Research into Practice: What a day of hacking on legal search taught us

By Caitlin Wilson and Barbara McGillivray

On 16 September 2026, researchers, legal professionals, UX designers, heritage practitioners, and members of the public gathered at King’s College London for a day-long hackathon. The goal of the day was to take real tools built on real collections, find the problems users have with them, and design something better together.

The event grew out of the first couple of rounds of user research conducted during the Lost for Words project (read more about it in this blog post), a collaborative doctoral award between King’s College London and The National Archives (TNA), for which Barbara McGillivray is the principal academic supervisor. In her doctoral project, Caitlin has been researching ways in which we can improve accessibility to the Find Case Law collection through semantic search. Through the development of prototype search engines, user research has been conducted to try to understand a few questions: How do people approach a complex collection like Find Case Law when they have little to no  prior knowledge of case law? What do people actually do after they find a result? And how do we build a tool that a lay person can use, while still being useful to legal professionals? The hackathon was proposed as a research and knowledge exchange activity, bringing together people with different expertise and experiences to explore these questions and co-design potential solutions. This blog post shares the ideas that emerged from the day and highlights how collaborative events of this kind can help translate research into practical improvements for users.

In order to bring different needs into focus, we divided participants into three tracks, each centred on a different TNA collection and its associated tool. The first was Find Case Law — TNA’s service for searching and reading judgments from courts and tribunals in England and Wales — participants in this track worked with a semantic search prototype developed through Lost for Words that lets users search the collection using natural language rather than exact legal terms. The second was Legislation Chat which is an experimental tool that lets users ask questions about UK Legislation in plain English and receive answers drawn directly from the text of the law. And lastly, the Parliamentary Archives, which recently moved to its new permanent home at TNA (read more about that here), holds records of both Houses of Parliament; participants in this track worked with the Discovery catalogue and a set of records flagged during an internal project as containing potentially sensitive or outdated terminology.In the morning, participants worked through scenarios using the tools, noted where they ran into difficulty and chose a problem to address. And by mid-afternoon, groups were building solutions: some sketched interfaces, some wrote code, and others mapped user journeys or prepared design briefs. Everyone shared their work at an end-of-day show-and-tell.

What the groups built

The Find Case Law track produced two distinct prototypes. One group identified something we hadn’t named clearly before: the tool performs differently depending on how you search. Short, crisp queries like a case name or a short legal concept return good results in a way that’s already familiar from keyword search. Long, narrative queries like the kind a litigant might type when they’re describing a situation rather than naming a term work better semantically, but the interface doesn’t signal this. The proposed prototype differentiated between the two modes, expanding the search box for narrative queries, probing for clarifying details, and returning AI-generated explanations of why each case was relevant to the specific situation described. The second group focused entirely on what happens after search: the results page. Their design added a contextual sidebar pulling relevant guidance from GOV.UK, adapted dynamically to the search query. The point was to close the gap between finding a case and knowing what to do with it.

The Legislation group proposed a chatbot that would invite people to choose the role closest to their perspective — lawyer, researcher, small-business owner or member of the public — and then adapt its wording and its suggested next steps. In their live demonstration at the end of the day, the group entered the same question under four different roles. They reported how the model changed its language depending on the user with little extra prompting. The group also considered how a chatbot should handle trust and legal disclaimers. Its proposal was to explain the limits of the service, use GOV.UK visual cues, and end each conversation by directing users to a named legal charity for further advice.

The Parliamentary Archives track split into two groups, each tackling a different problem. One team built a Python-based prototype to flag potentially offensive or outdated terms in catalogue descriptions for review. It retrieved records through the TNA’s Discovery API, then checked the text in two stages: first, it looked for specified word patterns (regular expressions); second, it used a language model to sort terms into categories without examples labelled for this particular task (zero-shot classification). The prototype also scored terms for severity, historical context and confidence. It would not change catalogue records automatically: instead, it flagged records for staff review and drafted content notes for cataloguers to approve. The team also proposed a way for members of the public to report terms they encountered. The second group focused on external researchers and the language they use. For example, someone studying the decriminalisation of homosexuality may need to search for historical terms that researchers today might not think to use. The group proposed a search-expansion feature that would show related historical terms alongside results, let users choose which terms to include, and explain how the suggestions were generated.

Three findings

Looking across the discussions, three themes kept returning.

