Joe Nockels
Projects
01
Terms and Conditions: Interpreting AI Tool Licences in Research Contexts
​
University of Sheffield, University of Birmingham, University of Buffalo, Programming Historian
Too often, university libraries are limited in recommending AI tools to students, due to certain terms and conditions. These conditions, in turn, lead researchers to accept individual risk through unauthorised usage. In modelling the usual red flags in AI licences through Natural Language Processing, this project will provide recommendations to tool providers in incorporating university library needs and their situational AI use.
02
Recognising Text, Recognising Processes -Explainable Automated Text Recognition for Scottish Spiritualist Newspapers (2025 - 2026)
National Library of Scotland, University of Sheffield
Internal Funding
This project researched how Explainable AI (XAI) developmental principles can intersect with library requirements, and support sustainable digital transcription at-scale. Directed by libraries' growing emphasis on XAI, this project answered: what aspects of ATR need further explanation? How are developers positioning themselves toward XAI public-facing documentation? Can XAI increase library audiences’ trust in ATR resources? Does greater explainability compromise ATR performance?
03
Using Handwritten Text Recognition (HTR) on The Life and Times of Frederick Douglass (1846-1894) (2024)
University of Edinburgh, Library of Congress
AHRC International Placement Scheme
This project demonstrated the efficacy of text recognition to analysis pipelines on handwritten library collections, using the autobiographical works of Frederick Douglass (1818 - 1895). Following this, it attempted to understand how intimate histories contained in handwriting can challenge and develop cultural understandings previously reliant on mechanical printed text.
04
.png)
Making the Past Readable: The Impact of Handwritten Text Recognition on Libraries and Their Users (2020 - 2024)
University of Edinburgh, University of Glasgow
AHRC Collaborative Doctoral Award.
This project considered the socio-technical infrastructure surrounding AI-enabled transcription of library collections. Despite sectoral awareness, institutional approaches still display gaps between conceptualising and operationalising HTR. Therefore, this project assessed the impact of HTR on libraries, users, and the wider information environment? Such analysis resulted in a set of recommendations for HTR’s future provision, directed thematically at libraries, HTR users and developers.