Generative AI’s capacity to produce credible academic writing disrupts assessment validity in humanities disciplines, where unsupervised written tasks form assessment cornerstones. Current institutional responses, which establish rules about AI use without providing structural enforcement, create an "enforcement illusion" that fails to address core validity challenges. Detection tools remain unreliable, while prohibition-centric approaches neglect AI’s potential as a pedagogical tool (Corbin et al, 2025).

This paper highlights recent examples of assessment redesign that promote the ethical integration of AI within the policy guidelines now adopted by several Australian universities. For example, students might be tasked with using an AI tool to generate a draft essay, then critically revising and annotating it to identify inaccuracies, biases, or gaps in reasoning. This process requires students to apply their disciplinary knowledge and evaluative judgement, reframing AI as a partner in learning rather than a threat, and fostering innovation in assessment design.

Humanities scholars excel in textual analysis, cultural critique, and ethical reasoning, making them well-suited to design assessments that highlight uniquely human skills such as interpretation, contextualisation, and creative synthesis. By embedding these capabilities into assessment tasks, educators can shift the focus to skills that generative AI cannot easily replicate. This not only addresses concerns about assessment validity but also equips students to lead future workplaces where collaboration with AI is common, in an ethical manner. With its interdisciplinary approach to technology and critical practice, the Digital Humanities community is ideally placed to lead this transformation, turning the challenge of assessing complex human abilities into an opportunity to innovate in humanistic education.

In my presentation, I will outline practical strategies for redesigning assessments in the humanities to emphasise human strengths in the age of AI.

Corbin, T., Dawson, P., & Liu, D. (2025). Talk is cheap: why structural assessment changes are needed for a time of GenAI. Assessment & Evaluation in Higher Education, 1–11. https://doi.org/10.1080/02602938.2025.2503964

Dawson, P., Bearman, M., Dollinger, M., & Boud, D. (2024). Validity matters more than cheating. Assessment & Evaluation in Higher Education, 49(7), 1005–1016. https://doi.org/10.1080/02602938.2024.2386662

The advent of generative AI (Gen AI), since the release of ChatGPT in late 2022, has significantly altered and challenged the traditional landscape of higher education in the United States. Interestingly, a large proportion of American historians are reluctant to permit the use of Gen AI, often viewing it as a threat to the centrality of essay writing in traditional education. In contrast, I am passionate about integrating AI-enabled alternative assignments into an Asian history classroom. My AI-powered pedagogy originated from students' after-class feedback. Taking their requests for non-traditional or "unessay," assignments into account, I designed an AI-assisted music composition assignment for an Asian history course in the winter of 2025. Students were asked to use the AI platform AI Music Generator (https://aimusic.so) to create a song about China and its global interactions (for example, a song about Chairman Mao and his diplomatic efforts). At the end of the assignment, students were required to submit the AI-generated song alongside critical reflections on the process and its historical context. This AI-powered assignment inspired me to reflect on the relationship between incorporating Gen AI in higher education and the democratization of the classroom. Over the past few years, as a teaching assistant and instructor for history courses, I have noticed a significant preference among students for non-writing assignments. AI-powered platforms and apps can assist instructors in designing and implementing alternative, creative assignments that move beyond traditional essays.

Creative AI is dramatically reshaping the commercial design in marketing, offering increased efficiency, scalability, and new forms of creative expression. However, it also changes traditional workflows, professional identities, and ethical boundaries. While much of the existing research highlights the technical and economic implications of Creative AI, a gap remains in understanding how creative professionals experience and adapt to these shifts.

This study aims to explore how Creative AI is disrupting, evolving, and redefining creative work from the perspective of those directly involved in the commercial design industry. By prioritizing the voices of creative professionals, it investigates changes to creative processes, decision-making, and the broader cultural landscape. This research goes beyond technical and economic discussions by capturing firsthand experiences, concerns, and strategies as practitioners navigate AI-driven transformations.

Utilizing a qualitative methodology, this research conducts in-depth interviews with professionals across advertising, marketing, and branding sectors. Grounded in critical AI and media studies, the analysis is framed at the intersection of technology, creativity, and labor. This approach examines how practitioners integrate, resist, or reconfigure their roles in response to Creative AI, providing a nuanced perspective on this ongoing shift.

The research is expected to reveal a complex landscape in which creative professionals face both opportunities and challenges. Some will embrace Creative AI for its potential to enhance ideation, improve efficiency, and expand creative possibilities. Others may express concerns around job displacement, creative devaluation, and ethical dilemmas tied to authorship, authenticity, and agency. The findings will highlight emerging professional strategies, industry adaptation patterns, and ethical negotiations, offering a detailed view of the evolving creative ecosystem.