People come to collections with different needs. The hackathon groups did not identify a single interface that would work equally well for everyone, instead they all posited that interfaces and systems need to be adapted to different user needs. The Find Case Law teams, for example, proposed different ways to search and the Legislation group explored adapting responses to different user roles; while the Parliamentary Archives teams distinguished between the needs of internal staff and external researchers. A key question for development is therefore who the tool is for, and whose needs may otherwise be overlooked.

Finding a result is only half the job. Both Find Case Law groups and the Legislation Chat group identified the same gap: users arrive at a result and then don’t know what to do next, meaning that users may need guidance, support or help deciding what to do with a result. The groups saw limited signposting beyond the results they were working with. One Find Case Law team proposed a GOV.UK guidance sidebar and the Legislation Chat group proposed a referral to a legal charity where users could seek further advice. Helping users move from a result to a useful next step emerged as a common design priority.

Human review should be built in, not added as an afterthought. The Parliamentary Archives prototype was designed not to change catalogue records automatically: an archivist is required to review flagged records and approve any content notes. Other groups explored related safeguards, including explanations of why a case appeared, feedback options and routes to further advice. Across the proposals, oversight meant more than checking a system’s work; it also meant helping users understand the results and find further support.

How other heritage organisations could try this approach

A hackathon built around real collections and tasks can produce a different kind of output from a design sprint or user survey. In our experience, asking participants to try real tasks with existing tools brought specific points of difficulty into view. Asking groups to sketch or build a response then required them to make design choices, rather than offer only abstract recommendations. The result was a set of proposals that can be developed and tested at a further date; they are not evidence, by themselves, that those proposals will work.

We believe that many heritage organisations face a similar challenge. They may have extensive digital collections, yet still find it difficult to see where an interface does not meet users’ needs. Watching people try real tasks, and bringing together people who know the collections with people who use them, can help make those gaps clearer. A mixed group may also suggest approaches that no single group would reach on its own.

Taken together, the day showed the value of bringing people with different experiences together to work on real collections. The ideas developed are starting points, not finished solutions: they still need to be tested with the people who will use these tools. But one lesson was clear: improving access to digital collections starts with understanding what people are trying to do and involving them in shaping the tools that help them do it.

If you’re working on access and discovery for a heritage collection and want to know more about how we ran the day, we’d be happy to talk.

 

This event was made possible through two London Arts and Humanities Partnership initiatives: the Lost for Words collaborative doctoral project at King’s College London and The National Archives, funded through an LAHP Collaborative Doctoral Award secured by Barbara McGillivray in partnership with The National Archives, and a further LAHP Staff-led Activities Fund award supporting the hackathon.

Revolut rolls out ‘Pay with Smile’ checkouts

Revolut has begun piloting its new facial-recognition checkout system, “Pay with Smile”, allowing customers to settle bills by scanning their faces at point-of-sale terminals.

Speaking to Metro, DDH’s Prof. Btihaj Ajana warns that that Revolut’s facial-recognition payment trial turns sensitive bodily data collection into a routine commercial practice, steadily eroding consumer anonymity. Having observed the technology deployed in China, Ajana cautions that framing biometric scans as everyday convenience normalises pervasive surveillance, fosters passive compliance, and makes opting out increasingly difficult. Crucially, unlike passwords or payment cards, facial biometrics cannot be reset once compromised, leaving users permanently exposed if breaches occur.

Full Metro article is accessible here.

Seminar – Meaning What, Exactly? Measuring and Learning Lexical Meaning Across Time and Languages

Part of Computational Humanities Research Group and King’s Linguistics Network

Register here: https://forms.gle/D8Kb5xAN5GUTa55t9

Hybrid (King’s College London, Room TBD + online via MS Teams)

19 November 2026, 4-5pm GMT

Roksana Goworek (Queen Mary University of London), Meaning What, Exactly? Measuring and Learning Lexical Meaning Across Time and Languages

Abstract

How can we analyse changes in word meaning across diachronic corpora? Changes in how words are used can reflect broader shifts in language and culture, making their detection relevant to historical linguistics as well as the study of cultural and social change. Contextualised language models have enabled large-scale analysis of semantic change by representing individual word usages in a shared vector space and comparing their distributions across corpora from different time periods. This raises several methodological challenges, from deciding how sets of representations should be compared, to obtaining representations that capture sense distinctions when target-language data are scarce, to creating the high-quality annotated data needed for training and evaluation.

Different approaches to comparing distributions of word usages can produce different estimates of semantic change, and their robustness may depend on the quality and structure of the underlying representations. These issues become particularly important for languages for which suitable models, corpora, or annotated data are limited. When target-language resources are scarce, the choice of training data can influence how well models generalise to those languages.

