We’re accustomed to the fact that much archaeology is collaborative in nature: we work with and rely on the work of others all the time to achieve our archaeological ends. However, what we overlook is the way in which much of what we do as archaeologists is dependent upon invisible collaborators – people who are absent, distanced, even disinterested. And these aren’t archaeologists working remotely and accessing the same virtual research environment as us in real time, although some of them may be archaeologists who developed the specialist software we have chosen to use. The majority of these are people we will never know, cannot know, who themselves will be ignorant of the context in which we have chosen to apply their products, and indeed, to compound things, will generally be unaware of each other. They are, quite literally, the ghosts in the machine.
Visualisation is much in vogue at present, especially with the increasing availability and accessibility of virtual reality devices such as the Occulus Rift and the HTC Vive, plus cheaper consumer alternatives including the Google Daydream and Sony’s Playstation VR, and there’s always Google Cardboard. We’re told that enhancing our virtual senses will increase knowledge, especially when we move into a virtual world in which we are interconnected with others (e.g. Martinez 2016), and the future is anticipated to bring sensors that go beyond vision and hearing and transmit movement, smells, and textures.
Hyperbole aside, we generally recognise (even if our audiences might not) that our archaeological digital visualisations are interpretative in nature, although how (or whether) we incorporate this in the visualisation is still a matter of debate. However, we understand that the data we base our visualisations upon are all too often incomplete, ambiguous, equivocal, contradictory, and potentially misleading whether or not we choose to represent this explicitly within the visualisation. I won’t rehearse the arguments about authority, authenticity etc. here (see Jeffrey 2015, Watterson 2015, Frankland and Earl 2015 (pdf), amongst others).
We’re becoming increasingly accustomed to our digital technologies acting as gatekeepers – perhaps most obviously in the way that the smartphone acts as gatekeeper to our calendar and/or email. In fact, this technological gatekeeping functionality appears everywhere you look, whether it’s in the form of physical devices providing access to information, software interfaces providing access to tools, or web interfaces providing access to data, for example. A while ago, I mused about the way that archaeological data are increasingly made available via key gatekeepers, and that consequently “negotiating access is often not as straightforward or clear-cut as it might be – both in terms of the shades of ‘openness’ on offer and the restrictions imposed by the interfaces to those data.” Since writing that, I’ve essentially left that statement hanging. What was I thinking of?
I’ve borrowed the idea of ‘deep-fried data’ from the title of a presentation by Maciej Cegłowski to the Collections as Data conference at the Library of Congress last month. As an archaeologist living and working in Scotland for 26 years, the idea of deep-fried data spoke to me, not least of course because of Scotland’s culinary reputation for deep-frying anything and everything. Deep-fried Mars bars, deep-fried Crème eggs, deep-fried butter balls in Irn Bru batter, deep-fried pizza, deep-fried steak pies, and so it goes on (see some more not entirely serious examples).
Hardened arteries aside, what does deep-fried data mean, and how is this relevant to the archaeological situation? In fact, you don’t have to look too hard to see that cooking is often used as a metaphor for our relationship with and use of data.
Infrastructures are all around us. They make the modern world work – whether we’re thinking of infrastructures in terms of gas, electric or water supply, telephony, fibre networks, road and rail systems, or organisations such as Google, Amazon and others, and so on. Infrastructures are also what we are building in archaeology. Data distribution systems have increasingly become an integral part of the archaeological toolkit, and the creation of a digital infrastructure – or cyberinfrastructure – underpins the set of grand challenges for archaeology laid out by Keith Kintigh and colleagues (2015), for example. But what are the consequences and challenges associated with these kinds of infrastructures? What are we knowingly or unknowingly constructing?
Patrik Svensson (2015) has pointed to a lack of critical work and an absence of systemic awareness surrounding the developments of infrastructures within the humanities. While he points to archaeology as one of the more developed in infrastructural terms, this isn’t necessarily a ‘good thing’ in the light of his critique. As he says, “Humanists do not … necessarily think of what they do as situated and conditioned in terms of infrastructures” (2015, 337) and consequently:
“A real risk … is that new humanities infrastructures will be based on existing infrastructures, often filtered through the technological side of the humanities or through the predominant models from science and engineering, rather than being based on the core and central needs of the humanities.” (2015, 337).
Solutions to the crisis in archaeological archives in an environment of shrinking resources often involve selection and discard of the physical material and an increased reliance on the digital. For instance, several presentations to a recent day conference on Selection, De-selection and Rationalisation organised by the Archaeological Archives Group implicitly or explicitly refer to the effective replacement of physical items with data records, where either deselected items were removed from the archive or else material was never selected for inclusion in the first place because of its perceived ‘low research potential’. Indeed, Historic England are currently tendering for research into what they call the ‘rationalisation’ of museum archaeology collections
“… which ensures that those archives that are transferred to museums contain only material that has value, mainly in the potential to inform future research.” (Historic England 2016, 2)
Historic England anticipate that these procedures may also be applied retrospectively to existing collections. It remains too early to say, but it seems more than likely a key approach to the mitigation of such rationalisation will be the use of digital records. In this way, atoms are quite literally converted into bits (to borrow from Nicholas Negroponte) and the digital remains become the sole surrogate for material that, for whatever reason, was not considered worthy of physical preservation. What are the implications of the digital coming to the rescue of the physical archive in this way?
In 2014 the European Union determined that a person’s ‘right to be forgotten’ by Google’s search was a basic human right, but it remains the subject of dispute. If requested, Google currently removes links to an individual’s specific search result on any Google domain that is accessed from within Europe and on any European Google domain from wherever it is accessed. Google is currently appealing against a proposed extension to this which would require the right to be forgotten to be extended to searches across all Google domains regardless of location, so that something which might be perfectly legal in one country would be removed from sight because of the laws of another. Not surprisingly, Google sees this as a fundamental challenge to accessibility of information.
As if the ‘right to be forgotten’ was not problematic enough, the EU has recently published its General Data Protection Regulation 2016/679 to be introduced from 2018 which places limits on the use of automated processing for decisions taken concerning individuals and requires explanations to be provided where an adverse effect on an individual can be demonstrated (Goodman and Flaxman 2016). This seems like a good idea on the face of it – shouldn’t a self-driving car be able to explain the circumstances behind a collision? Why wouldn’t we want a computer system to explain its reasoning, whether it concerns access to credit or the acquisition of an insurance policy or the classification of an archaeological object?