Abstract
When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar them from such activity? A close look at the methodology of interpretive social science reveals several abilities necessary to make a social scientific discovery (such as cognitive empathy and the ability to assign meaning) and one capacity necessary to possess any of them is imagination. Novel and significant interpretations required by social scientific discovery require imagination. For machines to make discoveries in social science, therefore, they must possess imagination algorithms.
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Notes
- 1.
Especially in the work of Herbert Simon and his students. See e.g. Newell, Shaw, and Simon (1958), Simon (1977, 1979), Bradshaw, Langley, and Simon (1980), Bradshaw, Langley, and Simon (1983), Langley, Simon, Bradshaw, and Żytkow (1987), Langley and Jones (1988), Shrager and Langley (1990), Langley, Shrager, and Saito (2002), Langley (2000), Dzeroski, Langley, and Todorovski (2007).
- 2.
- 3.
He writes, “Discovery consists precisely in not constructing useless combinations, but in constructing those that are useful, which are an infinitely small minority. Discovery is discernment, selection” (Poincaré, 1914, p. 51).
- 4.
For a statement of analytic induction, see Znaniecki (1934) and Lindesmith (1947). For statements of grounded theory, see Glaser and Strauss (1967), Corbin and Strauss (1990), Glaser (1978), Strauss (1987), and Strauss and Corbin (1990). For statements of the extended case method, see Burawoy (1991, 1998, 2000). In what follows, I try to distil the methods of ethnographic interpretation, but I cannot do them complete justice. Interested readers are encouraged to look at the sources listed for more details.
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Acknowledgments
Thanks to the organisers and participants of the conference “Scientific Discovery in the Social Sciences” at the London School of Economics, as well as Nancy Nersessian, Marco Buzzoni, Markus Kneer, Maël Pégny and Peter Sozou for comments on earlier drafts of this paper, as well as Susan Staggenborg (and Nancy Nersessian again) for generosity in sharing their knowledge of social scientific methodology. This work was funded by a postdoctoral fellowship from the University of Pittsburgh, and a postdoctoral fellowship from the Social Sciences and Humanities Research Council of Canada.
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Stuart, M.T. (2019). The Role of Imagination in Social Scientific Discovery: Why Machine Discoverers Will Need Imagination Algorithms. In: Addis, M., Lane, P.C.R., Sozou, P.D., Gobet, F. (eds) Scientific Discovery in the Social Sciences. Synthese Library, vol 413. Springer, Cham. https://doi.org/10.1007/978-3-030-23769-1_4
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