Entrée 147559

Artificial Intelligence (AI) is a hot topic at the moment, but my instinct is to see it, less as

something radically new and different, and more as just another episode in a long running

saga. Archivists have always had to grapple with the implications for the record of new

advances in information technology and as part of this, they have always sought to

experiment (both in thought and practice) with how best to tailor these advances to support

their recordkeeping purpose; how best to use the available technology to assist them in their

task. When it comes to technology-assisted appraisal and selection then, where has our

experimentation led?

One of the earliest experiments in this area appears to have been doctoral research carried

out by Anne Gilliland in 1995 to develop ‘an expert assistant for archival appraisal of

electronic communications’ (Gilliland-Swetland, 1995). This phrasing evokes earlier work in

AI carried out in terms of expert systems, thereby reminding us that the field of AI research

has itself a long and rich history going beyond the latest headline-grabbing developments in

machine learning.The expert systems approach tended towards the encoding of expert

knowledge into rules which would then be followed by the system. Such rules-based

approaches to AI are still taken but have perhaps been overshadowed by the more data-

based/driven approaches which have led to the current step-change in what is becoming

possible.

Jumping forward a decade, further experimentation was carried out as part of the Paradigm

project in 2005 to 2007. Paradigm involved archivists at the Universities of Oxford and

Manchester envisioning in practice how to work with – that is to accession, process and

preserve - born-digital material, specifically the private papers of a range of politicians. The

main output of the project was a workbook in which they reported everything they had learnt

from the experience. In terms of appraisal, they highlighted a range of tools that they had

found useful. Tools mentioned included: Karen’s Directory Printer, Unison and Windows

Explorer, but arguably what enabled these tools to be useful was the born digital and

structured nature of the (meta)data the tools allowed them to extract and use. No artificial

intelligence here, more technology assistance to get information (now available in a digital

form as data) in front of a human intelligence faster.

The tools suggested by the Paradigm project were also able to manipulate and compare the

information faster and this led to further practical experimentation, such as that reported by

Victoria Sloyan in respect of the appraisal and sensitivity review of two hard drives at the

Wellcome Library (2016). In this case, the superior information extraction and processing

capabilities of tools such as DROID and Microsoft Excel enabled, for example, the quick

identification (and elimination) of duplicate material and hence a reduction in the amount of

material that needed to be appraised in more detail. Such an approach was also suggested

by a contemporary experiment, this time one carried out at The National Archives (TNA)

using eDiscovery software. It concluded that“software tools are able to facilitate a ‘funnel’

approach to analysing born-digital records collections”; they offer “ways to prioritise and

reduce the volume of digital records that will have to be manually reviewed”.

TNA’s experimentation with eDiscovery software points to another important factor in this

equation, that of scale. One reason – perhaps the main reason - why assistance from

technology is so urgently being sought by archivists is that, as the volume of material

requiring ‘review’ increases, so does the possibility that no amount of ‘funnelling’ is ever

going to reduce it enough to match the size of the manual resource we have available to do

that review. The software TNA was experimenting with in the mid-2010s arose from

recognition of this fact in another context – that of the legal field’s framing of a process of

discovery; a process of reviewing an often vast amount of material to find that part of it which

had relevance and value to the case at hand. And so, if scale does eventually make

manual/human review or appraisal (as currently resourced) all but impossible, are archivists

prepared to give it up? To move to a position where such appraisal becomes a fully

automated process, one which they are happy to confine to and place into a black box

beyond their (or anyone else’s) direct observation and control?

This scenario has been the subject of more recent experimentation by The National Archives

as part of the Using AI for Digital Selection in Government project. This project sought to

assemble a range of ‘machines’ and to teach them, using examples, to appraise TNA’s own

corporate records as being either of long term value or not of long term value. One learning

machine was assembled in-house and five others were procured from a range of external

suppliers and consultants. Once taught, these machines then used what they had learnt to

appraise previously unseen records. The appraisals they made were then compared with

those made by TNA’s human record managers and in many cases the same appraisal was

reached.

What does this mean though and where do we go from here? Does it mean that the task of

appraisal can be undertaken by classifiers built using machine learning techniques? To some

extent, yes. Does it mean archivists will now delegate the task of appraisal to automated

systems? Almost certainly, no. Indeed, is the real question at issue here actually whether

archivists will ever be able to consider appraisal as just a task to be automated, rather than a

responsibility to be borne? What will it take for them to be willing to relinquish that

responsibility to others, however humanly or artificially intelligent they may be?

Bibliographical references

Gilliland-Swetland Anne,Development of an Expert Assistant for Archival Appraisal of Electronic Communications: An Exploratory Study. PhD Dissertation, University of Michigan, 1995.

Paradigm project «Holding page» [online], 2005-2007,http://www.paradigm.ac.uk/(access date 31.03.2023)

Sloyan Victoria,«Born-digital archives at the Wellcome Library: appraisal and sensitivity review of two hard drives», Archives and Records, 37/number 1, 2016, S. 20-36

The National Archives «The application of technology-assisted review to born-digital records transfer, Inquiries and beyond: Research report» [online], 2016, https://cdn.nationalarchives.g... (access date 31.03.2023)

The National Archives, «Using AI for Digital Selection in Government» [online], 2021, https://www.nationalarchives.g...(access date 31.03.2023)