Constructing suitable training and evaluation data presents its own difficulties. Manual word sense annotation is costly, while rare or emerging usages, which can be particularly informative for detecting changes in meaning, can be difficult to find through conventional corpus sampling. Targeted sampling can make this process more efficient, helping to construct the high-quality human-annotated resources needed to establish whether computational methods work reliably for low-resource languages.

This talk explores how choices in measurement, model training, and data annotation shape our ability to detect semantic change, and what is required to extend such research reliably to a wider range of languages. More broadly, it argues that the methods and resources underlying semantic change detection need to be scrutinised carefully if we are to make reliable claims about changes in meaning.

Bio

Roksana Goworek is a final-year PhD student at Queen Mary University of London. Her research focuses on how language models represent meaning, with interests spanning lexical semantics, cross-lingual transfer and information retrieval. More recently, she has also worked on mechanistic interpretability, investigating how contextual information is processed and propagated through language models, including during a research internship at the Alan Turing Institute.

Quantitative Diachronic Linguistics and Cultural Analytics 2027 (QDLCA27)

We invite submissions for the second edition of the conference Quantitative Diachronic Linguistics and Cultural Analytics 2027 (QDLCA27), to be held at King’s College London (Strand Campus, WC2R 2LS, London) on 14–15 January 2027. This will be an in-person event.

Language is in constant flux, shaped by social, cultural, and cognitive forces over time. With the increasing availability of large-scale textual data and computational tools, researchers are now better equipped than ever to uncover patterns and mechanisms of language change across different linguistic areas (e.g., morphology, syntax, semantics). This conference explores the intersection of quantitative diachronic linguistics and cultural analytics, to investigate how language evolves and how these changes relate – directly or broadly – to cultural dynamics. 

We welcome contributions that engage with any aspect of historical linguistics and diachronic language analysis, provided they incorporate quantitative approaches and offer insights into the interplay between linguistic and cultural change.

Confirmed keynote speakers are Prof Dirk Geeraerts (KU Leuven) and Dr Stefania De Gaetano-Ortlieb (Saarland University).

Submission Guidelines

  • We invite abstract for 20-minute presentations, followed by 10 minutes of discussion.
  • The abstracts should be anonymised and consist of a maximum of 400 words (excluding references).
  • Please submit your abstract as a .docx file via email to: quantitative.diachronic.ling@gmail.com. Use the following subject line: “ABSTRACT Quantitative Diachronic Linguistics”

In case of a large number of high-quality submissions, some abstracts may be selected for poster presentations. Authors will be invited to indicate whether they would consider their submission suitable for a poster session, should one be included in the programme. Poster selections will be based both on authors’ preferences and on reviewers’ recommendations, as reviewers will also be asked to assess the suitability of submissions for poster presentation.

Deadline: 13 September 2026, 23:59 BST

Topics (non-exhaustive list)

Submissions may include (but are not limited to) the following areas, with no restrictions on language(s) or historical periods:

  • Quantitative studies of language change across time
  • Corpus-based analyses of language evolution
  • Computational modelling of diachronic syntax, semantics, morphology, etc.
  • Cross-linguistic comparisons using large-scale data
  • Language change in connection with historical, literary, or cultural trends
  • Digital methods for exploring linguistic and cultural shifts
  • Applications of cultural analytics to linguistic data

Important Dates:

13 September 2026: Abstract Submission Deadline

26 October 2026: Notification of Acceptance

14-15 January 2026: Conference Dates

For any inquiries, please contact the organiser, Andrea Farina (andrea.farina@kcl.ac.uk).

This conference is organised by the project COALA – Computational Corpus Annotation for Quantitative Analysis of Latin Lexical Semantics (https://coala.er.kcl.ac.uk/about/), successfully evaluated by the European Research Council and funded by UK Research and Innovation. COALA develops computational methods and corpus annotation tools for the large-scale quantitative analysis of semantic variation and change in Latin across more than two millennia of textual history. It combines advances in historical word sense disambiguation, corpus linguistics, and computational semantics to transform research on historical lexical semantics and provide new insights into how meaning changes across genres, registers, and cultural contexts over time.

Scientific Committee

Eleonora Litta (Università Cattolica del Sacro Cuore) 

Pierluigi Cassotti (University of Gotenburg) 

Jurica Polančec (Old Church Slavonic Institute Zagreb) 

David Goldstein (UCLA)

Alek Keersmaekers (KU Leuven)

Erin Canning (University of Oxford)

Sabine Tittel (Heidelberg University)

Luisa Miceli (University of Western Australia)

Welcome to Richard Rogers, Visiting Professor at the Department of Digital Humanities ✨

We are delighted to announce that Richard Rogers (University of Amsterdam) will be joining us as a Visiting Professor at the Department of Digital Humanities, King’s College London. In the post below he discusses his plans.

