside evolutionary theory (after earlier attempts to ban evolutionary theory failed). They argued that creationism is a just as much a science, and therefore deserves equal time. The Merriam-Webster's Collegiate Dictionary defines creation science n (1979): creationism; also: scientific evidence or arguments put forth in support of creationism. Should an authoritative dictionary presuppose that creationism is a science? Freudian psychology has a poor reputation in scientific circles. Is it a pseudoscience? Immanuel Velikovsky and Erich van Daniken wrote best sellers Worlds in Collision and Chariots of the Gods, which angered many scientists. Are these examples of pseudoscience. Thor Heyerdahl launched the Kon-Tiki expedition to support his theory that the polynesians migrated from South America. Was he a pseudoscientist? Gould wrote a book called The Mismeasure of Man about the IQ debate, and phrenology, which purported to predict the criminal nature of people from their skull shape and other characteristics. IQ testing has been used to screen children from entering high school, or college, in many countries for many years. Does it predict future academic performance reliably? Is there really such a thing as intelligence? Chemistry grew out of alchemy. One s a science and the other is not. What s the difference? The label 'science' carries a high degree of authority, and people need to understand when the label, and the authority, are deserved. Is there any clear difference between an unscientific study and a scientific one? More generally, an understanding of what science is carries us a step closer to telling the difference between good and bad science, and the limits of good science. If we understand how science works, we can be better and more informed use of scientific expertise. (1 of 9) [ :08:14]

8 Demarcation If we wanted to know which subjects were generally accepted as science, we would probably find a fairly sharp and clear division between two categories. But we are interested in more than that! We want to understand the general characteristics of science that are different from pseudoscience. That is actually surprisingly difficult and controversial. Exercise: Critically evaluate the following characterization of science (from the Encyclopedia Britannica): any system of knowledge that is concerned with the physical world and its phenomena and that entails unbiased observations and systematic experimentation. In general, a science involves a pursuit of knowledge covering general truths or the operations of fundamental laws. Examples of Science and Pseudoscience The key to understanding Popper's demarcation criterion is to compare two examples. The first, Popper thinks is typical of science, while the second is typical of pseudoscience. Example (a): Einstein's prediction of the bending of star light. For over 200 years prior to Einstein, Newtonian physics had enjoyed a period of unprecedented success in science. Many scientists thought that Newton's theory was the end of science, and many philosophers not only believed that Newton's theory was true, they thought that it was necessarily true. They sought to explain why Newton's theory had to be true. All that began to change with Planck's 1900 introduction of the idea that energy comes in small discrete packages (the quantum hypothesis) and Einstein's discovery of the special theory of relativity in Einstein's special theory of relativity was a way of reconciling some inconsistencies between the wave theory of light and Newtonian mechanics. Instead of modifying the wave theory, he modified some of the fundamental assumptions used in Newtonian physics (like the assumption that simultaneity did not depend on a frame of reference, and that the mass does not depend on its velocity). However, Einstein's special theory of relativity said nothing about gravity. Einstein's general theory of relativity was his theory of gravitation, which he had published by Many scientists were impressed by the aesthetic beauty of Einstein's principles, but it was also important that it be tested by observation. For most everyday phenomena, in which velocities are far smaller than the speed of light, there is no detectable difference between Einstein's prediction and Newton's prediction. What we needed was a crucial experiment in which Einstein and Newton made different predictions. In 1916, there were successful tests of Einstein's special theory. But crucial tests of the general theory were harder to come by. One such case was provided by the bending of starlight by the gravity of the sun. The period from 1900 to at least 1916 was a period of revolution in physics, and Eddington's confirmation of Einstein's prediction in 1919 helped to complete the change in physics. "The idea that light should be deflected by passing close to a massive body had been suggested by the British astronomer and geologist John Michell in the 18th century. However, Einstein's general relativity theory predicted twice as much deflection as Newtonian physics. (2 of 9) [ :08:14]

9 Demarcation Quick confirmation of Einstein's result came from measuring the direction of a star close to the Sun during an expedition led by the British astronomer Sir Arthur Stanley Eddington to observe the solar eclipse of Optical determinations of the change of direction of a star are subject to many systematic errors, and far better confirmation of Einstein's general relativity theory has been obtained from measurements of a closely related effect--namely, the increase of the time taken by electromagnetic radiation along a path close to a massive body." (Encyclopedia Britannica) "The theories involved here were Einstein's general theory of relativity and the Newtonian particle theory of light, which predicted only half the relativistic effect. The conclusion of this exceedingly difficult measurement--that Einstein's theory was followed within the experimental limits of error, which amounted to +/-30 percent--was the signal for worldwide feting of Einstein. If his theory had not appealed aesthetically to those able to appreciate it and if there had been any passionate adherents to the Newtonian view, the scope for error could well have been made the excuse for a long drawn-out struggle, especially since several repetitions at subsequent eclipses did little to improve the accuracy. In this case, then, the desire to believe was easily satisfied. It is gratifying to note that recent advances in radio astronomy have allowed much greater accuracy to be achieved, and Einstein's prediction is now verified within about 1 percent." (Encyclopedia Britannica) "According to this theory the deflection, which causes the image of a star to appear slightly too far from the Sun's image, amounts to 1.75 seconds of arc at the limb of the Sun and decreases in proportion to the apparent distance from the centre of the solar disk of the star whose light is deflected. This is twice the amount given by the older Newtonian dynamics if light is assumed to have inertial properties. If light does not have such properties, as is generally accepted now, the Newtonian deflection is zero." (Encyclopedia Britannica) Reconstruction of the example: Philosophers need a general characterization of the example: Let E be a statement of the prediction made by Einstein's theory. E states the direction that the starlight will be observed at the time at which the star was to be observed by Eddington. Let T be a statement of the general principled in Einstein's general theory of relativity. Let A be the conjunction of all auxiliary statements used to derive, or deduce, E from T. That is to say, the argument with T and A as premises, and E as the conclusion, is deductively valid. Symbolically, we may write this as: T & A E. A will include assumptions like "the sun is spherical ball of mass M", "there are no other bodies close by to add to the sun's gravitational field," "If the sun were not present, then the star would be seen in the direction such-and-such," "the effect of stellar aberration on the direction of light is such-and-such," and so on. (3 of 9) [ :08:14]

10 Demarcation Example (b): Adler's 'individual psychology'. Compare the following two (hypothetical) explanations of human behavior. (1) E 1 : A man pushes a child into the water with the intention of drowning it. (2) E 2 : A man sacrifices his life in an attempt to save the child. Popper claims that Adler's 'individual psychology' can explain both of these behaviors with equal ease. Let T be Adler's theory, let A be the auxiliary assumption that the man suffered feelings of inferiority (producing the need to prove to himself that he dared to commit some crime). Then T & A 1 E 1. Let A 2 be the auxiliary assumption that the man suffered feelings of inferiority (producing the need to prove to himself that he dared to rescue the child). Now T & A 2 E 2. Definition: Let us say that a theory T predicts an event E if and only if there are auxiliary assumptions that have either been used successfully in other predictions, or are the simplest and most obvious assumptions that one would make in the situation, and that T & A E. If there exists auxiliary assumptions such that T & A E, where A is some ad hoc assumption that is introduced in light of the evidence E itself, then theory T merely accommodates E. In example (a), Einstein's theory predicts the observational evidence, while in example (b), the theory is merely accommodates the evidence. Popper describes the difference by claiming that Einstein's theory is falsifiable, whereas Adler's theory is not. Remark: Popper also claims that the problem with Adler's theory is that it is too easily verified: "the world was full of verifications of the theory." Adler may have seen it like that, but was he right? My feeling is that mere accommodations do not count as verifications at all. Hence, I think that a verificationist could account for the difference between these two examples as well as, if not better than, a falsificationist. Discussion Question: How does our previous distinction between ampliative inference and deductive inference enter into these examples, if at all. Popperians tend to think that there is no need for ampliative inference in science at all. Why might they think that? Are they right? Popper's Path to his Demarcation Criteria (Curd and Cover, pages 1-10) To understand a philosophical theory, like Popper's demarcation criterion, it is useful to see why simpler alternative proposals do not work. Proposal 1: Science is distinguished by its empirical method. That is, science is distinguished from pseudoscience by its use of observational data in making predictions. (4 of 9) [ :08:14]

11 Demarcation Objection: Astrology appeals to observation, but is not a science. Proposal 2: Scientific theories, like Einstein's, are more precise in their predictions that Adler's psychology, or astrology. Objection: While it is true that pseudosciences do often protect themselves from refutation by making vague or ambiguous predictions, that is not always the case. The 'predictions' of example (b) are precise enough for the purpose, and Einstein's prediction was not exact it had to allow for many errors of observation. Proposal 3: Science is explanatory, whereas pseudoscience is not. Objection: If you buy into the auxiliary assumptions in Adler's psychology, then the theory explains the phenomena perfectly well. It is true we have little reason to believe that the explanation is correct, but that is a different issue. Proposal 4: Science is distinguished from pseudoscience by its verifications, or confirmation. Objection: Popper's objection is that "The world was full of verifications of those theories." I have remarked that that does not ring true in examples (a) and (b). Nevertheless, there seems to be some force behind Popper's point in other examples. For example, Einstein could have pointed to all the verifications of Newton's theory for low velocities and claim these as verifications for his own theory. Yet he did not. Why not? Because, says Popper, these were not risky predictions. They were not potential falsifiers of Einstein's theory. Popper s Proposal: Every good scientific theory is a prohibition: it forbids certain things to happen. The criterion of the scientific status of a theory is its falsifiability, or refutability, or testability. Note: Popper also anticipates a major objection to his criterion: namely, that any scientific theory can be protected from refutation by introducing ad hoc auxiliary assumptions. His reply is that the very use of ad hoc assumptions, in reducing the falsifiability of theory, also diminishes its scientific status. The problem with Popper s reply is that it is not always, if ever, clear in advance that ad hoc auxiliary assumptions are needed to save the theory. This is essentially Kuhn s point. Hypothetico-Deductivism In the first set of lecture notes, I introduced the demarcation problem as a problem about the difference between good and bad kinds of ampliative inference. Popper rejects this formulation of the problem. He thinks it is wrong to think of theories as being inferred from, or induced from, the observational facts. Rather, the invention of theories is a question of (5 of 9) [ :08:14]

