What Is Science?

(and What Is a Scientific Theory?)

(and Readings on Philosophy of Science)

"The most remarkable discovery made by scientists is science itself. The discovery must be compared in importance with the invention of cave-painting and of writing. Like these earlier human creations, sicnece is an attempt to control our surroundings by entering into them and understanding them from inside. and like them, science has surely made a critical step in human development which cannot be reversed. We cannot conceive a future society without science." —Jacob Bronowski, Scientific American (1958)

1. Quine, Willard van Orman (1951), "Two Dogmas of Empiricism" Philosophical Review 60: 20-43.

2. Kemeny, John G. (1959), A Philosopher Looks at Science [ Intro & Chs.5,10 in PDF] (Princeton: D. van Nostrand).
   • Kemeny's version of the scientific method as a non-halting algorithm

3. Popper, Karl R. (1953), "Science: Conjectures and Refutations", from his Conjectures and Refutations: The Growth of Scientific Knowledge (New York: Harper & Row, 1962).
   

4. Popper, Karl R. (1959), The Logic of Scientific Discovery (New York: Harper & Row).

5. Wigner, Eugene (1960), "The Unreasonable Effectiveness of Mathematics in the Natural Sciences", Communications in Pure and Applied Mathematics 13(1) (February).
   • html
   • pdf
     An interesting reply from a computer scientist:
     
     • Hamming, R.W. (1980), "The Unreasonable Effectiveness of Mathematics", American Mathematical Monthly 87(2) (February)
       • original version (JSTOR.org)
       • html

6. Kuhn, Thomas S. (1962) The Structure of Scientific Revolutions (Chicago: University of Chicago Press).
   • "Ch. IX: The Nature and Necessity of Scientific Revolutions"

   • For an encyclopedia article on scientific revolutions by a UB PHI professor, see:
     • Corcoran, John (forthcoming), "Scientific Revolutions", Encyclopedia of American Philosophy.

   • Weinberger, David (2012), "Shift Happens", The Chronicle [of Higher Education] Review (27 April): B6–B9.

7. Hempel, Carl G. (1966), Philosophy of Natural Science (Englewood Cliffs, NJ: Prentice-Hall).
   • "Scope and Aim of this Book" (on empirical vs. non-empirical sciences)

8. Kyburg, Henry E., Jr. (1968), Philosophy of Science: A Formal Approach (New York: Macmillan).
   • Ch.1: The Concept of a Formal System

9. Ziman, John M. (1968), "What Is Science?", from John M. Ziman, Science Is Public Knowledge (Cambridge, UK: Cambridge University Press).
   • Reprinted in:
     Michalos, Alex C. (ed.) (1974), Philosophical Problems of Science and Technology (Boston: Allyn & Bacon): 1-27.

10. Thagard, Paul R. (1978), "Why Astrology Is a Pseudoscience", PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association: 223-234.

11. Arden, Bruce W. (1980), "COSERS Overview" [PDF], in Bruce W. Arden (ed.), What Can Be Automated? The Computer Science and Engineering Research Study (COSERS) (Cambridge, MA: MIT Press), Ch. 1, pp. 1-31.
    • See esp. the section titled "About Names and Labels" (pp. 5-7).

12. Salmon, Wesley C. (1984), Scientific Explanation and the Causal Structure of the World (Princeton: Princeton University Press).
    • "Ch.1. Scientific Explanation: Three General Conceptions"

13. Denning, Peter J.; Comer, Douglas E.; Gries, David; Mulder, Michael C.; Tucker, Allen; Turner, A. Joe; & Young, Paul R. (1989), "Computing as a Discipline", Communications of the ACM 32(1) (January): 9-23.

14. Hartmanis, Juris, & Lin, Herbert (eds.?) (1992), "What Is Computer Science and Engineering?" [PDF], in Juris Hartmanis & Herbert Lin (eds.), Computing the Future: A Broader Agenda for Computer Science and Engineering (Washington, DC: National Academy Press), Ch. 6, pp. 163-216.