I’m very pleased to be able to join the Department of Digital Humanities over the coming period. I’ve worked closely with colleagues at King’s College London for years and look forward to further collaborations.

My main project for the visiting stint is entitled, Chatbots for internet research: a critical reflection, which is shaping up into a book. It came into being initially as tests or experiments with chatbots and ultimately have become approaches to research that supplement and extend the digital methods I’ve been working on.

Chatbots for internet research has three lines of enquiry. One is how to use chatbots for social media, search engine and other online analysis (‘internet research’) but also how to study them as media, as both a vector space medium as well as a platform. Thirdly, I’m particularly interested in those occasions when researcher and machine findings misalign and how to characterise them. Certain of these moments have to do with platform effects such as user pleasing and value alignment that produce ‘overagreement’ and a ‘bias towards neutrality’, respectively. They may have to do with limited scraping, where model responses exhibit ‘technical shallowness’. But they also arise when chatbots are asked to prove themselves and then subsequently provide bogus sources, despite the fact that they appear to produce good (synthetic) data. I characterise this occasion as ‘ungrounded performance’.

During the visiting period, I’m looking for opportunities to conduct workshops and undertake such experiments as well as other methods work. 

Richard Rogers is Professor of New Media & Digital Culture, Media Studies, and Director of the Digital Methods Initiative, Humanities Labs, University of Amsterdam. His is author or co-author of Information Politics on the Web, Digital Methods (both MIT Press) as well as Doing Digital Methods (Sage) and Digital Methods: A Short Introduction (Polity). He is editor or co-editor of The Politics of Social Media Manipulation, The Propagation of Misinformation in Social Media (both Amsterdam University Press) and Content Moderation across Social Media Platforms (Routledge). Apart from his project on chatbots for internet research, he is currently working on auditing content moderation on social media platforms, FIMI and the politics of methods as well as Wikipedia as media archaeological instrument.

A Social Critique of AI amid the Climate Crisis

by Paul Schütze

I am currently a Visiting Senior Research Fellow at the Department of Digital Humanities, King’s College London. As part of that visit, I recently gave a talk titled “A Social Critique of AI amid the Climate Crisis.” In that talk, I argued that AI is more than an environmentally costly technology. It is a system and an ideology that keeps extraction going and makes the current socio-economic dynamics seem inevitable. From this perspective, climate apathy is not a political failure. It is the systemic outcome of an AI-driven social order.

What I have laid out here is a pointed version of my argument, without the full theoretical scaffolding underneath it. If you are interested in the longer version, I am genuinely happy to talk through it. Please reach out!

But what does a social critique of AI actually mean?

There is a perspective on the AI-and-climate connection that most people have heard by now. Data centres consume enormous amounts of energy. Training large models releases tons of CO₂. The hardware for AI models to run on requires the mining of rare earth minerals under brutal conditions. All of this is true, and all of this is important.

But, what I call a social critique of AI goes beyond this perspective. This is because, beyond the environmental impact, there lingers an underlying question: why does any of this continue to happen? If we know the climate effects of AI (and other technologies for that matter), why do we not change it?

Simply put, the AI-and-climate connection is not an epistemological issue, it is not an issue of having too little knowledge. AI does not only have an environmental footprint problem. This would be a flaw that could be fixed with a different technological design. Run the data centres on renewable energies. Build more efficient chips. Regulate the emissions of model training. All easy solutions. Yet, while this may be helpful in some regard, these apparent solutions do not solve the underlying problem. The extractive order simply keeps going.

A social critique of AI begins by refusing this story. No better design, no further knowledge, and no greener infrastructures can get us out of this crisis. A social critique insists on looking at AI not as a technology with some negative side effects. But, it understands AI as a system embedded in a specific socio-economic order, which is built on the logics of extraction, control, and apparent efficiency. This very system will not fix the climate crisis. The climate crisis is not a malfunction of that system. It is a structural feature.

Understanding AI in terms of a social order

Once you refuse this story, and once you shift the frame, AI’s climate impact starts to look different. With this, we can now conceptualise AI as an ideological apparatus – an assemblage of stories and assumptions, of material practices and institutions – that makes the current social order feel natural and inevitable.