12 Demarcation psychology, which has nothing to do with the status of the theory as scientific. There are no scientific or unscientific ways of inventing theories. They can come in a dream or they can be constructed from the data it does not matter. Rather, the essence of science is about how predictions are deduced from the theories. This way of viewing science is known as hypothetico-deductivism. The difference between science and pseudoscience rests solely on the 'deductive' part of the process. Kuhn s Characterization of Science Thomas Kuhn makes the following points against Popper (Curd and Cover, pages 11-19): The kind of examples Popper considers, like the 1919 test of Einstein s theory of gravitation, is an example of extraordinary science, or revolutionary science. These are relatively rare in science. In non-revolutionary science, or normal science, the aim of research is to connect the experimental data to the background theory, by inventing the appropriate auxiliary assumptions. If a scientist fails, then scientist s lack of ingenuity is blamed, not the theory. It is for normal, not extraordinary, science that scientists are trained, and... "If a demarcation criterion exists..., it may lie in that part of science which Sir Karl ignores." Question: Kuhn concedes that "There is one sort of 'statement' or 'hypothesis' that scientists do repeatedly subject to systematic test. I have in mind statements of an individual s guesses about the proper way to connect his own research problem with the corpus of accepted scientific knowledge." Thus, thinks (a) a demarcation criterion should refer to normal science, and (b) falsifiability does play a role in normal science. So, why doesn t he apply a falsifiability criterion to normal science, and say that an alleged science is genuinely scientific if and only if its solutions to puzzles are falsifiable? As Kuhn says, this is not what Popper has in mind. But does the new criterion work? Central Concepts in Kuhn s Account of Revolutionary Change in Science: Kuhn denies that theories change by falsification in science, but he does not deny that theories are sometimes replaced (revised). What is his own account of theory replacement? Here is very brief summary of his positive account: 1. The process by which one paradigm is replaced by another is called revolutionary science. 2. An anomaly is a violation of "the paradigm-induced expectations that govern normal science" (Kuhn, The Structure of Scientific Revolutions, 1970, p.52). 3. A crisis in normal science occurs when puzzle-solving breaks down, either because no solutions are found, or because the discrepancy corrected in one place shows up in (6 of 9) [ :08:14]

13 Demarcation another. 4. A paradigm is overthrown only if the paradigm is in crisis and there is a second paradigm that shows equal or greater puzzle-solving potential. Kuhn s Demarcation Criterion: All of genuine science has a puzzle-solving tradition, while pseudosciences do not. Objection: Until Kuhn says what a puzzle-solving tradition is, his criterion is rather vague. Why wouldn t a research tradition that sought worked backwards from the fact to the auxiliary hypotheses count as puzzle-solving. It seems that Kuhn needs to add something like falsifiability. Kuhn on Astrology: 1. Kuhn agrees that astrology is pseudoscience, but makes the point that it was not obvious that it was pseudoscience in the century it was practiced most. That is because its auxiliary assumptions, based on the configuration of the planets at the time of birth, were subject to genuine doubt. Not everyone was sure of their exact date of birth in any case. The problem is that similar arguments explaining away failed predictions are regularly used today in medicine or meteorology. 2. Astrology has no science to practice because practitioners had rules to apply, but no puzzles to solve. Most difficulties "were beyond the astrologer s knowledge, control, and responsibility." In astronomy, however, if a prediction failed, a scientist "could hope to set the situation right." There was a puzzle-solving tradition. Final argument: For a long period of time, there was a sense in which Ptolemaic astronomy was unfalsifiable by the means available (naked-eye observations). But that did not stop it from being science at the time. Moreover, when it was finally falsified (by Galileo s observation of the phases of Venus, the moon s of Jupiter, and Brahe s observations of comets), it had already been rejected. Necessary and Sufficient Conditions necessary condition: E.g., being enrolled in this course is a necessary condition for you getting an A for the course. That is, you will not get an A if you are not registered. Or equivalently, if you do get an A, then you are registered. In general: A necessary condition for an event or state of affairs X is one that has to hold for X to be true. A necessary condition is contrasted with a sufficient condition. sufficient condition: E.g., getting an A in this course is a sufficient condition for passing this (7 of 9) [ :08:14]

14 Demarcation course. That is, it you get an A then you will pass. In general: A sufficient condition for an event, or state of affairs X is one that enough to makes X true. necessary and sufficient condition: A condition is necessary and sufficient for a statement, or event, X if and only if it is necessary for X and sufficient for X. It is often expressed by the phrase if and only if or the abbreviation iff. E.g., a necessary and sufficient condition for passing this course is to receive a passing grade while being registered for the course. Popper says that the falsifiability is a necessary and sufficient condition for genuine science. Falsifiability is not a sufficient condition because astrology is falsifiable but not a science. In the 1960s, Michael Gauquelin examined the careers and times of birth of 25,000 Frenchmen, and found no significant correlation between careers and either sun sign, moon sign, or ascendant sign (see the Thagard reading). Gauquelin found some statistically significant correlations between certain occupations and the positions of certain planets at the time of their birth, but we can expect 1 in 20 random associations will be statistically significant by chance alone. Also, studies of twin do not show the correlation one would expect. These results cannot be explained away by supposing that almost all assumptions in every case were false. Therefore, such a study falsifies astrology in a sense that Popper would accept, and these studies were always possible, which proves that astrology was always falsifiable. Falsifiability is not necessary for science. The example of Ptolemaic astronomy shows this, because prior to the invention of telescope it was not falsifiable but it was still a science. Counterexamples: In order to show that a condition is not a sufficient condition for X, we only need an example in which the condition holds, but X does not. In order to show that a condition is not a necessary condition for X, we only need an example in which X holds but the condition does not. In each case, the examples are called counterexamples. Astrology is a counterexample for the sufficiency of falsifiability for science, and Ptolemaic astronomy is counterexample to its necessity. Here are some other arguments that make use of counterexamples. Astrology is not a science because it has mystical origins. Counterexample: Chemistry had its origins in alchemy and medicine had occult beginnings. Astrology is not a science because people believe astrology for irrational reasons. Counterexample: Many people believe in Einstein's theories for irrational reasons. Astrology is not a science because it assumes that gravitational influences of the planets influence us, but they are too weak to do that. Counterexamples: The lack of a physical foundation did not stop geologists from believing in continental drift, and we (8 of 9) [ :08:14]

15 Demarcation have plenty of evidence to prove that smoking causes lung cancer with knowing the details of the carcinogenesis. (9 of 9) [ :08:14]

16 Lakatos Lakatos's Methodology of Scientific Research Programs Last modified on Thursday, September 24, 1998, by Malcolm R. Forster Points of Disagreement between Lakatos and Kuhn 1. Subjective or objective? Kuhn s demarcation criterion appears to be subjective--it depends on what scientists do and what they believe (their psychology). In contrast, Lakatos insists that "a statement may be pseudoscientific even if it is eminently plausible and everyone believes in it." Belief that earth is flat may count as an example of that. And "it may be scientifically valuable even if it is unbelievable and nobody believes in it." Copernicus's theory that the sun moves like that, and very few believed in evolution when Darwin introduced his theory. 2. Sociology or logic? Another point of disagreement between Kuhn and Lakatos is whether a demarcation criterion should be talking about which statements are scientific or pseudoscientific, or whether it should be saying which community is scientific or unscientific. Lakatos, as a neo-popperian, was raised in the tradition in which logic was the main tool in philosophy of science, whereas Kuhn is more interested in the sociology of science. 3. Religion or Science? Kuhn compares science to religion, but Lakatos rejects this comparison. Main Point of Agreement between Lakatos and Kuhn Any good science can be practiced in a pseudoscientific way. The demarcation between science and pseudoscience refers to its method and not just what the theory says (its content). For example, some evolutionists may be tempted to fill in auxiliary assumptions in an ad hoc way by working backwards from what is to be explained. For example, if see from the fossil record that horses teeth become elongated, we may be tempted into using evolutionary theory to infer that there was some change in the environment that made shorter teeth less fit, and then explain the change by appealing to the law of natural selection that "only the fittest survive." It would be equally easy for Newtonian mechanics to be practiced in a pseudoscientific way. After all, Newton s law of inertia says that a body continues in a straight line with uniform velocity until acted on by a force, and then defines a force as anything that diverts a body from uniform motion in a straight line. Lakatos on Popper s Demarcation Criterion (1 of 8) [ :08:43]

17 Lakatos 1. Lakatos argues that falsifiable already refers to how science is practiced. He interprets Popper as demanding that scientists "specify in advance a crucial experiment (or observation) which can falsify it, and it is pseudoscientific if one refuses to specify such a potential falsifier. If so, Popper does not demarcate scientific statements for pseudoscientific ones, but rather scientific method from non-scientific method." 2. While Popper s criterion does focus on practice, it is still wrong because it "ignores the remarkable tenacity of theories." Scientists will either invent some rescue hypothesis (accommodate the theory) or ignore the problem and direct their attention to other problems. For example, some problems may be too hard (nobody rejected Newtonian mechanics because it couldn t predict all the properties of turbulent fluid flow, or the chaotic motion of a physical pendulum). A Puzzle about Prediction Earlier, we saw that Popper's two examples, Adler's theory at one extreme, and Einstein's theory at the other, illustrated a difference between accommodation and prediction. Adler's theory merely accommodated the facts because it worked backwards from the evidence E to the auxiliary assumption A needed so that the theory T entailed E (T & A E). At the other extreme, if intellectual honesty requires that a scientist specify a potential falsifier in advance, then they must specify A in advance. That is a sufficient condition for the theory to make a prediction. But is it necessary? Lakatos s Picture of Science The typical unit of science is not an isolated hypothesis, but rather a research programme, consisting in a hard core (theory), protective belt (auxiliary assumptions) and a heuristic. Lakatos quote: A heuristic is a "powerful problem solving machinery, which with the help of sophisticated mathematical techniques, digests anomalies and even turns them into positive evidence. For instance, if a planet does not move exactly as it should, the Newtonian scientist checks his conjectures concerning atmospheric refraction, concerning propagation of light in magnetic storms, and hundreds of other conjectures that are all part of the programme. He may even invent a hitherto unknown planet and calculate its position, mass and velocity in order to explain the anomaly." (Lakatos, 1977, p. 5) In Kuhn's terminology: Heuristics are hints about how to solve normal science puzzles. In my terms: A heuristic is a hint about how to change the auxiliary assumptions so that the theory better fits the facts. The negative heuristic forbids scientists to question or criticize the hard core of a research programme. "The positive heuristic consists of a partially articulated set of suggestions or hints (2 of 8) [ :08:43]

