Abstract
It is argued that in deterministic contexts evidence for causal relations states whether a boundary condition makes a difference or not to a phenomenon. In order to substantiate the analysis, I show that this difference/indifference making is the basic type of evidence required for eliminative induction in the tradition of Francis Bacon and John Stuart Mill. To this purpose, an account of eliminative induction is proposed with two distinguishing features: it includes a method to establish the causal irrelevance of boundary conditions by means of indifference making, which is called strict method of agreement, and it introduces the notion of a background against which causal statements are evaluated. Causal statements thus become three-place-relations postulating the relevance or irrelevance of a circumstance C to the examined phenomenon P with respect to a background B of further conditions. To underline the importance of evidence in terms of difference/indifference making, I sketch two areas, in which eliminative induction is extensively used in natural and engineering sciences. One concerns exploratory experiments, the other engineering design methods. Given that a method is discussed that has been used for centuries, I make no claims to novelty in this paper, but hope that the combined discussion of several topics that are still somewhat underrepresented in the philosophy of science literature is of some merit.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
‘We may not proceed as by induction to establish a universal on the evidence of groups of particulars which offer no exception, because induction proves not what the essential nature of a thing is but that it has or has not some attribute’ (Aristotle 1928, II, 7, 92a36-b1).
In the twentieth century, the classic accounts which most stress the relevance of boundary conditions are Keynes (1921) and Mackie (1980). More recently, the tradition was picked up in particular by Baumgartner and Graßhoff (2004). Russo (2007) also stresses the significance of variation in comparison with regularity.
For a concise overview see Howick (2011) and further references therein.
While Norton uses the term eliminative induction in the broader sense of eliminating hypotheses, he also discusses in quite some detail Mill’s methods.
Note that the situation is symmetric if P and CX are exchanged. Therefore, additional constraints like time ordering have to be taken into account to establish a causal direction where necessary.
Eliminative induction is not only able to identify the nomic necessity of causal laws, but also various other kinds of necessity, e.g. definitional necessity.
Skyrms (2000, Sec. V.9) presents a similar story relying on a somewhat complicated reconstruction of continuous variables as families of physical qualities.
On closer inspection, it is not difficult to show that in his treatment of induction, Hume almost exclusively had enumerative induction in mind. This shortcoming was already stressed by John Maynard Keynes in his Treatise on Probability: ‘by emphasizing the number of instances Hume obscured the real object of the method. […] The variety of the circumstances […] rather than the number of them, is what seems to impress our reasonable faculties.’ (1921, 233–234) Russo (2007) endorses a similar anti-Humean viewpoint emphasizing variation over regularity.
A difficulty arises from the definitions of causal relevance and irrelevance as given in Sects. 3.2 and 3.3. In cases of overdetermination, a phenomenon may cease to have a cause on some level of description even though determinism holds in principle (cp. example in Sect. 3.3). However, this does not constitute a problem, since in those cases the phenomenon is fixed, no chance can interfere, and thus cases of overdetermination are not subject to the above-mentioned type of counter examples to the method of difference. More generally, not all phenomena need to be caused, in particular phenomena that cannot be otherwise, e.g. by definition, do not have causes since the method of difference cannot be applied.
‘The objects in the field, over which our generalisations extend, do not have an infinite number of independent qualities; that, in other words, their characteristics, however numerous, cohere together in groups of invariable connection, which are finite in number’(1921, 256).
Emphasizing the nature of evidence and scientific method when discussing causation is much in the spirit of the epistemic approach advocated by Williamson (2005) and Russo and Williamson (2011), who argue that an understanding of causality can only result from a thorough examination of causal epistemology.
For examples I recommend a Google search on ‘how to write a lab report’ resulting in e.g. http://schools.cbe.ab.ca/b631/Science%20Web%20Page/Grade%209%20Science%20Web%20Page_files/9%20How%20To%20Write%20Up%20A%20Lab%20Report.pdf, accessed 29.8.2013.
The distinction and terminology is Steinle’s (1997, 2005, esp. Ch. 7), it is also used by Burian (1997). For a more recent discussion confer Waters (2007) and references therein. The basic idea of exploratory experimentation is also described in Vincenti (1993) from an engineering perspective. With increasing use of information technologies in science, novel research paradigms emerge, in particular data-driven approaches. For an attempt to relate these to an account of eliminative induction, see my draft ‘Big Data—The new science of complexity’ (http://philsci-archive.pitt.edu/9944/).
Additional difficulties arise, when the causal knowledge gained with the model is to be applied to the real object under operating conditions, i.e. to a propeller of a plane in flight. Engineers, much more than natural scientists, have to take care that the background is stable enough to allow for practical application.
