Although it is increasingly recognised that the tools we use to examine our objects of study change our relationship to them, this is not an area that has been studied in any great detail within Digital Archaeology beyond perhaps discussions of the effects of different categories of software (the impact of GIS or database applications, for instance, or the effect of enlarged access to open data sources) on how we organise and understand the past. I have suggested elsewhere that through understanding how these technologies operate on us as well as for us, we can seek to ensure that they serve us better in what as archaeologists we already do, and help us initiate new and innovative ways of thinking about the past (Huggett 2004; 2012a). This entails going beyond the relatively commonplace reflections on specific software applications and their context of use: the tools we create, adopt, refine and employ have the effect of augmenting and scaffolding our thought and analysis, and consequently I have argued that they need to be approached in a considered, aware, and knowledgeable manner.
One of the key transformations in archaeological studies in the past thirty years is the shift from analogue to digital. In archaeological survey, for instance, we have witnessed a move from analogue dumpy levels and tapes to digital total stations and electronic distance meters that employ built-in algorithms to capture, record and process data through a mixture of semi-automated and fully automated methods. We have seen the cost of terrestrial laser scanners come down in recent years, and, perhaps more significantly, the development of the SIFT (Scale Invariant Feature Transforms) algorithm has seen an explosion in the use of structure from motion photogrammetry as a means of three-dimensional survey using consumer-grade cameras and drones. In the process, we have witnessed changes to the way in which we see the world and capture what we see. Much the same story might be told about other toolsets – whether we think of the developments in geophysical survey, for instance (see Ferraby, this issue), or the expansion of digital photography (for example, Morgan, forthcoming), or the growth of digital archives. But in each case, what do the changes in perspective offered by these tools imply for the practice of archaeology? And, as importantly, what are the implications of the development and use of these tools themselves?
The fact that archaeologists have been largely content to benefit from the application and contribution of these digital tools and have not paid a great deal of attention to these questions is far from unique. For example, until recently most philosophers of science focused on the theories surrounding scientific knowledge rather than the instruments that were employed in laboratories or elsewhere (for example, Bunge 2010, 85). Similarly, Ian Hodder has argued that archaeologists need to look more closely at things themselves:
'As social actors we tend to see things in ego-centred ways, in terms of what they can do for us. We hardly look at them. Our interests are in the effects for us, aesthetic, social, scientific, psychological and so on. But every now and then we actually look at the thing itself, as a whole object, a thing in its own right … there is sometimes a moment of realization that in order to understand the thing we have to look harder, anew, deeper, more fully.' (Hodder 2012, 2)
Here Hodder is interested in 'things' in the widest possible sense whereas I am thinking in rather narrower, digital, terms. However, as he goes on to say,
'… what makes an object relevant and useful in relation to the production of scientific knowledge … is not just the object itself, but the knowledge involved in recognizing an object for what it is and how it can be used.' (Hodder 2012, 3)
He adds that there is also knowledge incorporated within the object itself, in the form of knowledge about measurement procedures, physical properties and so on. We might add to this list the embedded algorithms used to capture and manipulate data, for example
The expanding development of autonomous cars and other forms of data-driven artificial intelligence (AI) has resulted in a lot of discussion about the benefits and risks associated with apparently knowledgeable machines in society more generally. In this context, however, AI devices are only one small group of things that incorporate and use knowledge for our benefit. At the other extreme, some philosophers of science – and indeed, Hodder himself – would argue that knowledge is encapsulated in even the most basic artefact. Hence, for example, the archaeological trowel contains knowledge in the form of its design, the relationship between handle and blade, etc. (albeit characteristics determined by a different domain), and through its application it reveals knowledge of archaeological value. If we doubt the complexity inherent in the trowel, consider that its mode of practice has to be adapted to the soil conditions and its use is not self-evident to the novice, nor does any written description of its operation substitute for direct demonstration and hands-on experience.
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