18 Lakatos on how to change, develop the 'refutable variants' of the research programme, how to modify, sophisticate, the 'refutable' protective belt." (Lakatos, 1970, p.135). Example: Le Verrier and Adams were faced with the following problem in Newton's theory of planetary motion. There were discrepancies (unpredicted wobbles) in the motion of the outermost planet known at the time (Uranus). They postulated that these might be caused by a hitherto unknown planet. Based on that conjecture they recalculated the solutions to Newton's equations, and fit the solutions to the known data for Uranus. That fit even predicted the position of the postulated planet, whereupon Neptune was seen for the first time once telescopes were pointed in that direction (actually, it was later discovered that it had been seen before, but mistaken for a comet). In this example, the positive heuristic used was something like this: "If there is an anomaly in Newton's theory on the assumption that there are n planets, then try assuming that there are n+1 planets." The Role of Background Evidence We have identified auxiliary assumptions with Lakatos's protective belt. That is, we are assuming that auxiliary assumptions are always provisional in some sense. However, we must now decide whether to count statements of background evidence, prior observations, and data, as auxiliary assumptions. They are auxiliary in the sense that they are needed in order to make predictions. In the Le Verrier-Adams example it would be impossible to predict the position of the postulated planet without making use of the observed positions of Uranus, and the other planets. Let use refer to this background data by the letter D ('D' for data). We now replace the previous pattern of inference (T & A E) by the pattern: T & A & D E. We still refer to A as the auxiliary assumption, but with the explicit understanding that it excludes the background observational evidence or data D. Models It may be useful at this point to introduce the concept of a model. A model is theoretical statement, (often in the form of an equation) usually deduced from a theory with the aid a auxiliary assumptions. That is, a model M is equal to a theory T combined with an auxiliary assumption A (which will be long list of assumptions in most cases). That is, M = T & A. Example: In the LeVerrier-Adams example, there was first a Newtonian model of planetary motion that assumed that there are only 7 planets. There were discrepancies between the (3 of 8) [ :08:43]

19 Lakatos predictions of this model and the observed motions of Uranus. Therefore, the model was replaced by one that assumed the existence of 8 planets. Not only did that accommodate the anomalous motion of Uranus, but it predicted position of the eighth planet, whereupon Neptune was discovered. Remarks: 1. A model M is falsified when M & D E because D is not blamed for the failed prediction. Therefore, models are falsifiable, or refutable, even though theories are not. 2. The notion of a 'model' corresponds to Lakatos's notion of a 'refutable variant of a theory'. If a Lakatosian heuristic defines an ordered list of auxiliary assumptions, A 0, A 1, A 2, A 3,... then it also defines an ordered list of models M 0, M 1, M 2, M 3, This use of the term 'model' differs from two other uses that are common in the philosophy of science. (a) A 'model' as in a model airplane. Such models do appear in science, such as in the 'model of the DNA molecule' Watson and Crick used, which was made of wooden balls joined with sticks. (b) 'Model' in the sense used by mathematicians in model theory. There it has a rather technical meaning, which corresponds roughly to what logicians call an interpretation of a language (an assignment of objects to names, set of objects to properties, a set of object pairs to relations, and so on). 4. Scientists use the term 'model' all the time, and it very rarely fits sense (a) and absolutely never fits sense (b). Our use of the term best fits the standard scientific usage. Solution to the Puzzle about Prediction If a heuristics exists, then a scientist has an ordered list of suggested models M 0, M 1, M 2, M 3,... Now the theory T is no longer falsifiable in Popper's methodological sense, for if a scientist tries makes the prediction E 0 from model M 0 and E 0 proves to be false, then the scientist does not blame T, but instead moves to M 1, because it is next on the ordered list, and so on. Scientists now predict E 1 because M 1 & B E 1. And so on. There is no falsifiability of the theory, but it can still make predictions. Thus, the idea of a heuristic may save the distinction between accommodation and prediction, and thereby providing a weaker sufficient condition for prediction. Note that the research program makes a different set of predictions at different times. This allows Lakatos to introduce the idea of novel predictions--new predictions not make before. When Should One Model Supercede Another? (4 of 8) [ :08:43]

20 Lakatos Lakatos does not believe that falsification is important in science, but like Kuhn, he does recognize that theories, or paradigms, are superceded in science. He objects to Kuhn's description of this process, of scientific revolutions, as being a like a religious conversion, or a social revolution. Lakatos things that the process is more objective. Here is his view. Thesis: A model M supercedes a model M if and only if (1) M has excess empirical content over T : that is, it predicts novel facts, that is, facts improbable in light of, or even forbidden by M; (2) M explains the previous success of M, that is, all the unrefuted content of M is contained (within the limits of observational error) in the content of M ; and (3) some excess content of M is corroborated. (see Lakatos, 1970, p. 116; the phrase "should supercede" is my paraphrase, and I have replaced 'theory' by 'model'.) This is Lakatos's account of normal science. Lakatos introduces some new terminology to help formulate his theory of science. 1. A problemshift is a series of models...m 1, M 2,... such that (i) each can explain the empirical success of its predecessor, and (ii) each can explain at least some of the emprical failure of it predecessor as well. In other words, a Lakatosian problemshift occurs whenever a Kuhnian solution to a normal science puzzle is found, since to be a solution is must remove the anomaly with creating new one. Note that a problemshift does not have to make novel predictions. 2. A theoretically progressive problemshift is a problemshift that predicts some novel facts. 3. A problemshift is empirically progressive if it is theoretically progressive and some of the novel predictions have been corroborated. Note: In Lakatos's original writings, Lakatos uses the word 'theory' instead of 'model', but only because he fails to make the distinction. I think that he models in mind. Definition: A problemshift is progressive if it is theoretically and empirically progressive. Otherwise the problemshift is degenerating. The idea of a degenerating problemshift corresponds to Kuhn's notion of crisis. Example 1: The LeVerrier-Adams discovery of Neptune is a great example of a problemshift that was progressive, because (1) it led to novel predictions (the position of Neptune), which (2) were then corroborated. Example 2: Ptolemaic astronomy was degenerating not because it failed to be theoretically progressive (Ptolemaic astronomers had the option of adding more epicycles) but because it was not empirically progressive. That is, adding an epicycle would lead to novel predictions, (5 of 8) [ :08:43]

21 Lakatos but they were not corroborated (confirmed). Lakatos on Revolutions What is Lakatos's theory about when one theory should supercede another? In fact, Lakatos does not provide such a criterion. Not even when one research program is degenerating and another is progressive does Lakatos say that scientists do or should only work on the progressive one, because like the stock-market, they may change their status over time. The methodology of scientific research programmes does not offer instant rationality. It is not irrational for a scientist to work on a young research programme if she thinks it shows potential. Nor is it irrational for a scientist to stick with an old programme in the hope of making it progressive. Thus, Lakatos appears to agree with Kuhn that theory change is a rather fuzzy phenomenon. But he does insist that it depends on the assessment of objective facts--the future progressiveness or degeneration of research programs. The decision of scientists, however, must rely of their subjective predictions of the future course of science. Unlike Kuhn, Lakatos does not think that the uncertainty makes these decisions irrational. Example 3: Prout's program. Prout, in 1815, claimed that the atomic weights of all pure elements were whole numbers. He knew that the experimental results known at the time did not confirm his theory, but he thought that this arose because chemical substances as they naturally occurred were impure. Thus, there ensued a program of research whereby chemical substances were purified by chemical means. This program led from one failure to the next. The program at this stage was degenerating. However, Rutherford's school explained this failure by the fact that different elements can be chemically identical (as explained by the periodic table). They proposed that the substances should be purified by physical means (powerful centrifuges), whereupon the program made a progressive shift. Lakatos (1970, pp ) uses this as an example of why it would be wrong to advise scientists to instantly abandon a degenerating research program. Question: We have talked about Lakatos's view of normal science and revolutionary science. However, this is separate from the demarcation issue. Popper thinks that the essence of science lies in the nature of revolutions, but Kuhn thinks that the essence of science lies in the nature of non-revolutionary science. Where does Lakatos stand on this issue? Lakatos's Demarcation Criterion Lakatos is not explicit about his demarcation criterion in the passage we read, but he is explicit about in his 1970 article: "We 'accept' problemshifts as 'scientific' only if they are at least theoretically progressive; if they are not, we 'reject' them as 'pseudoscientific.'" (1970, p. 118) (6 of 8) [ :08:43]

22 Lakatos Presumably, therefore, a research program is scientific if and only if it is at least theoretically progressive. Note that it is possible for a research program to be scientific at one time, but not at another. It is even that a program practiced by one group is scientific, while the practice of another group is pseudoscientific. This is how Lakatos is agreeing with Kuhn's point that even a good theory can always be practiced in a pseudoscientific was. Thus, Adler's theory (about inferiority complexes) might potentially be a good theory, but the fact is that it was being practiced in a pseudoscientific way (if Popper's account is correct). Lakatos is agreeing with Kuhn, against Popper, that the essence of science lies in the nature of normal science. Example 4: Astrology. Astrology has no theoretically progressive problemshifts, and therefore no empirically progressive problemshifts. That is, it made no novel predictions, despite that fact that it made predictions. Therefore, astrology was not a science. Example 5: Prout's program. While Prout's program was degenerating, it was still theoretically progressive, and hence scientific. Example 6: Jeane Dixon was a self-proclaimed psychic who predicted that JFK's assassination. She made over 200 predictions each year (most of them wrong of course). Did her method count as scientific? It would be by Popper's criterion, but not by Kuhn's or Lakatos's demarcation criteria. Like astrology, there was no Kuhnian puzzle solving, and no theoretically progressive problemshifts. Musgrave's Criticisms of Lakatos In an article called "Method or Madness" (in Cohen, R. S., Feyerabend, P. K.. and Wartofsky, M. W. (eds) Essays in Memory of Irme Lakatos, Dordrecht, Holland, D. Reidel), Alan Musgrave (1976) raises some interesting objections to Lakatos's theory of science, which I have expanded upon in places. 1. Is the negative heuristic needed? Before 1850, Newtonian seldom treated Newton's law of gravitation as part of the hard core. Therefore, scientists did not follow Lakatos's methodology and render Newton's laws unfalsifiable by fiat. And why should scientists have to specify in advance not to modify or renounce them in the face of difficulties. Surely, it is enough that it is harder to produce theoretically problemshifts by changing central assumptions because it is then harder to explain all the successes of the superceded model. But there is no reason to rule it out in advance. 2. Are positive heuristics always specified in advance? Where was the positive heuristic in the example of Prout's program? No-one tried physical separation of chemical substances as soon as the chemical methods failed. They kept trying to improve the chemical methods. It was only after the discovery of chemical similarities (7 of 8) [ :08:43]

23 Lakatos that the hint or suggestion appeared. 3. Why not compare one research program against another? Musgrave thinks that Lakatos is overcautious in not recommending any rule for choice between competing research programs. Why not say, that on the whole, the scientific community should devote more resources to progressive as opposed to degenerating research programs? (8 of 8) [ :08:43]

24 Evolution Evolutionary Theory Last modified on Friday, October 02, 1998, by Malcolm R. Forster (Extracted in part from "Philosophy of Biology" by James G. Lennox) Fact versus theory: Fact of evolution = the fact that evolution has occurred. Theory of evolution = an explanation about how and why evolution has occurred. Note: Darwin did help establish the fact of evolution. However, the fact of evolution was already accepted by some prominent biologists prior to Darwin, so this is not his most important claim to fame. It is possible to accept the fact of evolution, but to seriously disagree with (or even misunderstand) Darwin s theory of how the fact of evolution come about. Darwin s theory of evolution is roughly as follows: 1. The struggle for survival: Biological organisms have more offspring than can possibly survive. 2. Inheritability: Biological organisms inherit some of their traits from their ancestors and pass them on to their descendents. 3. Variation: The inheritable traits of biological organisms vary, even within the same species. 4. Differential fitness: Some inheritable traits will be more advantageous than others in the struggle for survival. Therefore, there has been and will continue to be, on average, a (natural) selection of those organisms that have advantageous traits that will lead to the evolution of species. This is what Lakatos would call the hard core of Darwin s research program. The radical nature of Darwin s theory The fact of evolution is radical enough, especially in light of the extremely recent arrival of homo sapiens. It questions the primacy of our place of the universe. However, the Darwin s theory is even more radical than that. Darwin delayed publication of his theory for many years; in fact he only published when he discovered that Wallace was about to publish the (1 of 11) [ :09:06]