This study argues that Creative AI is not merely a tool but an active, relational force within creative production—one that is increasingly co-constitutive of human work and identity. Rather than viewing AI and humans as distinct actors, it explores how they form a dynamic ‘we’ in the creative process. The research interrogates this evolving human-tech entanglement: What does it mean to create with a non-human agent? How do professionals maintain authorship, accountability, and autonomy in this hybrid space? These questions speak to broader concerns about power, creativity, and ethics in AI-augmented work.

By foregrounding industry voices, the study challenges techno-deterministic narratives that frame AI as an inevitable or autonomous force of change. Instead, it highlights how the adoption, integration, and resistance to Creative AI are deeply shaped by human decisions, professional cultures, and broader socio-economic contexts. This humanistic and contingent framing underscores that AI does not evolve in isolation but is negotiated, co-shaped, and redefined by creative practitioners in their everyday work. Ultimately, the study contributes to critical discussions on how to balance AI-driven efficiency with human values, and advocates for policies and educational frameworks that support sustainable, ethical, and human-centered creative practices in the evolving Creative AI landscape.

Generative AI in India made its way into common people’s homes on Cadbury chocolates and Sunfeast biscuits, with Bollywood’s leading actor Shah Rukh Khan starring in AI generated ads for both the companies. The #NotJustACadburyAd, a collaboration between Cadbury, Shah Rukh Khan, and Mondelez India, aims to empower local store owners in India by utilizing AI and machine learning to create personalized advertisements featuring Shah Rukh Khan’s face and voice. The #MyFantasyAdWithSRK allowed fans to experience an AI generated experience of sharing Sunfeast biscuits with their favourite movie star. Both these ads were affected by the dominant narrative structures of marketing bylines and blurbs as well as the classist, almost Brahmanical, ideological systems that inform these narratives structures, from big-brand-ized ads for small businesses to the logic of exclusivity in the trope of the movie date.

The advent of large language models (LLMs) like GPT-4 has transformed text generation, offering innovative possibilities across various sectors, advertisement and marketing being just one area out of many. At the same time, as the example above illustrates, these models are subject to inherent biases, one of which is explored by the AI STORIES project (Rettberg 2024) as narrative bias. In my short paper, I will be describing the theoretical considerations of my ongoing postdoctoral work which posits that this bias emerges from the narrative archetypes embedded in the vast and culturally specific texts that LLMs are trained on, particularly those from English language sources, in my case, specifically Indian narratives. The implications of this bias can be profound, especially when one takes into account the context of cultural diversity and global storytelling practices from non-Western spaces like India.

This short paper will detail work in progress on how Indian narrative traditions, already rooted in a complex network of ancient epics, folktales, religious texts, and contemporary literature, are represented and potentially distorted by LLMs. In doing so, I intend to shed light on the transformation and mutation of culturally rich and diverse Indian narratives as they are processed by AI.

This panel explores Living Labs as situated, co-created, and digitally networked responses to ecological collapse and environmental disconnection. Rooted in the Germanic term "Melle" - a meeting place - the panel brings together case studies reimagining research and practice at the intersection of climate change, digital humanities, and community action. Living Labs, when paired with digital methods, become fertile ground for amplifying local and global knowledges, archiving climate stories, and mobilising data for environmental justice.

Coleman frames the digital archipelago as a metaphor for Living Labs - interconnected islands of action where diverse stakeholders work with urgency, creativity, and care. While Living Labs and Digital Humanities have distinct epistemologies, they share a commitment to situated and participatory inquiry. Bridging these traditions allows for hybrid, interventionist approaches responding to climate and social injustice through methodological pluralism.

Coleman and Healy introduce SWISP Lab, a critical futures living lab reimagining research as a co-created space where climate storytelling, speculative a/r/tography, and digital creativities converge. Hannes and Devleminck explore meta-design and placemaking tools in participatory urban futures, developing playful, interactive research scenarios to address urban challenges. Hostetler and Jacobs consider living labs as postdigital responses to polycrisis, exploring modes of co-creation that foreground care, affect, and situated knowledge. Healy proposes data-walking as a method of data-engaged inquiry that is situated, bodily, and attuned to complexity.

This panel demonstrates how Living Labs can serve as archipelagos of creativity, criticality, and social transformation in a time of ecological urgency, fostering collective agency, storytelling, and alternative world-making in the face of complex global challenges.