15. Abelson, Harold, & Sussman, Gerald Jay, with Sussman, Julie (1996), Structure and Interpretation of Computer Programs, "Preface to the First Edition":
    • "Underlying our approach to this subject is our conviction that "computer science" is not a science and that its significance has little to do with computers. The computer revolution is a revolution in the way we think and in the way we express what we think. The essence of this change is the emergence of what might best be called procedural epistemology -- the study of the structure of knowledge from an imperative point of view, as opposed to the more declarative point of view taken by classical mathematical subjects. Mathematics provides a framework for dealing precisely with notions of "what is." Computation provides a framework for dealing precisely with notions of "how to." "

16. Papineau, David (1996), "Philosophy of Science" [PDF], in Nicholas Bunnin & E.P. Tsui-James (eds.), The Blackwell Companion to Philosophy (Oxford: Blackwell): 290-324.

17. Simon, Herbert A. (1996), The Sciences of the Artificial, 3rd edition (Cambridge, MA: MIT Press).
    • SCI/ENGR Book Collection Q175 .S564 1996
    • "Natural science is knowledge about natural objects and phenomena. We ask whether there cannot also be "artificial" science—knowledge about artificial objects and phenomena." (p. 3.)
    • Ch. 1 ("The Natural and Artificial Worlds") has sections on the nature of understanding by simulating and on computers as artifacts, as abstract objects, and as empirical objects.

18. Rosenberg, Alex (2000), Philosophy of Science: A Contemporary Introduction (London: Routledge).

19. Okasha, Samir (2002), Philosophy of Science: A Very Short Introduction (Oxford: Oxford University Press).
    • This is the very best intro to philosophy of science.

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20. Kolak, Daniel; Hirstein, William; Mandik, Peter; & Waskan, Jonathan (2006), Cognitive Science: An Introduction to Mind and Brain (New York: Routledge).
    • "§4.4.2. The Philosophy of Science"

21. Cham, Jorge (2006), Piled Higher and Deeper, "The Scientific Method vs. The Actual Method"

22. Dyson, Freeman (2006, 19 October), "Writing Nature's Greatest Book", New York Review of Books 53(16).
    • An interesting book review that discusses some of the origins of science.
    • In particular, I suggest (that's a 4th ranking, after "required", "strongly recommended", and "recommended" :-) that you take a look at the paragraph that discusses Galileo and Descartes. It begins on the bottom of p. 2 and goes to the top of p. 4.

23. Lohr, Steve (2006, 2 November), "Group of University Researchers to Make Web Science a Field of Study", New York Times: C6.
    • Is "Web science" a science?
    • How is it related to computer science?

24. "recommendations on texts...whose subject is the philosophy of science." (From Ask Philosophers.)

25. Hitchcock, Christopher (2007), "Conceptual Analysis Naturalized: A Metaphilosophical Case Study", Journal of Philosophy 103(9) (September): 427-451.
    • § I, "Theories of Causation" (pp. 429-433) contains an excellent summary of various contemporary and historical theories of the nature of cause and effect.

26. Tedre, Matti (2007), "The Philosophy of Computer Science (Winter-Spring 2007)"
    • Tedre, Matti (2007), "Introduction to the Course", Lecture Notes in the Philosophy of Computer Science.

27. Reed, Dan (2007), "Computing: All Our Constants Are Variables", Computing Research News 19(4) (September): 3.
    • Makes an interesting distinction between science as "natural philosophy" and as scientia (= knowledge).

28. Steedman, Mark (2008), "On Becoming a Discipline", Computational Linguistics 34(1) (March): 137-144.
    • Has some interesting things to say on the differences between a discipline such as physics and a discipline such as computer science (in general) and computational linguistics (in particular), especially in §1, "The Public Image of a Science".

29. Petroski, Henry (2008), "Scientists as Inventors", American Scientist 96(5) (September-October): 368-371.
    • The first two sections argue that all scientists are sometimes engineers and all engineers are sometimes scientists.

30. Vardi, Moshe Y. (2010), "Science Has Only Two Legs", Communications of the ACM 53(9) (September): 5
    • Argues that computing (or "computational science") is not a new kind of science or a new way of doing science, but just a more efficient way of doing the same kind of science that humans have always done.