25 Evolution same theory. The probable reason for his delay was a fear of the controversy his theory would provoke. 1. Darwin s theory undermines one of best theological arguments for the existence of God: If you come across a watch, and observed its intricate design, then it is reasonable to infer the existence of a watchmaker. If you come across a biological organism that has an even more intricate design, then it is reasonable to infer the existence of a Creator. This is called the argument from design. Evolutionary theory provides an alternative explanation. Moreover, the imperfection of many designs is evidence for evolution and against design. 2. Darwin s theory does not imply that evolution is progressive. Evolution has no predetermined direction. The direction of evolutionary change depends on the local environment at the time. There is no progression from inferior to superior organisms implied by the theory. In fact, immoral traits like ruthlessness and violence are often rewarded in evolution. In particular, there is no implication that homo sapiens is superior to other species. There is no final cause directing evolutionary change. Evolution is not teleological or goal directed. 3. Darwin s theory supports a materialistic world view (nothing to do with materialism in the consumer sense). The view that humans have souls, while animals do not, finds no place in Darwin s theory. It supports the view that the only things in the universe are material things. The protective belt: Darwin s theory predicts (or postdicts) that evolution has occurred. However, the theory, by itself, does not say which traits are inheritable, nor how they vary, or the way in which resources are limited, or how the different traits aid in survival, or how all these factors change over time. A model of a particular episode or instance of evolutionary change will add specific details to the hard core assumptions, concerning: a. the range of inheritable traits in a biological population(s). b. the environment, and how it changes over time. c. the relative benefit that these traits confer to the members of the populations possessing them in the various environments (fitness values). Accommodation versus prediction: Some of these details may be introduced as parameters (e.g., fitness parameters), which are inferred backwards from facts to be explained. But if all of these details are inferred from the facts to be explained, then the theory is merely accommodating the facts, and there are no predictions (or postdictions). In that case, evolutionary theory would be pseudoscientific according to Lakatos s demarcation criterion. (2 of 11) [ :09:06]

26 Evolution The positive heuristic, if it exists, should suggest how these details should be filled in should the most plausible assumption fail to accommodate the observational facts. Definition: A homology is a similarity between or amongst different species that is the result of their common ancestry. There are at least 3 kinds of homologies: (a) Structural homologies such as the similarity between the bone structure in a bat s wing and our forearm. (b) Behavioral homologies arising for instincts inherited from a common ancestor. (c) Protein homologies in which the sequences of amino acids that for a protein are similar because of common ancestry. Similarities that do not arise from common ancestry, such as the wing of a bird and the wing of an insect, are called analogies. Kinds of evidence for evolution: 1. The fossil record. The facts of evolution, or the story of evolution has been pieced together mainly from the fossil record. Example 1 is an example of Darwin s theory may explain such evidence. 2. Homologies in living species. If we look carefully at living species we see surprising and unexpected similarities (Lakatos s novel facts?) between disparate species. These may range from similar bone structures in limbs of whales and bears, to similarities of the instinctive behavior of water fowl living in quite different areas of the globe, to similarities and differences in protein sequences in living organisms. 3. Artificial selection. Breeding experiments that show that selection can transform a population from one kind to another. This provides limited support for inheritability and variation. It does not provide evidence for the other postulates. 4. Experimental evidence from genetics. There is now a lot of biochemical evidence about DNA and the mechanisms of inheritance. This helps provide auxiliary hypotheses about the source of inheritable variation, and the mechanisms of inheritance. For example, it could help support Assumption 3 in Example 1. Let's at an example of evolutionary explanation. Example 1: The evolution of horses. Fact to be explained: In the lineage leading up to the modern genus Equus, of which the horse is a species, the fossil record shows that the ratio of molar tooth height to length increases over time, and that there is an acceleration in the rate of change through time. Assumption 1: The environment changed. In the Miocene period, Merychippus and its descendents abandoned the habit common to all earlier horses of browsing on leaves, and took the newly evolved grasses as their main food. Support: There is independent fossil evidence confirming that grasses evolved and (3 of 11) [ :09:06]

27 Evolution become abundant at that time. Assumption 2: Engineering assumption. The high silicate content of grasses makes for increased wear per unit of vegetation consumed. Support: Look at modern species and assume that the same physical facts apply for all time. Also note that there was another horse lineage which continued to grace on leaves and did not evolve an elongated tooth. Assumption 3: Adaptationist assumption. Height to length ratio of teeth varied in horse populations, and was an inheritable trait. Support: Look at modern horse species to check for variation and check for inheritability through artificial breeding experiments. Assumption 4: Resource assumption. There were greater food resources available per individual for those horses able to grace on the newly evolved grasses. Support: It is almost a matter of logic to say that a horse that can eat leaves or grass has more food available to it than a horse that can only eat leaves. Assumption 5: Co-evolution assumption. Grass continued to be a viable food resource despite the grazing of the new horse species. That is, the grasses managed to survive this grazing assault. Remarks: Support: Look at fossil evidence for grasses; compare "grazability" of modern grasses. 1. It is very hard to think of all the auxiliary assumptions need to deductively entail the fact to be explained. 2. Most of the assumptions have independent sources of support. It will not matter if some of the assumptions have no independent support, since some degree of accommodation is allowed. 3. Some of the assumptions talk about other instances of evolution. Does this beg the question? No, at worst it shows that the explanations need to be evaluated as a whole. That is why Darwin's Origin was convincing in a way that previous arguments for evolution were not--it tied together many different explanations that appealed to the same core assumptions. 4. What matters is that various facts are tied together in a surprisingly tidy way, which is hard to explain as "arising from chance". (4 of 11) [ :09:06]

28 Evolution Figure 1: Phylogeny based on differences in the protein sequence of cytochrome c in organisms ranging from Neurospora mold to humans. "The Theory of Evolution: Patterns and rates of species evolution: MOLECULAR EVOLUTION: The molecular clock of evolution." Britannica Online. < (5 of 11) [ :09:06]

29 Evolution Figure 2: Rate of nucleotide substitution over paleontological time. Each dot marks (1) the point at which a pair of species diverged from a common ancestor and (2) the number of nucleotide substitutions, or protein changes, that have occurred since the divergence. The solid line drawn from the origin to the outermost dot gives the average rate of substitution. From F.J. Ayala, E. McMullin (ed.), Evolution and Creation (1985) "The Theory of Evolution: Patterns and rates of species evolution: MOLECULAR EVOLUTION: The molecular clock of evolution." Britannica Online. < (6 of 11) [ :09:06]

30 Evolution VESTIGES OF EVOLUTION: "Human and other nonaquatic embryos exhibit gill slits even though they never breathe through gills. These slits are found in the embryos of all vertebrates because they share as common ancestors the fish in which these structures first evolved. Human embryos also exhibit by the fourth week of development a well-defined tail, which reaches maximum length when the embryo is six weeks old. Similar embryonic tails are found in other mammals, such as dogs, horses, and monkeys; in humans, however, the tail eventually shortens, persisting only as a rudiment in the adult coccyx." "The Theory of Evolution: The evidence for evolution: EMBRYONIC DEVELOPMENT AND VESTIGES" Britannica Online. < BIOGEOGRAPHY: "Darwin also saw a confirmation of evolution in the geographic distribution of plants and animals, and later knowledge has reinforced his observations. For example, there are about 1,500 species of Drosophila vinegar flies in the world; nearly one-third of them live in Hawaii and nowhere else, although the total area of the archipelago is less than onetwentieth the area of California. There are also in Hawaii more than 1,000 species of snails and other land mollusks that exist nowhere else. This unusual diversity is easily explained by evolution. The Hawaiian Islands are extremely isolated and have had few colonizers; those species that arrived there found many unoccupied ecological niches, or local environments suited to sustain them and lacking predators that would prevent them from multiplying. In response, they rapidly diversified; this process of diversifying in order to fill in ecological niches is called adaptive radiation." "The Theory of Evolution: The evidence for evolution: BIOGEOGRAPHY" Britannica Online. < MOLECULAR EVOLUTION: A remarkable uniformity exists in the molecular components of organisms--in the nature of the components as well as in the ways in which they are assembled and used. In all bacteria, plants, animals, and humans, the DNA comprises a different sequence of the same four component nucleotides, and all of the various proteins are synthesized from different combinations and sequences of the same 20 amino acids, although several hundred other amino acids do exist. The genetic "code" by which the information contained in the nuclear DNA is passed on to proteins is everywhere the same. Similar metabolic pathways are used by the most diverse organisms to produce energy and to make up the cell components. (7 of 11) [ :09:06]

31 Evolution This unity reveals the genetic continuity and common ancestry of all organisms. There is no other rational way to account for their molecular uniformity when numerous alternative structures are equally likely. The genetic code may serve as an example. Each particular sequence of three nucleotides in the nuclear DNA acts as a pattern, or code, for the production of exactly the same amino acid in all organisms. This is no more necessary than it is for a language to use a particular combination of letters to represent a particular reality. If it is found that certain sequences of letters--planet, tree, woman--are used with identical meanings in a number of different books, one can be sure that the languages used in those books are of common origin. Genes and proteins are long molecules that contain information in the sequence of their components in much the same way as sentences of the English language contain information in the sequence of their letters and words. The sequences that make up the genes are passed on from parents to offspring, identical except for occasional changes introduced by mutations. To illustrate, assume that two books are being compared; both books are 200 pages long and contain the same number of chapters. Closer examination reveals that the two books are identical page for page and word for word, except that an occasional word--say one in 100--is different. The two books cannot have been written independently; either one has been copied from the other or both have been copied, directly or indirectly, from the same original book. Similarly, if each nucleotide is represented by one letter, the complete sequence of nucleotides in the DNA of a higher organism would require several hundred books of hundreds of pages, with several thousand letters on each page. When the "pages" (or sequence of nucleotides) in these "books" (organisms) are examined one by one, the correspondence in the "letters" (nucleotides) gives unmistakable evidence of common origin. The arguments presented above are based on different grounds, although both attest to evolution. Using the alphabet analogy, the first argument says that languages that use the same dictionary--the same genetic code and the same 20 amino acids--cannot be of independent origin. The second argument, concerning similarity in the sequence of nucleotides in the DNA or the sequence of amino acids in the proteins, says that books with very similar texts cannot be of independent origin. The evidence of evolution revealed by molecular biology goes one step further. The degree of similarity in the sequence of nucleotides or of amino acids can be precisely quantified. For example, cytochrome c (a protein molecule) of humans and chimpanzees consists of the same 104 amino acids in exactly the same order; but differs from that of rhesus monkeys by one amino acid, that of horses by 11 additional amino acids, and that of tuna by 21 additional amino acids. The degree of similarity reflects the recency of common ancestry. Thus, the inferences from comparative anatomy and other disciplines concerning evolutionary history can be tested in molecular studies of DNA and proteins by examining their sequences of nucleotides and amino acids. The authority of this kind of test is overwhelming; each of the thousands of genes and (8 of 11) [ :09:06]

