an invitation to philosophy of science

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1 an invitation to philosophy of science petri ylikoski the structure of the lecture 2 Part I: Introducing philosophy of science with very short examples The aims of science Scientific methodology Nature of scientific knowledge Ontology of science Part II: An example of philosophy of science in action What does the claim that observation is theory-laden mean?

2 3 what is philosophy? The aim of philosophy, abstractly formulated, is to understand how things in the broadest possible sense of the term hang together in the broadest possible sense of the term. (Wilfrid Sellars, 1963) The word philosophy means the love of wisdom, but what philosophers really love is reasoning. (Robert Nozick, 1993) What there is (ontology)? How can we know about it (epistemology)? What should we do (ethics)? 4 philosophy as a discipline A field rather than a doctrine shared problems rather than accepted theories accumulation of problems and arguments, not philosophical facts the identity of philosophy is constantly contested the issues are conceptual, empirical/scientific results might be relevant indirectly Philosophy of science as a borderline between science and philosophy Meta-reflection about science! descriptive questions (what is the nature of the sciences?)! prescriptive questions (how the sciences should be conducted?)

3 the aims of science (axiology) 5 Cognitive aims Epistemic significance (which questions to ask?)! which facts and phenomena should be objects of description, prediction and explanation? Epistemic values (what qualities the answers should have?)! truth, accuracy, explanatory power, theoretical unification, simplicity, fruitfulness, Social aims The role(s) of science in society! Enlightenment, human health and happiness, economic growth, national prestige, legitimation or critique, 6 what is the aim of science? Instrumentalism To save the phenomena Science aims at prediction and technological application Theories organize our knowledge of observable phenomena, but do not tell things about things behind them Everything beyond this belongs to metaphysics and theology Realism Cutting nature at its joints Science aims primarily at explanatory understanding of phenomena and prediction and technological applicability are just bonuses The value of knowledge is not just instrumental, it has value in itself

4 methods of the sciences (methodology) 7 The concepts and principles used in the process of scientific research distinct from particular research methods The general characteristics research process Scientific discovery, heuristics Theory and concept formation Observation, experiment, prediction Induction, abduction, statistical inference Peer review, publication Justification of scientific claims Evidence, confirmation, testing Demarcation! Scientific argumentation 8 fallibilism Charles S. Peirce ( ) Scientific knowledge (or its justification) is never absolutely certain All knowledge is provisional, and could turn out to be false Does not mean that all knowledge is equally uncertain or that we should accept general scepticism about all knowledge Scientific research as self-correcting process Critical scientific debate and empirical testing weed out unreliable claims and replaces them with more trustworthy

5 the nature of scientific knowledge 9 What is the form of scientific knowledge What are theories, models? The place of taxonomies in science? What is the role of tacit knowledge? How scientific knowledge changes How new methods and theories begin and how they develop? How does scientific knowledge grow?! are there scientific revolutions?; what are the units of change? The relations between sciences How to understand the unity of science?! what is reduction, reductionism?! what is interdisciplinarity? 10 what is reductionism? Often a number of different ideas are treated as one the job for philosopher is to sort them out In reductionism one can distinguish four different ideas that can be accepted or rejected independently 1. Program to link the sciences to each other Aims to build systematic interrelations between the sciences! some sciences are constraints for others an asymmetric relevance Critics: an alternative would be to talk about co-evolution of scientific fields - the influence could go both directions 2. The idea of unity via reduction The ultimate aim of science is an unified theoretical structure which is achieved via theory-reduction between fields Critics: assumes problematic notion of theory unity can be achieved also by other means

6 11 more forms of reductionism 3. A heuristic for research The idea that working with a simplified hypothesis is the most fertile way forward in research! by showing how the simple idea is wrong one learns about the complexity Critics: this might be a fruitful heuristic, but is it the only one? 4. An ontological doctrine The idea that theories at the macro-level are somehow suspect, so either! Theories and explanations should always be formulated at the lower level! Macro-level theories should always have explicit micro-foundations Critics: the metaphysical arguments for these suggestions are confused and unjustified 12 ontology of science What is the nature of general categories and concepts used in the sciences? law of nature, natural kind, causation, probability, indeterminism, What kind of entities scientific theories are talking about? field, force, species, gene, intentionality, group, how the concepts should be defined; how they could be fitted with concepts in other theories; What kind of general picture of the world makes sense? realism, materialism, emergence,

7 13 causation and manipulation Causation as an agency notion bringing about, predicting and preventing things C causes E, if we can bring about E by bringing about C Cannot serve as a reductive analysis of causation, because the bringing about is already a causal notion.! All proposed reductive analyses have failed, maybe we should be satisfied with descriptive analysis Goes nicely with the idea that controlled experiments are the best way to achieve causal knowledge! A natural way to understand the difference between a real causal relation and a mere correlation. The above gives a root meaning that can be extended to cases where the manipulation is only hypothetical (but the dependence between C and E is similar)! We don t want to be too anthropocentric theory-ladenness of observation 14 A bit of historical background for the philosophical debate Logical positivists made a sharp distinction between theoretical and observational terms and built much of their philosophy on it Thomas Kuhn and N. R. Hanson challenged this distinction (in 1960 s) by claiming that observation is theory-laden The ambiguity of this notion is still with us The term has been used to make quite different points the conceptual nature of observation the role of expectation in observing the skillful nature of observation the Duhem-Quine -thesis the empirical underdetermination of theories

1) the influence of concepts on sense perception 15 What we observe, is

Hanson: Did Kepler and Tycho [Brahe] see the same thing in the east at

and Seeing that It is still controversial how much our theoretical

perception is concept-laden (or even influenced by our beliefs) how much

8 1) the influence of concepts on sense perception 15 What we observe, is conceptually influenced N. R. Hanson: Did Kepler and Tycho [Brahe] see the same thing in the east at dawn?! can be understood literally or metaphorically Seeing as something and Seeing that It is still controversial how much our theoretical beliefs influence what we can see The big issue: even if sense perception is concept-laden (or even influenced by our beliefs) how much it matters? the increasing use of instruments in scientific observation what matters is public data, not subjective experiences 16

17 2) the role of expectations in research 18 Theoretical

not looking for Biases in perception, memory or reporting!