AI as an ideological apparatus works like this: It tells us that optimising technological systems is progress. That efficiency is inherently valuable. That data-driven decisions are superior. That technological innovation is the primary driver of human well-being. Yet, these are very specific claims that serve very specific interests. They reproduce what is already there. They make the current order feel permanent and even desirable. They make alternatives feel naive and impossible. This ideological function is what makes AI so damaging in the context of the climate crisis. AI does not just skyrocket emissions. It deepens the conditions that prevent any serious climate action.

This is the key point of a social critique of AI amid the climate crisis. We are on a trajectory toward three degrees of warming by 2050. Three degrees means ecosystem collapse, food system failure, large parts of the planet becoming uninhabitable. AI keeps these realities at bay, just enough that it does not feel necessary to actually confront this catastrophic reality.

A social critique refuses to accept that comfort. It calls out the underlying structures that produce the climate crisis. It paints AI as an integral part of these structure. It insists on facing the reality rather than retreating into the ideological narratives that make business-as-usual feel acceptable.

This is why a social critique of AI amid the climate crisis is important. The goal cannot simply be to design a better AI ethics framework or to improve the efficiency of data centres. The aim cannot be to propose the right carbon tax or the right AI regulation. But, we need to make visible the systems that keep (re)producing this outcome. We must trace how AI is embedded in and amplifies these very systems, and we thereby must refuse the stories that make all of this seem inevitable. AI is helping to build a world in which saving the planet means something entirely different from what it would actually require. Making this visible is the aim of the social critique I propose here.

New Funding Opportunity: King’s-Ramón Areces Foundation PhD Scholarship (K-FRA)

Yutong Liu & Digit / https://betterimagesofai.org / https://creativecommons.org/licenses/by/4.0/

The Department of Digital Humanities is delighted to announce a prestigious new doctoral scholarship scheme, offered in partnership with the Ramón Areces Foundation.

The King’s–Ramón Areces Foundation PhD Scholarship Programme (K-FRA) is designed to support a researcher of Spanish nationality in undertaking full-time doctoral study within our department, starting in October 2026.

A comprehensive support package

The scholarship provides an exceptional level of support over three years of research, including:

  • Full tuition fees covered for the duration of the programme
  • An annual stipend of £22,780 (including London Weighting)
  • A £1,000 annual grant for research training and related support
  • Overseas student health cover and a standard-class return airfare between London and Madrid

Research themes

We welcome applications across the full breadth of Digital Humanities. We are particularly keen to receive proposals aligned with digital methods and cultural heritage, computational humanities and cultural AI, digital identities or governance, including projects that apply digital tools within the arts or wider cultural sectors.

As Paul Spence, Reader in Digital Humanities, notes:

The King’s-Ramón Areces PhD Scholarship Programme enables outstanding researchers to pursue innovative, internationally oriented doctoral work, strengthening long-standing academic links between UK and Spanish digital humanities researchers.

Key dates and how to apply

Application closing date: 13 February 2026.

To support prospective applicants, we will be hosting an online information session on 12 January, from 15.00 to 16.00 (UK time). To register your interest and receive access details, please complete the online registration form.

The session will provide further information about the programme, the application process, and the specific terms and conditions set by the Ramón Areces Foundation.

Find out more

For full eligibility criteria and detailed application instructions, please visit the official page of the King’s–Ramón Areces Foundation PhD Scholarship Programme (K-FRA).

Best overall student in MA Digital Humanities, 2024-2025

Congratulations to Kesara Ariyapongpairoj for being awarded “Best Overall Student in the MA Digital Humanities” in 2024-2025. 🎊

Kesara is a MA Digital Humanities graduate from King’s College London with a background in Philosophy. Her research focuses on how digital media and emerging technologies have transformed the production and dissemination of information, and the socio-political and cultural impact of online narratives in shaping belief systems and ideologies.

Continue reading “Best overall student in MA Digital Humanities, 2024-2025”

a late autumn co-learning workshop on digital methods for social and cultural research

Last week Claudia Aradau, Liliana Bounegru and Jonathan Gray co-organised a late autumn co-learning workshop on digital methods for social and cultural research. 🍂🌱🐿️🦔

Continue reading “a late autumn co-learning workshop on digital methods for social and cultural research”

Dr Rachael Kent wins historic case against Apple in £1.5 billion collective action

The case, Kent v Apple, was brought by Dr Rachael Kent, Senior Lecturer at King’s College London, who made history as the first female Class Representative in the UK’s collective action regime.

Dr Rachael Kent
Continue reading “Dr Rachael Kent wins historic case against Apple in £1.5 billion collective action”