32 Evolution thousands of proteins contained in an organism provides an independent test of that organism's evolutionary history. Not all possible tests have been performed, but many hundreds have been done, and not one has given evidence contrary to evolution. There is probably no other notion in any field of science that has been as extensively tested and as thoroughly corroborated as the evolutionary origin of living organisms. "The Theory of Evolution: The evidence for evolution: MOLECULAR BIOLOGY" Britannica Online. < Homology, in biology, similarity of the structure, physiology, or development of different species of organisms based upon their descent from a common evolutionary ancestor. Homology is contrasted with analogy, which is a functional similarity of structure based not upon common evolutionary origins but upon mere similarity of use. Thus the forelimbs of such widely differing mammals as humans, bats, and deer are homologous; the form of construction and the number of bones in these varying limbs are practically identical, and represent adaptive modifications of the forelimb structure of their common early mammalian ancestors. Analogous structures, on the other hand, can be represented by the wings of birds and of insects; the structures are used for flight in both types of organisms, but they have no common ancestral origin at the beginning of their evolutionary development. A 19th-century British biologist, Sir Richard Owen, was the first to define both homology and analogy in precise terms. "homology" Britannica Online. < Figure 3: The labellum of (9 of 11) [ :09:06]

33 Evolution the mirror ophrys (Ophrys speculum). The colouring so closely resembles that of the female wasp Colpa aurea that males of the species are attracted to the flower and pick up pollen during their attempts at copulation. E.S. Ross DOBZHANSKY: Between 1920 and 1935, mathematicians and experimentalists began laying the groundwork for a theory combining Darwinian evolution and Mendelian genetics. Starting his career about this time, Dobzhansky was involved in the project almost from its inception. His book Genetics and the Origin of Species (1937) was the first substantial synthesis of the subjects and established evolutionary genetics as an independent discipline. Until the 1930s, the commonly held view was that natural selection produced something close to the best of all possible worlds and that changes would be rare and slow and not apparent over one life span, in agreement with the observed constancy of species over historical time. Dobzhansky's most important contribution was to change this view. In observing wild populations of the vinegar fly Drosophila pseudoobscura, he found extensive genetic variability. Furthermore, about 1940 evidence accumulated that in a given local population some genes would regularly change in frequency with the seasons of the year. For example, a (10 of 11) [ :09:06]

34 Evolution certain gene might appear in 40 percent of all individuals in the population in the spring, increase to 60 percent by late summer at the expense of other genes at the same locus, and return to 40 percent in overwintering flies. Compared to a generation time of about one month, these changes were rapid and effected very large differences in reproductive fitness of the various types under different climatic conditions. Other experiments showed that, in fact, flies of mixed genetic makeup (heterozygotes) were superior in survival and fertility to pure types. "Dobzhansky, Theodosius" Britannica Online. < INDUSTRIAL MELANISM: Melanism refers to the deposition of melanin in the tissues of living animals. The chemistry of the process depends on the metabolism of the amino acid tyrosine, the absence of which results in albinism, or lack of pigmentation. Melanism can also occur pathologically, as in a malignant melanoma, a cancerous tumour composed of melaninpigmented cells. Melanic pigmentation is advantageous in many ways: (1) It is a barrier against the effects of the ultraviolet rays of sunlight. On exposure to sunlight, for example, the human epidermis undergoes gradual tanning as a result of an increase in melanin pigment. (2) It is a mechanism for the absorption of heat from sunlight, a function that is especially important for cold-blooded animals. (3) It affords concealment to certain animals that become active in twilight. (4) It limits the incidence of beams of light entering the eye and absorbs scattered light within the eyeball, allowing greater visual acuity. (5) It provides resistance to abrasion because of the molecular structure of the pigment. Many desert-dwelling birds, for example, have black plumage as an adaptation to their abrasive habitat. "Industrial" melanism has occurred in certain moth populations, in which the predominant coloration has changed pale gray to dark-coloured individuals. This is a striking example of rapid evolutionary change; it has taken place in less than 100 years. It occurs in moth species that depend for their survival by day on blending into specialized backgrounds, such as lichened tree trunks and boughs. Industrial pollution, in the form of soot, kills lichens and blackens the trees and ground, thus destroying the protective backgrounds of light-coloured moths, which are rapidly picked off and eaten by birds. Melanic moths, by their camouflage, then become selectively favoured. "Industrial" melanic moths have arisen from recurrent mutations and have spread via natural selection. "melanin" Britannica Online. < (11 of 11) [ :09:06]

35 Creationism The Creationist Debate Last modified on Sunday, October 11, 1998, by Malcolm R. Forster Background: Creationists are happy with either of two claims: 1) Creationism is not a science, and neither is evolutionary theory (which should not be taught in schools), or 2) evolutionary theory is a science but so is creationism (which should be taught in schools along side evolutionary theory). They would be happier with 1) but will settle for 2). In recent years, anti-creationists have concentrated on blocking arguments to the second conclusion. Ruse's criteria for science 1. Science looks for patterns in nature, order, and natural regularities (laws). 2. Science is explanatory, and the use of natural regularities is necessary for this purpose. 3. Science makes predictions, and the use of natural regularities is necessary for this purpose. 4. Science looks for testability. This has two aspects. (a) Confirmation, or positive support for the theory. (b) a theory must be open to possible falsification. E.g., if a planet were discovered going in squares, then the laws would have been shown to be incorrect. 5. Science is tentative. A scientist must be prepared to reject his theory. 6. Science should strive for simplicity and unification. 7. Scientists should be intellectually honest. Criticisms and Comments: a. It is not clear to me why natural regularity is necessary for explanation. Nor is it clear to me that explanation is necessary for science, although if science is often explanatory. b. In 4, Ruse should not claim that theories are open to logical falsification. He need only insist that the theories models are open to falsification. Theories are and should be rejected, but that is covered 5. c. There is no mention of the distinction between prediction and accommodation, which I think is important. d. The emphasis on natural laws plays an important role in Ruse's argument because he quotes two different creationists, who emphasize that the process used by God in the act of creation are now not operating in the natural universe. However, I do not see why science should care about the difference between natural and unnatural laws. Show me an unnatural law and I will make good scientific predictions and explanations. Laudan's complaints (1 of 4) [ :09:24]

36 Creationism A. Creationism does make testable empirical assertions; e.g., that the earth is 6,000 to 20,000 year old, and most of the features of the earth's surface are diluvial (arising for the great flood). They are testable, and they have failed those tests (c. f. astrology.) B. Creationists have changed their views. C. To say that science is a matter of natural law is rather fuzzy. Darwinism was accepted by many scientists well before the laws of genetics were known. Continental drift was accepted before the mechanism was understood. Smoking is accepted as a cause of cancer, even though the mechanism is still not fully understood. D. Ruse s standards of testability and revisability are exceedingly weak. They could be satisfied by the declaration "I will abandon creationism if we find a living specimen between man and the apes." Exceedingly unlikely, but strong enough for falsifiability. E. The key issue, according to Laudan, is whether evolutionary theory is better supported by the evidence than creationism. Debating the scientific status of the theories is a red herring. Arguments that Creationism is a Pseudoscience (Kitcher) Argument 1: Scientific theories make predictions (= observational consequences deduced from the theory). If the predictions prove to be false, then the theory is false. That is, scientific theories are falsifiable (the Popperian demarcation criterion). Creationist theory is not falsifiable. Therefore creationist theory is not science. Objection: Predictions are not deduced from scientific theories alone. Therefore, if the prediction prove false, the theory is not falsified. Thus, a key premise in the argument is false. Argument 2: Scientific theories together with auxiliary assumptions form models. Predictions are deducible from models. Scientific models are falsifiable. Creationist models are not falsifiable. Therefore creationism is not a science. Objection: (Kitcher 1982, "Believing Where We Cannot Prove" (reading 72), p. 66) Imagine that we want to expose some self-styled spiritual leader as a fraud. We point out that the teacher's central doctrine "Quietness is wholeness in the center of stillness" is unfalsifiable. Call this doctrine D. But when it is coupled with other statements, it produces observational consequences. For instance, let O be any observational statement. Then D combined with "If D then O" has the observational consequence O. So, there are models of the "theory" (M = {D, if D then O}) that are falsifiable. In other words, this criterion lets in too much, and it (2 of 4) [ :09:24]

37 Creationism would be easy for creationists to use it to argue that creationism is a science. Argument 3: (Kitcher's) In genuine science, auxiliary hypotheses are independently tested, scientific theories tend to be unified, and scientific theories suggest new lines of investigation and new models (fecundity). Creationism does not display this cluster of features. Therefore, creationism is not a science. Objection: While I agree that these features mark a difference between genuine science and creationism, it is not clear why these features of science are relevant to the purpose of science as a source of knowledge. This is not really an objection, but it does suggest that the argument is incomplete. Argument 4: (Mine) Science succeeds at more than accommodating experience. Its models succeed at anticipating facts not used in the construction of the models. While creationism can easily accommodate the facts, it is not very successful in anticipating new facts in the required sense (there are some small exceptions to this, so it is a matter of degree). Note 1: This gets around the objection to argument 2 because a model of the form {D, if D then O} will not predict a new observation O'. One can merely add a new auxiliary assumption "if D then O'" in order to accommodate the new fact. Note 2: The independent testability of auxiliary assumptions (in argument 3) arises when the same auxiliary assumptions enter into other models. E.g., the auxiliary assumption that Madagascar separated from Africa at the certain point in geological history is also used in geological models, and gains independent support from them. This is also an example of unification (though not of theory unification). Note 3: Theory unification aids in the anticipation of novel facts because it allows for the extension of a model constructed in one domain of explanation to another. Note 4: My criterion is very close to Lakatos s criterion (a research programme is scientific if and only if it is theoretically progressive) since theoretically progressive comes down to making novel predictions. Clarification: It is important that anticipation, or prediction, of novel facts does not have to be prediction of the future. It is unfair to count only a prediction of the future course of evolution as the only thing that will count as prediction in evolutionary theory. It should also be allowed that predictions do not have to be strictly deductive consequences. It is enough that they fit the model well. Remark 1: Argument 4 captures, I think, all the virtues of argument 3, except that it is clearer that prediction is central to the purpose of science in its pursuit of knowledge. (3 of 4) [ :09:24]

