Talks, webinars, workshops and podcasts on AI, language and learning, with dates, venues, and links to recordings and slides where they exist. 67 listed, 3 with a recording and 6 with slides or a handout.
Soonest first.
Dominik opens the October meeting of the AI Thought Exchange with a short review of what happened in AI over the summer, followed by discussion with educators from the UK and Australia. His slot starts at 09:10 BST. The AI Thought Exchange is an international discussion group on AI in education.
We are at an inflection point in what transformation we can expect in the age of AI. Agentic AI systems are now capable and reliable in way that allows us to delegate meaningful work to them. In the second half of 2026 we now have access to AI agents that can not just reliably work with files on computers but also use existing tools across a data processing workflow that have only been available to very few. This creates new opportunities for working with large amounts of data, from organising and maintaining collections to carrying out analysis. It also makes best reproducibility practices much more within reach for busy researchers. AI agents powered by more capable models can also expand the range of possibilities as to what data we can aspire to collect and open up new methodological opportunities.
This talk will outline key new tools and practice and illustrate their possible impact through several case studies.
A monthly roundup of AI news, with an RSS feed.
Researchers get more from AI when they move from asking a chatbot for answers to using desktop agents that work with their files and tools. The lecture shows how agents can work with archives, organise data, write and adapt analysis code, improve literature searches and make research more reproducible.
Dominik's annual retrospective webinar for the University of Oxford AI Competency Centre.
The emergence of Large Language Models (LLMs) has completely upset not only what we can expect of a computer but also how we view the role of technology in the process of learning. Now we have machines that can help at all stages of the learning process - they can not only help us manage cognitive load but also completely remove it. This talk will explore the roles AI can play in the learning process both from the perspective of the learner and the educator. It will explore the role of the LLM-powered tool not only as a productivity assistant, peer reviewer, or tutor but also as a toolmaker.
The question of AI in education is often reduced to debating about the impact of ChatGPT on the integrity of assessment. But AI in 2026 is not just ChatGPT and not just about what answers can be produced by a Large Language Model. One of the leading trends is the rise of agentic AI systems that can not only write snippets of code but build entire software systems or websites. This new approach to AI-assisted software development is often referred to as 'vibecoding' and it is this style of coding that is the focus of this talk. The webinar will outline the state of the art and its implications, looking at the key tools and the best ways for educators to approach getting to know them in order to integrate them into their work.
The emergence of Large Language Models has disrupted expectations of computing and technology's role in learning. This session explores how AI can support learners and educators at every stage, from managing cognitive load to serving as productivity assistants, peer reviewers, tutors, and toolmakers.
This hands-on workshop introduces language teachers to AI-assisted coding ('vibecoding') as a powerful new avenue for creating language learning applications. Using Gemini and Google AI Studio, the session demonstrates how educators can design, prototype, and deploy simple apps without prior programming expertise. Beyond technical skills, the workshop invites critical reflection on the pedagogical possibilities enabled by AI-assisted app creation.
Three years after the public launch of ChatGPT, the chatbot paradigm has undergone a transformation. The main mode of interacting with Large Language Models is no longer just a chat. This session steps back from day-to-day trends to look at how the landscape has shifted since 2022 and what the current frontier in what 'AI can do' and what 'we can do with AI' looks like.
Large Language Models represent an entirely new paradigm of semantic information processing. They are the first time a computer can process the meaning of text without mark-up. Their ability to 'understand' text is at the same time familiarly human and completely alien. This talk outlines how Large Language Models 'read' and 'understand' text, and how they generate their response, contrasting with how humans perform the same tasks.
This workshop will guide senior leaders in education through the essential steps of understanding the landscape of generative AI to enable better decision-making. Participants will explore the strategic implications of AI, address the current knowledge gaps, and develop continuous learning strategies to stay ahead in a rapidly evolving landscape.
On the two-year anniversary of the release of ChatGPT, this webinar reflects on the journey to today and the current state of generative AI with a focus on what has changed compared to our expectations in 2022, what has stayed the same and what we can see coming on the horizon.
This talk will explore what exactly large language models (LLMs) have learned about languages, and why it matters. It will attempt an outline of an answer to how these models understand the structure of language, and how this compares to how humans think about language. To answer the question, it will look at how LLMs perform across a range of different languages, even those with smaller digital footprints, and what this implies about how they represent language.
It will contrast the results from this investigation with the latest findings from the field of "mechanistic interpretability." These findings offer insights into the inner workings of LLMs, offering clues about the fundamental differences between how we understand language and how language is represented inside the models.
Finally, it will suggest a need a new approach to LLM research that brings together a richer understanding of language and a systematic investigation into how LLMs perform across a variety of languages.
This practical workshop will explore the opportunities for new kinds of digital scholarship in the humanities and social sciences presented by Large Language Models. It will present Large Language Models as a new kind of machine for processing semantic information in text with a completely new kind of capabilities and also new kinds of limitations. It will then explore what new opportunities these new machines present for digital scholarship based on practical examples. These opportunities lie not only in using Large Language Models as tools to assist with text data but also as a new kind of object to study.
The workshop is focused on enabling scholars in the humanities to get started with using Large Language Models in their work - no prior experience or knowledge is required. It will combine brief explanations and case studies with hands-on activities.
The major breakthrough of generative AI and specifically Large Language Models is the ability to work with unstructured documents with no semantic mark up. Combined with broad cross linguistic capabilities, this has great potential for digital humanities across many disciplines. This paper will explore the capabilities and limitations for Large Language Models when it comes to dealing with unstructured text, the key tools available to students and researchers as well as prospects of future developments.
Find out how tools built on large language models work and how you can make one for yourself or your students with or without code.
Chatbots are not the only way we can use Large Language Models to help us. There are now many possibilities for educators to create useful tools for themselves and their students. Even for those who do not want to build their own tools, it is useful to develop some understanding how these tools are made.
This session will break down the anatomy of an AI-based tool and explain how they are different from a chatbot, what role large language models play in how these apps work and what else their makers need to take into account.
A deep dive into the fascinating world of artificial intelligence, specifically focusing on its integration and impact on the education sector. We explore the significant roles of generative AI, including various tools and systems, aiming to demystify this transformative technology.
In this specialized talk for language professionals, LLMs are described as 'superpolyglots' but 'weird linguists.' While models like GPT-4 can translate between languages with high fluency, their acquisition method (reading the entire internet) is fundamentally different from human acquisition (embodied social interaction).
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