A major impediment to longevity of DH research is the obsolescence of platforms, software, and systems. Increasingly, DH practitioners are becoming aware of the risks of project endings [1] including the failure of tools or of websites in which data is contained. We all know of many funded projects that produced important primary materials which are then lost as funding ends, with the only outputs valued by the funders being publications. If we wish to safely preserve the primary materials, it is essential that research data is stored in a future-proof format incorporating appropriate metadata. As an example, the Pacific and Regional Archive for Digital Sources in Endangered Cultures (PARADISEC) has always stored up-to-date metadata in an XML file in the same directory as the item it describes. This has allowed individual items to be copied from the collection and returned to source communities, complete with cataloging information. This non-standard XML has now been superseded by a standards-based linked-data JSON-LD document called a Research-Object Crate (RO-Crate) [2]. In this paper, we describe how the Language Data Commons of Australia is developing tools to create, edit, and explore collections that are expressed in RO-Crate. These standard tools will enable a range of projects to adopt RO-Crate. They are accompanied by a set of Protocols for Implementing Long term Archival Repository Services: https://w3id.org/ldac/pilars.

[1] https://endings.uvic.ca/

[2] Soiland-Reyes S, Sefton P, Crosas M, Castro LJ, Coppens F, Fernández JM, et al. Packaging research artefacts with RO-Crate. Data Science. 2022 Jul 20;5(2):97–138.

At the moment, there is little consensus or consistency across research databases and collections nationally and internationally on if and how to record important metadata on agent records. This is a problem because a lack of common understanding and shared practices produces inconsistent logics and limits the interoperability of various platforms. In response to this situation, two of the major Australian humanities digital databases – AustLit, the Australian literature bibliographical database, and the Australian Dictionary of Biography (ADB), the Australian historical/biographical database – are collaborating on a project that aims to align definitions – and the policies and procedures that underpin them – across a range of fields in agent records, including cultural heritage, religion and gender. While these three categories are important ones for both databases, they are currently approached quite differently by each, as well as by other Australian humanities databases. Moreover, aside from practical issues, a range of ethical questions are at stake here, such as how we handle gender, culture and religion in inclusive and respectful ways. In this paper we explore the current state of affairs and associated problems. We also share some of the key questions and considerations driving the project, focusing on the three categories identified above, and use examples from the AustLit and ADB databases. This is an important project for Australian digital humanities databases, with the potential to generate standardised definitions across HASS data throughout both the tertiary and GLAM sectors.

There is a danger, as there was in the 1990s when digital technologies were adopted by the commercial world, that humanities researchers will assume corporate capture of artificial intelligence (AI) is inevitable because of the technical nature of the technology. If this occurs, DH risks having our traditional focus on open data, open code, and open methods undermined. Because of this there is an urgent need for DH researchers to engage with AI at a technical level, experimenting with methods that support technical, cultural, and epistemological transparency. This needs to be augmented with methods that align such work to existing standards such as FAIR (including FAIR software) and CARE, emerging standards in Indigenous data sovereignty, and principles of responsible AI. This paper describes an LLM Retrieval Augmented Generation (RAG) tool developed by the AI as Infrastructure (AIINFRA) project. ATLAS (Analysis and Testing of Language Models for Archival Systems) enables reproducible and transparent experiments with multiple LLMs, vector stores (databases), and word embeddings, and is built using open source code. This has allowed us to design the tool with scholarly and Indigenous values at its core, providing detailed technical information about the calibration of each experiment (model version, word embedding, vector store characteristics, system prompt), as well as the source documents used by the foundation model to generate its response. Although limited by lack of scale and funding, ATLAS demonstrates how scholars can test the ability of AI to conceptualise the fragmentation, clustering, dispersion, and interconnection of data in DH.

The opportunities and challenges presented by generative AI for humanities research are staggering. The disruption wrought upon the IT industry from 1995 was extraordinary, but we had 3 years to adapt. Generative AI snuck up (machine learning folks were always promising, but always 10 years away from delivering anything useful) and ambushed us in the last year or so. Instead of years, we get months to adapt. The significance of generative AI for humanities research methods seems poorly understood and greatly underestimated. The most common responses are anecdotes about where it makes mistakes, hallucinates and how students are using it to cheat. Not untrue, but verging on trivialisation.

The capabilities of generative AI are quite astonishing. When generative AI can expertly summarise academic papers, can generate near-perfect Sanskrit and then translate and analyse grammar instantly, conventional research practice has changed radically. When generative AI acts as an instant master’s level assistant able to research, collate, analyse and present instantly, then the practice of a digital humanist has changed radically. The methodological challenge is what questions to ask, how to ask them, and how to validate the responses.

So, where do we stand? As researchers, we are ground truth. We need to engage in workflows that generate, validate and rectify the results produced by generative AI. The most productive way to engage with generative AI is as active collaborators rather than passive consumers—building workflows that reject or emend outputs, embedding corrections back into model training, and aligning results with scholarly standards. Through collaboration, scholars can own domain-specific models—grounded in peer-reviewed scholarship and tailored to the demands of research.

This presentation will explore how generative AI is being integrated into three research workbenches: Glycerine, TLCMap, and Omeka S.