38 Creationism Remark 2: In order to successfully apply Argument 4, we need to argue that Darwin s theory of evolution has made successful predictions. Here I would appeal to the example of protein homologies as a prime example. (4 of 4) [ :09:24]

39 Vision The Psychology of Vision Last modified on Monday, October 19, 1998, by Malcolm R. Forster The Astonishing Hypothesis That consciousness is nothing more than a "bunch of neurons firing in the brain" Three reason for surprise a. Reluctant to accept that a complex system can be explained by the behavior of its parts and the interactions between them. b. How can you reduce something subjective, like our vivid experiences of red, to something objective, like neural firings? Support: Does not rule out the existence of neural correlates. c. How can the reductionist thesis explain the existence of free will? Answer: Our free will may only appear to be free. Questions Arising from the Psychology of Vision A Metaphysical Question 1. Is consciousness anything more than a "bunch of neurons firing in the brain"? Support for the astonishing hypothesis: a. Reductionism cannot work; ignores that reduction is a dynamic interactive process. b. Consciousness as a substance is a category mistake. Gilbert Ryle ( ) and the ghost in the machine. E.g., "N. G. gives me the creeps" does not imply the existence of the creeps. "Which building is the university" does not wrongly imply that the university exists, but it does make a mistake about the kind of category to which universities belong. "It has crossed my mind" does is not mistaken about the existence of minds, but does suggest that minds are in the same category as material things, though different in kind (dualism). Hence arises the mind-body problems concerning how these two substances interact, how do they exchange energy, and so on. Ryle thought that dualism arises from a category mistake, similar to the mistake of thinking that there is such a thing as the creeps that N. G. gives me. Philosophical Questions about the Science (1 of 4) [ :09:46]

40 Vision 1. Can the study of consciousness be reduced to neurophysiology? 2. How can one study consciousness in a scientific manner? 3. Does the fact that neurophysiological experiments are done only on anesthetized animals limit the scientific study of consciousness? 4. Can consciousness be studied by introspection? Too subjective? Not testable, or falsifiable? 5. Or is the use of some introspective evidence unavoidable? 6. Is there a theory in this science? Are there hard core assumptions in Lakatos s sense? Philosophy of Science Questions that might be answered by the Science 1. What is observation? 2. Is observation theory-laden? 3. Is observation always a reliable source of information? 4. Is observation objective? Or are there biases that can be built into the observation? (Do we see what we expect to see?) Scientific Questions 1. Experiments show how different pieces of information are fed into the visual system. But how are these piece put together again to produce a single visual experience, or perception? Is there an analogy between the way that information is processed in science and the way that information is processed by the visual system? Seeing is Believing? Popular Misconceptions about Seeing: 1. Why should we study something so effortless? 2. We want to cure something when it s not working, but very few scientists bother asking how my brain works when I see something. At the root of this misconception is the photographic account of seeing: The Photographic Account of Seeing: Since the eye works like a camera, seeing is similar to taking photographs. Therefore, the mind (or the brain) is like a photographic film. Vision depends on: (2 of 4) [ :09:46]

41 Vision 1. What is there when you open your eyes (how can it depend on what is not there!). 2. The physical constitution of the observer. 3. The relative position of the observer and the observed, and the environment (lighting, fogginess, and so on). 4. Nothing else. Consequences of the Photographic Account of Seeing: 1. You are not easily deceived by your visual system. "Seeing is believing." Provided that vision is not impaired, it is a reliable source of knowledge about the external world. 2. Vision is not ambiguous in any way. We all see the same things in the same environment. Vision is not subjective, and not laden with prior expectations (we don t see what we want to see). 3. The mind is passive in observation. The mind does not construct what we see. The Fallacies of the Photographic Account of Seeing: 1. You are easily deceived by your visual system. 2. The visual information provided by your eyes can be ambiguous. 3. Seeing is a constructive (active) process. 1. You are easily deceived by your visual system. a. Side vision is blurry. We have the illusion of seeing clearly everywhere because we move our eyes easily and frequently. b. Gray on a background gradient. c. Kanisza s triangle, illusory contours. d. The Müller-Lyer illusion 2. Visual system can be ambiguous. a. Different apparently square shapes produce the same 2D projections. b. Monocular depth vision. c. Necker s triangle. 3. Seeing is a constructive (active) process. a. Kanisza s triangle. b. Blind spot. (3 of 4) [ :09:46]

42 Vision Conclusion: The photographic account does not work because, roughly speaking, it would imply that your television can see. You cannot wire up your TV to sound an alarm each time a dog appears on the screen. Still less, could it ever tell the difference between a dog and a painting of a dog. It only records sequences of colored dots. It cannot interpret or understand what they mean. The Homunculus Theory of Seeing: Amend the photographic account slightly by supposing that there is some central "inner" intelligence that monitors and interprets the photographic record of the visual system. This can explain away all the fallacies of the photographic account. Crick s astonishing hypothesis is that "it s all done by neurons", so that neither the homunculus, nor our consciousness, is needed to explain vision. But how can neurons do things as if they were done by a homunculus? (4 of 4) [ :09:46]

43 Values Values Is Science Value-Free? Definition: Value-laden statements make reference to something being good or bad in some way, or are biased by the someone's judgment of what is good or bad. Value-free statements about the world contain no reference to what is good or bad, nor are they influenced by anyone's judgments of what is good or bad in any sense. Thesis 1: Science is a source of objective, value-free, facts about the world. Science has nothing to do with values, either in the statement of its theories, or in the methods it uses to obtain those theories. Objection: 1. All intentional actions are driven by values and beliefs (as modern decision theory tells us). 2. Therefore, all intentional actions of scientists, including the acceptance or rejection of theories, are driven by values. 3. Therefore all of science is value-laden. In light of this objection, perhaps there is a way of weakening the thesis to make it acceptable? Perhaps we can make a distinction between "objective" values and "subjective" values, and make the claim that science is free of subjective values? Definition 1: Values, like truth, approximate truth, closeness to the truth, predictive accuracy, or fit with data, simplicity, unification, or explanatory power, are values that are constitutive of science. These are also called cognitive values. Cognitive values are generally related or thought to be indicators of truth. Definition 2: Norms, preferences, beliefs, and interests that are unrelated to cognitive values of science are non-cognitive values, or contextual values (by Longino). They are called this because, unlike cognitive values, they tend to vary from one scientific context to another. E.g., preference for a theory based on the gender or race of its author. However, contextual values may be less obnoxious, like preference based on the scientific institution of its author, or on a sense of loyalty to one s teachers or to the scientific community to which you belong. Thesis 2: Science is a source of objective facts about the world free from the influence of contextual values. (1 of 3) [ :10:02]

44 Values Objection: Every scientist is, as a matter of fact, influenced by non-epistemic values, such as loyalty to teachers and colleagues, acceptance by peers, and so on, especially in judgments about what background theory to accept. We seemed to have reached the conclusion that science is not, as it actually exists, free of non-cognitive values. Thesis 3: (The Value-Neutrality Thesis) "When contextual values intrude into science, their influence is invariably pernicious." Objection: When the contextual values refer to the shared values of scientific communities like (Longino s) recognized avenues for criticisms, shared standards, community response, and equality of intellectual authority, then the result is not necessarily bad. Is the Philosophy of Science Descriptive or Prescriptive? Problem: The sociology and history of science explicitly study the influences of social and political values in science. Yet the philosophy of science tends to steer clear of this issue. But how can the philosophy of science be about science if it tends to ignore the influence of noncognitive values? A common response at this point is to chance the thesis from a claim about the way science is to a claim about the way that science should be? (I don't happen to believe that this response is satisfactory.) Terminology: A description of science is a statement about the way that science is, whereas a prescription for science is a statement about the way that science should be, or ought to be conducted. Thesis 4: Science ought to be a source of objective facts about the world, free from the influence of non-epistemic values. Objections: As a prescription of science, Thesis 3 is highly unrealistic, and impractical. It would be impossible to implement. It would be like saying that we should all grow wings and fly to work because there would be less pollution and fewer traffic accidents. If a recipe for science cannot be followed, than in what sense can we say that it should be followed? It simply sidesteps important questions about the status of scientific knowledge as it actually exists. (2 of 3) [ :10:02]

45 Values The Sociological Turn In the 1960s, after Kuhn, the following thesis was widely accepted. Thesis 5: Science is (and ought to be) a process laden with cognitive values, and noncognitive (contextual) values. Therefore: 1. It is up to the scientific community to (collectively) decide what science is bad and what science is good. "As in political revolutions, so in paradigm choice-there is no standard higher than the assent of the relevant community." (Kuhn, 1970, p.94) 2. There is nothing more to the objectivity of science beyond the inter-subjective agreement amongst scientists. 3. Science is nothing more than social psychological process, like religious or political persuasion, except that the process is constrained by scientific standards rather than religious or political values. 4. There is no objective standard of progress in science beyond that dictated by the community. "Truth is what the scientific community says it is." Thesis 5 is unobjectionable, I think. However, the conclusions drawn from it is disputed by philosophers of science (though widely accepted amongst historians and sociologists of science). This is known as the sociological turn in science studies. Next, we will look at the arguments that Kuhn put forward for these conclusions, and the objections raised by philosophers of science. (3 of 3) [ :10:02]

46 Kuhn's Structure of Scientific Revolutions Kuhn's Structure of Scientific Revolutions Last modified by Malcolm R. Forster on October 30, Kuhn s book is about scientific revolutions the grand changes in theory that take place periodically in the history of science. The choice of the word revolution is significant because it invites the analogy between scientific change and political change (e.g., the French revolution). Butterfield as a Precursor to Kuhn In scientific revolutions "of all the forms of mental activity, the most difficult to induce is the art of handling the same data as before, placing them in a new system of relations with one another by giving them a different framework " (p. 1) Scientific revolution requires a "transposition of mind." (p. 5) Aristotelian s use of auxiliary assumptions. In explaining why an arrow does not fall to the ground as soon as it s released from the bow: " the air that was being pushed or compressed in front had to rush round behind to prevent that vacuum that must never be allowed to take place." (p. 6) Kuhn's Structure of Revolutions Kuhn's view of scientific revolutions centers around his notion of a paradigm. He introduces it in the first few pages of SSR, but revamps the notion in the postscript in the light of charges of vagueness. I will use his later definition. Paradigm as Disciplinary Matrix, has 4 components: 1. Symbolic generalizations: E.g. Newton's laws of motion. (In what we call theory.) 2. Metaphysical presumptions. E.g., Atoms as "billiard balls", or light as a wave, or light as particles. (In what we call theory.) 3. Values: E.g., the accuracy of prediction (pp ), puzzle solving success, simplicity. (Not usually thought of as changing much.) 4. Exemplars: Textbook or laboratory examples that students learn. E.g., harmonic oscillator (simple pendulum), Keplerian orbits, or random mating models in population genetics. (Introduces the idea of tacit knowledge.) Remarks: a. Exemplars help introduce the notion of tacit knowledge, learned by doing science, like (1 of 7) [ :10:25]

