Abstract
Computational science and engineering (CSE) technologies and methods are increasingly considered important tools for the humanities and are being incorporated into scholarly practice. This chapter uses a single case of the use of simulation in the humanities in order to better understand the value and the issues with cross-disciplinary exchanges. We focus on the epistemic practices of this case – by which we mean the practices in which knowledge and truth are manifested, defended, and critiqued. We see these practices and their connections to CSE as requiring increased attention and in this chapter provide some guidance as to potential resources and important themes.
TopIntroduction
Computational science and engineering (CSE) technologies and methods are increasingly considered important tools for the humanities and are being incorporated into scholarly practice. As noted by many digital humanists (McCarty, 2005), these tools foster novel modes of engagement with older questions as well as the development of new lines of research. This makes them attractive objects for innovative scholarship and examples of such research are multiplying (Schreibman et al, 2004).
However, this is not to say that such adoptions and, increasingly, adaptations of simulation and modelling technologies are without challenges. One challenge is the fear by scholars that some of the means for exploring and communicating knowledge that are particular to specific humanities fields may be lost. Others worry that the capabilities of new technologies may not be fully exploited. Experiments and explorations in this area are therefore ongoing and are seen by members of relevant academic disciplines as having great potential but also as sites for concern. Formost among the issues is a desire to conserve and maintain the diversity of knowledge practices that is the hallmark of humanistic scholarship.
Computing has been called an ‘epistemic technology’ (Hooker, 1987), and it is certainly the case that simulation and modelling technologies fall into this category. By epistemic technology Hooker means that computational technologies amplify the knowledge-making capacities of humans, supporting and facilitating the creation, legitimation, and critique of truth claims. Specifically, along with great possibilities for revealing and visualizing insight, simulation and modelling also often embed specific practices of inquiry, evaluation, verification, and testing. These epistemic technologies make visible already existing fractures between and within humanities disciplines and also work to introduce new dividing lines. More importantly, these technologies may be used by members of particular disciplinary groups to buttress their own position within the wider scholarly context, create new divisions, or bring disparate groups together. Such processes have previously been explored within traditional scientific fields (Galison & Stump, 1996; Galison, 1997; Knorr-Cetina, 1999). In this chapter we address the interconnectness between epistemics and computational technologies within cross-disciplinary research in the humanities.
In order to call attention to the epistemic problems and possibilities, this chapter traces a particular adoption of computer modelling in archaeology, seeing the progression of this case as illustrative of the dynamics and challenges humanities scholars face in adopting CSE practices. Using stakeholder interviews carried out between 2005-2007, this chapter explores why a computer model reconstruction of a pre-Roman temple was created by a classical archaeologist and – more importantly – how it was received by other archaeologists, cultural heritage professionals, and computer scientists working in archaeology.
It is important here at the outset of this chapter to be clear about its intention. Rather than evaluate the role of simulation and modelling in archaeology generally – or the specific ‘good’ or ‘bad’ science of the specific case – this research is situated in and supported by insights from the Sociology of Scientific Knowledge (SSK) and Science and Technology Studies (STS) more generally. Using a single case as a ‘controversy’ study is a practice common in SSK and STS (Bloor, 1991; Collins, 1981; Dascal, 1998) as a means of exploring how critical decisions are made within research disciplines that involve either the maintainence or rejection of existing conventions of acceptability.
The starting point is thus the principle of ‘symmetry’ from which much sociological research on science emerges. This concept, originally described by Bloor (1981) states that theories about scientific projects must not rely on normative assumptions that assume that ‘good’ science is good because it is true but ‘bad’ science is bad because of politics, social reasons, or some other external factors. Most research in the STS tradition has taken this as a core insight and thus most STS research projects start from a position of epistemic neutrality, taking controversy over truth claims as the ‘topic rather than the starting point’ (Collins & Yearly, 1992, p. 302).
Key Terms in this Chapter
Epistemic Technologies: Technologies that amplify the knowledge-making capacities of humans.
Chain of Inferences: The process of interpretation and evidence that links observable phenomenon to theoretical reasoning.
Double-Bind: A situation in which an individual or group finds themselves having to meet two conflicting demands neither of which can be escaped or ignored.
Epistemic: The processes by which knowledge is made, communicated, and legimitated.
Controversy Study: Method for exploring how academic disciplines revise, maintain, or discard previous practices of knowledge-making.
Entanglements: The ways the instruments used to practice knowledge work embed specific epistemics.
Terracottari: Archaeologists who focus mainly on the study of terra-cotta structures and materials.
Post-Processual: Type of research in Archaeology that rejects linear models of causality and explanation and relies instead on interpretivist frames of reference.
Sima: a decorative tile that runs the length of the pediment of the roof on a classical building.
Predictive Modeling: Statistical method for determining the likelyhood that archaeological evidence will be found in a particul locale.
Processual: Type of research in Archaeology that encourages the use of ‘scientific methodology’, and, more specifically, the adoption of empirical-causal sensibilities.