The influence on attention can only be cured (partially) by an open

9 17 2) the role of expectations in research 18 Theoretical expectations can guide attention and making of observations We mostly find what we are looking for! Ignoring (intentionally or non-intentionally) things that one is not looking for Biases in perception, memory or reporting! Some of these biases can be avoided by good design of research! The influence on attention can only be cured (partially) by an open mind Theoretical expectations can make anomalous observations salient (without expectations them might not seem significant)

10 3) observation and experimentation as skills 19 Earlier experience and training influence the ability to make observations Tacit knowledge (Michael Polanyi) Evaluation of experiment also involves evaluation of an experimenter! the capabilities of the experimenter! the trustworthiness of the experimenter Harry Collins: experimenter s regress in frontier science: The only way to tell who is a competent experimenter is the right result What happens when there is a dispute about the right result of the experiment?! is the result due to experimenter s incompetence or reality of the phenomenon?! how the circle is broken? 20 4) duhem-quine -thesis Pierre Duhem s thesis (1905) The theory and its auxiliary hypotheses face the observations as a whole. Observations alone cannot tell what has to be given up or revised in the case of false prediction. Observations alone cannot falsify a hypothesis. Crucial experiments (in a strict sense) are impossible. Scientists need bon sens to make a judgment but what is that? W. V. O. Quine s thesis (1952) Any statement can be held true come what may, if we make drastic enough adjustments elsewhere in the system. More radical thesis than Duhem s The claim is about what is logically possible, not what is sensible or prudent Raises the issue whether there are rational means to solve scientific disputes

11 what the observation means illustration from csi 21 We have found organic matter from the crime scene We have found human DNA from the crime scene More interesting and stronger claim The sample of DNA from the crime scene matches X (or his relatives) X has been on the crime scene X has been a participant in the crime Less interpretive assumptions and more secure claim X is quilty 5) empirical underdetermination 22 The possibility that two (or more) theories fits equally well with empirical evidence The temporary problem: Currently the empirical evidence cannot decide between two (or more) competing theories! a possible problem in real science! the solution: more evidence, preferably about issues about which the theories disagree The eternal problem: Even if we have all the possible empirical evidence, we cannot decide between competing theories (empirical equivalence.)! the end of science perspective! logical possibility that there is an infinite number of empirically equivalent theories

the relevance of eternal problem 23 Relevant for the debate about scientific realism constructive empiricism: as there is no scientific (empirical) way of deciding between these theories, we should

12 the relevance of eternal problem 23 Relevant for the debate about scientific realism constructive empiricism: as there is no scientific (empirical) way of deciding between these theories, we should only believe that even our best theories are just empirically adequate, not that they are literally true. The big questions: Are the alternatives really plausible (or just ad hoc logical constructs)? Does it matter that the theories differ in some of their nonempirical claims? What about other ways of justifying the choice between competing theories! metaphysical preferences; simplicity; explanatory power; theoretical unification, etc. rethinking observation: data and phenomenon 24 James Woodward & James Bogen Phenomena stable and replicable effects or processes, that are potential objects of explanation and prediction for a general scientific theories provides evidence for a theory Data observational evidence for claims about phenomenon produced by observation and experimentation Theory explains, predicts Data Phenome non is evidence for

13 25 from data to phenomenon Data is often a result of a complex and idiosyncratic causal processes, which involve various factors. usually it is impossible to derive or systematically explain all the details of the data. The theory of data production is separate from the theory about the phenomenon. It is concerned with: the causal processes that produce the data; the working mechanisms of the instruments; the reliability of the procedures and instruments; the methods used in the processing of data The same phenomenon can be detected by using different experimental/observational set-ups There is not much point in replicating data more relevant is the production of better or alternative data about the same phenomenon 26 further reading Bird 1998: Philosophy of Science. McGill-Queens University Press. Godfrey-Smith 2003: Theory and Reality. An Introduction to the Philosophy of Science. University of Chicago Press. Hacking 1983: Representing and Intervening. Cambridge University Press. Kiikeri & Ylikoski 2004: Tiede tutkimuskohteena. Filosofinen johdatus tieteentutkimukseen. Gaudeamus. Niiniluoto Johdatus tieteenfilosofiaan. Käsitteen- ja teorianmuodostus. Otava. Niiniluoto 1984: Tieteellinen päättely ja selittäminen. Otava. Woodward 2003: Making Things Happen. A Theory of Causal Explanation. Oxford University Press. Ziman 2000: Real Science. What it is, and what it means. Cambridge University Press.

Cognitive domain: Comprehension Answer location: Elements of Empiricism Question type: MC

Cognitive domain: Comprehension Answer location: Elements of Empiricism Question type: MC Chapter 2 1. Knowledge that is evaluative, value laden, and concerned with prescribing what ought to be is known as knowledge. *a. Normative b. Nonnormative c. Probabilistic d. Nonprobabilistic. 2. Most