47 Kuhn's Structure of Scientific Revolutions the ability to read x-rays, rather than applying rules), and cannot be written down or articulated. (Even logic and mathematics is an example of this.) b. Tacit knowledge is neuropsychological: "so much past experience is embodied in the neural apparatus that transforms stimuli to sensations." (p.195) Note that he is suggesting that tacit knowledge affects the way scientists see. c. (p.188) Exemplars give a theory empirical content. This makes perfect sense if exemplars are models (= theory + auxiliary assumptions), because we need auxiliary assumptions to make predictions from a theory. d. A disciplinary matrix is different from a theory not only in its inclusion of values and tacit knowledge, but also because it refers essentially to a scientific community, a sociopolitical entity, rather than an item of knowledge. Two Kinds of Science Normal Science: Science as it is practiced within a single paradigm. Models are constructed as the solutions to puzzles under the guidance of a theory, but the theory itself is not criticized or blamed for failures (e.g., Leverrier-Adams example discovery of Neptune). Revolutionary Science: The transformation from one paradigm to another. Contrasts with normal science. Normal and Revolutionary Science are Different In normal science, the theory is not questioned. In revolutionary science it is. In normal science there is cumulative progress. In revolutionary science there is not. In normal science there is no meaning variance. In revolutionary science there is. In normal science change is incremental and gradual. In revolutionary science the change is total, and relatively sudden. Contrasts with a Popperian Picture of Science Popperianism and Bayesianism assume that the same methodological principles that apply to normal science and revolutionary science. Kuhn denies this: 1. Kuhn s argues: Normal science does not aim at novelty: (1) Novelties of fact or theory (i.e., discoveries?) lead to the end of normal science. (2) Normal science does not aim at its own demise. Therefore, (3) normal science does not aim novelties of fact or theory and, when successful, finds none. It s not clear that Kuhn is right about (1). Why should a new discovery (e.g., x-rays, (2 of 7) [ :10:25]

48 Kuhn's Structure of Scientific Revolutions pulsars, radio waves, HIV virus) necessarily lead to the demise of normal science? Perhaps he should only assume that they may. Will the argument still work? 2. The falsificationist s folly is to think that the falsification of a model is also a falsification of the background theory. Anomalies (= mismatches between the current best model and observation, or between accepted models) are not sufficient. Crisis (= failure at prediction) is sufficient. E.g., Ptolemaic astronomy failed not because it could not remove anomalies, but because the anomalies, once removed, would reappear when new observations were made. 3. In normal science the theory is not tested. Even in the face of crisis, the theory is not immediately rejected one also needs a better alternative. (A leaky roof is better than no roof at all.) Here Kuhn (p. 80) points out that "science students accept theories on the authority of teacher and text, not because of evidence." But is that really the only explanation of why this is true? This one of the ways that Kuhn shifts from an internal (= non-sociological) view of science to an external (=community-based) view of science. 4. Expectations obscure our vision. Kuhn cites a psychological experiment in which subjects are shown ordinary playing cards mixed up with some anomalous cards, like a black four of hearts. The results show that subjects initially see what they expect to see (either the four of spades, or the four of hearts). Therefore, science is subjective. Relativism Scientists who work in different paradigms live in different worlds. KUHN: "...after discovering oxygen Lavoisier worked in a different world." (p.118) "after Copernicus, astronomers lived in a different world." (pp.116-7) "until that scholastic paradigm was invented, there were no pendulums, but only swinging stones, for the scientists to see. Pendulums were brought into existence by something very like a paradigm-induced gestalt switch." (p.120) We could add our own examples. After evolutionary theory, human beings became just another primate. After the "darkenings of the sun" were explained, they became solar eclipses. After atomic theory, water became H 2 O. And so on. Ambiguous: a. Scientists who work in different paradigms live in different psychological worlds; i.e., have different beliefs about the world. [PLAUSIBLE] b. Scientists who work in different paradigms live in different external physical worlds. [IMPLAUSIBLE] Theory-Ladeness of Observation (3 of 7) [ :10:25]

49 Kuhn's Structure of Scientific Revolutions "What scientists observe depends on what they believe." (Visual gestalt analogy) 1. No scientist can ever observe something that contradicts their theory? 2. Scientists who accept rival theories can never observe the same thing? Kuhn cites many examples: a. Galileo sees a pendulum, where Aristotle sees a (slowly) falling stone. b. "Looking at a contour map, the student sees lines on paper, the cartographer a picture of a terrain." (p.111) c. "Looking at a bubble-chamber photograph, the student sees confused and broken lines, the physicist a record of familiar subnuclear events." (p.111) d. "Looking at a bubble-chamber photograph, the student sees confused and broken lines, the physicist a record of familiar subnuclear events." (p.111) e. Herschel s discovery of Uranus, which he first thought was a star, and then a comet. Kuhn s argument for relativism: 1. Kepler s sun is at rest and Ptolemy s sun is moving. 2. Therefore, Kepler s sun cannot be the same as Ptolemy s sun 3. Therefore, the object that Kepler observes is not the same as the object that Ptolemy observes. Fallacies of Equivocation A fallacy of equivocation occurs when an argument uses an ambiguous word in two different ways. E.g., P1. We have the right to abstain from voting. P2. We should do what is right. C. Therefore, we should abstain from voting. When we eliminate the ambiguity, the argument is either invalid or unsound. P1. We are entitled to abstain from voting. P2. We should do what is correct. C. Therefore, we should abstain from voting. [INVALID] (4 of 7) [ :10:25]

50 Kuhn's Structure of Scientific Revolutions P1. We are entitled to abstain from voting. P2. We should do what we are entitled to do. [FALSE] C. Therefore, we should abstain from voting. P1. It is correct to abstain from voting. [FALSE] P2. We should do what is correct. C. Therefore, we should abstain from voting. In Kuhn s argument, there is an equivocation between what Kepler and Ptolemy believe about the sun, and the object of their beliefs. 1. Kepler believe that sun is at rest and Ptolemy believes that the sun is moving. 2. Therefore, the object of Kepler s beliefs and the object of Ptolemy s beliefs cannot be the same object. [INVALID] 1. The object of Kepler s beliefs is at rest while the object of Ptolemy s beliefs is moving. [FALSE] 2. Therefore, the object of Kepler s beliefs and the object of Ptolemy s beliefs cannot be the same. Meaning Variance Incommensurability: "The normal-scientific tradition that emerges from a scientific revolution is not only incompatible but often actually incommensurable with that which has gone before." (p.103) Incommensurability is vague in at least two dimensions: (a) Are values the same across revolutions? (b) (Meaning variance) Are all terms of one theory translatable into the other? The Slippery Slope to Relativism A. Newtonian mass is not the same thing as Einsteinian mass. B. If Einstein s theory is true, then Newtonian mass does not exist. A. It is extremely unlikely that Einstein s theory is true, so Einsteinian mass does not exist either. B. No scientific theory refers to anything real. (5 of 7) [ :10:25]

51 Kuhn's Structure of Scientific Revolutions C. The real world is of no concern to science. D. Relativism. "The world of the scientist is a world given and structured by theory, and as theory changes, so does the scientist s world." (From Musgrave 1979, p. 338) Musgrave recommends that one avoid stepping onto the slope in the first place. Kuhn is not so careful. There is no such thing as a neutral observation language Kuhn refuses to accept the reasonable idea that Aristotle and Galileo agree on the facts (described without reference to the notion of a pendulum ) but interpret them differently. "How could it be so in the absence of fixed data for the scientist to interpret?" (p. 122) This is perhaps Kuhn s most radical departure from traditional philosophy of science. If, for any two competing theories, there were no neutral observation language, then their fit with the data could not be compared because there would be no such thing as the data. There would be no common currency of comparison at any level. But why couldn t Aristotle and Galileo agree on many things, like whether one stone dropped from a tower hits the ground within one second of the other. Why can t Ptolemy and Copernicus agree on whether there was a solar eclipse today? Kuhn does not say. His argument seems to go like this: There is no language of observation that is neutral for all theories. Therefore, there is no language of observation that is neutral between any two theories. The conclusion does not follow the premise. Eclipse, stone, second may be a theory-laden terms, but they are not laden with the theories under contention. Kuhn is confusing the idea of an theory-neutral observation language that neutral between two competing theories. For example, Carbon-14 dating is theory-laden, but it is neutral between competing archaeological theories. NOTE: If models from two different traditions are incompatible because they make incompatible predictions. Then they cannot be incommensurable in all their terms. Proof: Let A and B be two models in different theories, and suppose that A O and B not-o, where O is a prediction. Then the terms in O are in A and in B, and they mean the same in both contexts. How communication is restored by conversion to the new paradigm, according to Kuhn. His answer is surprisingly conventional: a) the claim to have solved crisis-provoking problems, b) the claim to novel predictions, and c) the claim to simplicity. However, note his emphasis on claims, for Kuhn is thinking of the process as a sociopolitical one, rather than a (6 of 7) [ :10:25]

52 Kuhn's Structure of Scientific Revolutions process of logic. Kuhn s theory of science is a description rather than a prescription of science. "Some critics claim that I am confusing description with prescription, violating the timehonored philosophical theorem: Is cannot imply ought. " (p.207) Kuhn s claims that his theory is prescriptive, or normative, and this is warranted because scientists "behave as the theory says they should." His reply is hard to fathom. He does not say what goal scientists maximize by behaving as they do, or why that is the best way of maximizing such goals. The only difference between, say, creationists and evolutionists lies in the community standards they adopt. He provides no insights into why one community standard is better than the other, and in what respect. The sociological turn One of the most serious influences of Kuhn s book has been to provide support for those who want to turn away from the philosophy of science towards the sociology and psychology of scientific communities. One argument goes like this (ask the class to evaluate the argument): 1. Either the philosophy of science is the right way to study science, or the sociology is the right way to study science, but not both. 2. Kuhn showed that the philosophy of science is wrong way to study science. 3. Therefore, the sociology of science is the right way to study science. Just because an argument is bad, does not mean its conclusion is false. There is noting wrong with studying the sociology or the psychology of scientific communities. But there are some questions it does not address. For example, Kuhn is unable to explain the sense in which his theory of science describes what scientists should do, rather than merely what they actually do. It s not that philosophers are denying that scientists are doing things right. The point is that any such claim must be assessed relative to a particular set of goals (e.g. truth), and it should be explained how their practice leads to such goals. Sociologists do none of this, so there is role for philosophers of science. (7 of 7) [ :10:25]