A certain notion of modularity has recently come under attack (e.g. in Cartwright 2007). However, this debate does not concern Arthur’s basic observation that modularity, broadly understood, constitutes a pragmatically useful feature for technological invention.
References
Anderson J (1938) The problem of causality. Australas J Psychol Philos 16(2):127–142
Aristotle (1928) Posterior analytics. Transl. Geoffrey R.J. Mure. In Ross WD (ed) The works of Aristotle, vol. 1. Oxford University Press, Oxford
Arthur BW (2009) The nature of technology. Free Press, New York, NY
Bacon F (1620/1994) Novum organum. Open Court, Chicago, IL
Baumgartner M, Graßhoff G (2004) Kausalität und kausales Schließen. Books on Demand, Norderstedt
Bucciarelli LL (2003) Engineering philosophy. Delft University Press, Delft
Burian R (1997) Exploratory experimentation and the role of histochemical techniques in the work of Jean Brachet, 1938–1952. Hist Philos Life Sci 19:27–45
Cartwright N (2007) Hunting causes and using them. Cambridge University Press, Cambridge
Dawkins R (2006) The selfish gene. Oxford University Press, Oxford
Fisher RA (2003) The design of experiments. In: Bennett JH (ed) Statistical methods, experimental design, and scientific inference. Oxford University Press, Oxford
Glennan S (2011) Singular and general causal relations: a mechanist perspective. In: Illari PM, Russo F, Williamson J (eds) Causality in the sciences. Oxford University Press, Oxford, pp 789–817
Goodman N (1983) Fact, fiction, and forecast. Harvard University Press, Cambridge, MA
Hacking I (1983) Representing and intervening. Cambridge University Press, Cambridge
Howick J (2011) The philosophy of evidence-based medicine. Wiley-Blackwell, Chichester
Illari PM (2011) Mechanistic evidence: disambiguating the russo-williamson thesis. Int Stud Philos Sci 25(2):139–157
Keynes JM (1921) A treatise on probability. Macmillan, London
Lavoisier A (1789/1965) Elements of chemistry. Dover, New York, NY
Mackie JL (1965) Causes and conditions. Am Philos Q 12:245–265
Mackie JL (1980) The cement of the universe. Oxford University Press, Oxford
Meijers A (ed) (2009) Philosophy of technology and engineering sciences. Handbook of the philosophy of science, vol 9. Elsevier, Amsterdam
Mill JS (1886) System of logic. Longmans, Green & Co., London
Norton J (2010) A survey of inductive generalization. http://www.pitt.edu/~jdnorton/papers/Survey_ind_gen.pdf. Accessed 28 Feb 2012
Pearl J (2000) Causality: models, reasoning, and inference. Cambridge University Press, Cambridge
Radder H (ed) (2003) The philosophy of scientific experimentation. Pittsburgh University Press, Pittsburgh, PA
Röntgen WK (1895) Eine neue Art von Strahlen. Stahel’sche K. Hof- u. Universitäts-Buchhandlung, Würzburg
Russo F (2007) The rationale of variation in methodological and evidential pluralism. Philosophica 77:97–124
Russo F, Williamson J (2007) Interpreting causality in the health sciences. Int Stud Philos Sci 21:157–170
Russo F, Williamson J (2011) Epistemic causality and evidence-based medicine. Hist Philos Life Sci 33(4):563–581
Skyrms B (2000) Choice and chance. Wadsworth, Belmont, CA
Spirtes P, Glymour C, Scheines R (2000) Causation, prediction and search. M.I.T. Press, Cambridge, MA
Steinle F (1997) Entering new fields: exploratory uses of experimentation. Philos Sci 64:S65–S74
Steinle F (2005) Explorative experimente. Franz Steiner Verlag, Stuttgart
Vincenti W (1993) What engineers know and how they know it. Johns Hopkins University Press, Baltimore
von Wright GH (1951) A treatise on induction and probability. Routledge, New York, NY
Waters CK (2007) The nature and context of exploratory experimentation. Hist Philos Life Sci 29(3):275–284
Williamson J (2005) Bayesian nets and causality: philosophical and computational foundations. Oxford University Press, Oxford
Acknowledgments
I am much grateful for helpful comments from two anonymous referees as well as the editors Phyllis Illari and Federica Russo.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Pietsch, W. The Structure of Causal Evidence Based on Eliminative Induction. Topoi 33, 421–435 (2014). https://doi.org/10.1007/s11245-013-9190-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11245-013-9190-y