Author: Jennifer Edmond

The Trinity College Centre for Digital Humanities is recruiting a 2-year post-doctoral fellow with expertise in computational literary studies to join its growing and diverse team. The purpose of this post is to support the development of the LI4AI project, through the delivery of collaborative research in the field of computational literary studies (70%), and teaching backfill for the project PI (30%).

LI4AI is a proposal-stage research project that will use literary evidence to develop an evidence-based model upon which key competencies related to positive liberty – agency, autonomy, competency, transgression, creativity, trust and empathy – can be specified and made actionable within a software environment. As such, it will apply an urgently needed applied humanities approach to the challenge of AI development and regulation in light of the necessary pivot toward humane technology development and deployment.

LI4AI is led by Trinity College Dublin’s Professor Jennifer Edmond, Co-Director of the Trinity Centre for Digital Humanities. The appointee will be based in the Trinity Long Room Hub Arts and Humanities Research Institute and will work closely with Professor Edmond and the DH@TCD Team, also based in the Trinity Long Room Hub.

For more information, see the document below.

Jörg Lehmann and Jennifer Edmond were very pleased to have been given a chance to present some learnings from the KPLEX project to an engaged audience at the DH 2019 conference on 12th July 2019.  The paper was entitled “Digital Humanities, Knowledge Complexity and the Six ‘Aporias’ of Digital Research,” and explored a number of the cultural clashes we found between the perspectives in our interviews.  While DH was never a planned audience for our results, the response today convinced us that there is still much to mine from our interviews and insights!

The slides from the presentation can be viewed here.

Jennifer Edmond
Director of the Trinity College Dublin Centre for Digital Humanities and Principal Investigator on the KPLEX Project

One of the major terminological forces driving ICT development today is that of ‘big data.’ While the phrase may sound inclusive and integrative, in fact, ‘big data’ approaches are highly selective, excluding, as they do, any input that cannot be effectively structured, represented, or, indeed, digitised. Data of this messy, dirty sort is precisely the kind that humanities and cultural researchers deal with best, however.  In particular, knowledge creation and information management approaches from the humanities shed light on gaps such as: the manner in which data that are not digitised or shared become ‘hidden’ from aggregation systems; the fact that data are human created, and lack the objectivity often ascribed to the term; and the subtle ways in which data that are complex almost always become simplified before they can be aggregated. Humanities insight also exposes the problematic discursive strategies that big data research deploys, strategies that can be seen reflected not only in the research outputs of the field, but also in many of the urgent challenges our digitised society faces.

The lecture is available to view here: https://www.youtube.com/watch?v=E2vdFBo9wB4

The KPLEX project now features as a Net4Society Success Story in Social Science and Humanities Integration (SSH) into Information and Communication Technology (ICT) Research.  The fact sheet is now available to read here

A summary of the findings of the KPLEX Project is now available to download here.

“I end up is feeling that in the rush to new tools and ‘Big Data’ Humanist scholars are forgetting what they spent much of the second half of the twentieth century discovering – that language and art, cultural construction, human experience, and representation are hugely complex – but can be made to yield remarkable insight through close analysis. In other words, while the Humanities and ‘Big Data’ absolutely need to have a conversation; the subject of that conversation needs to change, and to encompass close reading and small data. ”

http://historyonics.blogspot.ie/2014/11/big-data-small-data-and-meaning_9.html