53 Objectivity The Objectivity of Science Philosophy versus Social Psychology In my view, the philosophy of science is not a branch of psychology (although many post-kuhnian philosophers of science who have taken the sociological turn think otherwise). The reference to "goals of science" is not a reference to the intentions of scientists in doing science. Science may achieve a degree of truth with or without scientists intending that that is what they are doing. An Analogy: People may have moral beliefs against extramarital sex. Their behavior may be caused by a belief in a moral goal, but the behavior may achieve many other things, like a lower incidence of venereal disease, higher stability of family units and so on. Likewise, scientists may be solely concerned with personal fame, and unconcerned with the truth of theories (not that I believe that). Yet, science might still make progress towards the truth even if it were unintended. Philosophy of science is about the achievements of science, and how they come about, rather than the psychology of scientists. I mention this, because I often see philosophers of science appealing uncritically to the opinions of scientists in order to support a view about science. Means versus Ends Definition 1: Goals, or ends, refer to the achievements, or potential achievements of science. Goals like truth, approximate truth, closeness to the truth, empirical adequacy, predictive accuracy are called epistemic goals. Social, moral, political, and pragmatic goals are non-epistemic goals. Definition 2: Means, methods, or criteria refer to what scientists actually do when they do science, or to the values they use to judge the achievement or degree of achievement of epistemic goals. Means can only refer to the features of scientific theories or models that scientists can see. For example, "Choose the model that is closest to the truth" is not a means because scientists cannot see that a model or theory is true. "Choose the model that best fits the background data" is a genuine means because scientists can see which model best fits the background data. Means are not valued for their own sake, but only as a means towards a goal. In talking about cognitive values, goals and means to goals get mixed up together. Traditional philosophy of science is primarily concerned with the relationship between methods and epistemic goals. But it is impossible to study this relationship if the two things are not clearly separated. For example, is simplicity a goal of science, or is it a means to a goal of science (and remember this is not a question of what scientists believe). Simplicity, as such, is not an epistemic goal (it does not mention truth), and it is only an epistemic, or cognitive value in so much as it does indicate the achievement of some epistemic goal. MEANS ENDS lead to (1 of 3) [ :10:41]

54 Objectivity methods rules of inference decision rules selection criteria approximate truth closeness to the truth predictive accuracy empirical adequacy Example: Under what circumstances does choosing the best fitting model lead to the acceptance of hypotheses that are closer to the truth? The benefits of such means-goal analysis might be: 1. Better Understanding of Science: If successful, this would be useful in understanding how science works, for it could tell us to the extent that social and political factors are "getting in the way" or "helping promote" progress towards the truth. That is, it would play a role in explaining the success of science (to the extent that it is successful) rather than merely describing the way science is. 2. Better Prescription for Science: A knowledge of the effectiveness of scientific methods would also help in prescribing how the improve science. Although, at best, it would enable us to estimate the gains and losses from different science policies (e.g., how should scientists or potential scientists be trained?). It would not tell us how to trade off epistemic gains against social or political costs of a given policy, and therefore would not tell us what science ought to be. But it would form an important component of a normative prescription for science one that is not provided solely by the history or sociology of science. Note: This agenda for the philosophy of science is very ambitious, and it is true that it has not made much progress in fulfilling this role to date. It is a very immature discipline at the moment. My argument is only that there is a role here that is not filled by the history or sociology of science. The Hard Problems in the Philosophy of Science Puzzle: If a philosophy of science mentions only cognitive values, and all science is laden with noncognitive values, and the philosophy of science is not a prescription of science, then what is the philosophy of science about? Answer in Brief: The philosophy of science also studies the effectiveness of scientific methods and techniques in bringing about epistemic goals. For example, it might tell us when, and under what circumstances, a naïve empiricist methodology (of choosing the best fitting model) is better than a method of trading off simplicity and fit in obtaining better approximations to the truth. This is to study science as a means to the goal of truth, irrespective of what scientists believe is achieved by their methods, or their psychological reasons for their decisions. It is an objective study of science is a stronger sense than studying the inter-subjective agreements of community beliefs (which is the main concern of philosophers of science who took the sociological turn ). Consider any putative goal of science, whether it be the truth of theories, the predictive accuracy of models, or the economic prosperity of the United States. Call the goal X. Now consider two, or more, ways or (2 of 3) [ :10:41]

55 Objectivity methods of doing science. Call them A and B. It is now an objective question whether A is more effective than B in achieving X. Definition: Operational questions are questions about the relative effectiveness of ways or methods of doing science in achieving a goal X. Operational questions have nothing to do with what scientists believe. Operational questions are hard questions. Operational theses are answers to operational questions. For example, "A is more effective than B in achieving X" is a typical operational thesis on my definition. Such theses are weakly normative in the sense that they imply ought statements when coupled with goal statements. For example, if one could establish that A is more effective than B in achieving X, and X is the goal of science, then it would follow that one ought to adopt A as the methodology of science. There is a huge difference between social psychological questions and operational questions, although the distinction is not always clear. For example, compare the following normative arguments: 1. The scientific community agrees that method A is better than method B at achieving X. X is the goal of the community. Therefore, the scientific community ought to adopt method A. 2. Method A is better than method B at achieving X. X is the goal of the community. Therefore, the scientific community ought to adopt method A. There is an important difference between these arguments. The first provides a subjective justification for using method A, while the second provides an objective justification for the same action, or policy. The operational claim in (2) is harder to establish, but it has stronger implications. That is an important tradeoff. Notes: 1. Scientists themselves are not always particularly well qualified to answer operational questions. An analogy, try asking an someone how to walk (other than a physical therapist, or someone who had to relearn to walk as an adult). 2. On this characterization, the philosophy of science is neutral to the sociology of science and to, for example, feminist critiques of science. It may well turn out that feminist ways of doing science are more effective in achieving epistemic goals (as Sandra Harding suggests), or that the elimination of bias has beneficial effects (as in the examples that Kathleen Okruhlik describes). 3. Non-cognitive values may enter into the definition of the methods, and they may affect the beliefs about the effectiveness of methods, but they do not affect the effectiveness of the methods themselves. In that sense, non-cognitive values do not enter into the philosophy of science. (3 of 3) [ :10:41]

56 Verisimilitude The Problem of Verisimilitude The Problem of Progress Popper (1963) noted that there is no general agreement on the answers to two very basic questions: (A) Can we specify what scientific progress consists of? (B) Can we show that science has actually made progress? One quick answer to (A) is that (1) Science aims at true theories, and that progress consists of the fulfillment of this aim. In answer to (B), we should add: (2) Science has made progress in meeting this aim. The problem now arises when we add a third plausible statement to the first two: (3) Scientific theories have all been false. In the history of planetary astronomy for example, Ptolemy s geocentric theory is false, Copernicus s version of the heliocentric theory is false, Kepler s laws are false, Newtonian gravitational theory is false. It would be naive to suppose that Einstein s general theory of relativity is true. This conflict is "the problem of progress." The Problem of Verisimilitude The famous problem of verisimilitude flows from this (Musgrave, unpublished): Realists... seem forced to give up either their belief in progress or their belief in the falsehood of all extant scientific theory. I say seemed forced because Popper is a realist who wants to give up neither of them. Popper has the radical idea that the conflict between (1), (2), and (3) is only an apparent one, that progress with respect to truth is possible through a succession of falsehoods because one false theory can be closer to the truth than another. In this way Popper discovered the (two-fold) problem of verisimilitude; (A*) Can we explain how one theory can be closer to the truth, or has greater verisimilitude than another? (B*) Can we show that scientific change has sometimes led to theories which are closer to the truth than their predecessors? Note: Closeness to the truth is not the same as the probability of truth. A simple example shows this: A: The time on this stopped watch is correct to within one minute. B: The time of my watch (which is 2 minutes fast) is accurate to within one minute. Both hypotheses are false. But B is closer to the truth than (1 of 8) [ :11:48]

57 Verisimilitude A. But A is more probable than B, because the probability of A being true, though small, is non-zero. But the probability of my watch being accurate to within one minute, given what we know about my watch, is zero. Popper's Definition of Verisimilitude So, how should we define verisimilitude? Popper (1963) defined verisimilitude as follows: DEFINITION: Theory A is closer to the truth than theory B if and only if (i) all the true consequences of B are true consequences of A, (ii) all the false consequences of A are consequences of B, and (iii) either and some true consequences of A are not consequences of B or some false consequences of B are not consequences of A. Note: Popper s definition allows that there are false theories A and B such that neither is closer to the truth than the other. A fatal flaw in this definition was detected independently by Tichý (1974) and Miller (1974). They showed that, according to Popper s definition, for any false theories A and B neither is closer to the truth than any other. This is a fatal flaw because the philosophical motivation behind Popper s definition was to solve the problem of progress by showing that it is possible that some false theories are closer to the truth than other false theories. The Weather Example Suppose that the weather outside is hot (h) or cold (~h), rainy (r) or dry (~r), windy (w) or calm (~w). Suppose that the truth is that it s hot, rainy, and windy (h & r & w). Now consider two competing theories about the weather. A says that its cold, rainy and windy (~h &r & w) and B says that it s cold, dry and calm (~h &~r & ~w). Both theories are false, but intuitively, one might think that A is closer to the truth than B. But Popper s definition does not yield that result. First, B has some true consequences that A does not have. For example, B implies that A is false, but A does not A does not imply that A is false. Second, A has some false consequences that B does not have. For example, A implies A, which is false, while B does not imply A. More generally, it is possible to prove that no false theory is closer to the truth than any other false theory by Popper s definition. Therefore Popper s definition cannot solve the problem of progress because it requires that some false theories are closer to the truth than other false theories. Nobody noticed the defects in Popper s definition for over 10 years, and so it is not a trivial result. The best way I know of "seeing" the result clearly is to represent the theories in terms of possible world diagrams. Possible World Diagrams (2 of 8) [ :11:48]

58 Verisimilitude Figure 1: Each point inside the rectangle represents a possible world. There are 8 kinds of possible worlds that can be described in terms of h, r, and w. Any proposition expressible in the language is represented by the set of possible worlds in which the proposition is true. Note that the three simple propositions, h, r, and w are each true within four numbered regions. The conjunction of any two of them is true within two numbered regions, and the conjunction of three of them is true within a single numbered region. Figure 2: The theories T, A, and B are represented by the set of possible worlds for which those propositions are true. Since they are conjunctions of three simple propositions, they are each represented by the single numbered regions 1, 2, and 8, respectively. Logical deduction, or logical entailment, is represented by the subset relation, because, by definition, one statement entails another if and only if the truth of the first guarantees the truth of the second. Therefore, for example, T Þ h, T Þ r, and T Þ w, as we would expect. Figure 3: The proposition that the weather is minnesotan is represented by the shaded region. Notice that it is the combination of four numbered regions, 1, 4, 7, and 8. Each of h, r, and w is also represented by four numbered regions. Remember that logical deduction, or logical entailment, is represented by the subset relation. Thus, B Þ m because if the actual world were in region 8, then it would also be in the shaded region representing m. Note also that T Þ m, but A does not entail m (3 of 8) [ :11:48]

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