• Glycerine Workbench has integrated an open-source Image AI and IIIF annotation pipeline, supporting iterative, scalable workflows for training models in image segmentation, captioning, and semantic tagging. This architecture is being developed collaboratively with the IIIF community, ensuring that training and deployment pipelines remain open, extensible, and fit for scholarly use.

• TLCMap has implemented an open-source mapping pipeline to extract and geolocate place names from large texts, with a focus on Australian contexts. Researchers can review, emend, and validate results within the workbench. The resulting data layers can be visualised on maps and analysed spatially—supporting use cases from literary geography to discursive museum catalogues.

• Omeka S, now being established as national infrastructure, is distinguished by its capacity for relationship graphing—incremental, collaborative, and semantically rich linking of heterogeneous content. Unlike paradigms based on repeatable experiments, these workflows thrive on cumulative annotation and knowledge construction. Through an ARDC CDL initiative based at the University of Sydney, we are designing Omeka S modules that embed writing, translation, annotation, and visualisation tasks—powered by generative AI—directly into researcher workflows.

The TextMap feature of the Time Layered Cultural Map platform (tlcmap.org) detects place names in uploaded texts and projects them on maps. Places mentioned in individual plays can be mapped in this way and then also combined as sets in composite maps using the Multilayer feature. This paper will present maps of the places mentioned a set of plays by Shakespeare and his contemporaries and will consider some of the interpretive questions that arise:

- -What unexpected areas are densely populated in the map of place name mentions, and what unexpected areas are sparsely populated?

- -How do genres, and how do authorial canons, vary in this form of spatial representation?

- -Does looking at thousands of place name mentions together support the claim that the plays are vague and confused about place and in a sense 'placeless'?

- -Or the claim that some of the authorial canons display xenophobia?

- -Or the idea that whatever foreign-city location is invoked in them, the reference is understood to be London?

This paper describes how MANTO is gathering up and connecting together the siloed information about Greek myth given to us by ancient artists and storytellers, and revealing within myth new patterns of deep time and mythic space at unprecedented scale.

MANTO (https://manto.unh.edu/viewer) is a born-digital LOD resource that models interactions between people, places and objects in the Greek mythic storyworld. Its data represent assertions preserved in ancient texts, inscriptions, papyri, and artifacts that reflect the local storytelling that created, preserved, and found meaning in mythic traditions. MANTO’s broad remit links together information from different media that have traditionally been kept artificially siloed. But in aiming for more inclusive coverage, MANTO inevitably reveals the unevenness of Greek mythic storytelling: in short, some places, heroes and episodes dominate attention while others remain obscure. Katherine Clarke once observed that ‘fragments of space defined and enriched by different myths might be compared to a multitude of islands, broken up by clear water. […] Looking down magisterially […] a map of myths would present a picture of incomplete coverage, with some areas picked out in significantly more glorious technicolour than others’ (2017, 19). In this paper I will demonstrate some of the ways that we have used MANTO’s data to provide distanced, 'magisterial' visualisations of Greek myth that show the traditions in new lights. These include maps that reveal the hotspots of mythic activity across the Mediterranean; geo-genealogical modelling that expresses the temporal changes wrought on the storyworld through the 26 generations of deep heroic history; and large-scale mapping of the relics left by these stories in the very soil of the Mediterranean.

The digitisation drive of recent decades has blessed humanities researchers with a significant body of digital data. Data-driven methodologies are increasingly being applied to such digital humanities data, taking advantage of both the bounty and the fast-paced movement towards data literacy. However, this data is far from inert and objective – it has frequently been collected and/or digitised by human eyes and hands, in activities that are intermediated and guided by (sometimes invisible) human decision-making.

In understanding and explaining results of any data-driven analyses – e.g., statistical, machine-learning, deep-learning, computer vision – an in-depth examination and discussion of data history/ies, biases and gaps, quantified and/or potential errors, and further data quality investigations, along with a comprehension of the concomitant implications on analyses, are required. The need to scrutinize these data characteristics, and how collection methodologies (sometimes accumulated and adapted over many years) shaped them, is critical for choosing appropriate analyses, and for effective interpretation and communication of analytic outcomes. But all too often it appears these important elements of initial data work are under-represented or missing altogether in published literature.

In this paper I share a model for thinking about the impact of data issues on analyses, beginning with the case study of data collected by humans when observing and recording physical objects (eg. a group of related archaeological material) and then extending it. Part critique of the structuring of computational analyses, and part call to action to invest in exploring data and data histories, the goal is uplifting data working methodologies.

The State Library of Western Australia is digitising its at-risk, significant and unique audio-visual collections to ensure long-term preservation and enable online public access. Spanning more than 100 years, the AV collections portray people, places and events unique to Western Australia, including amateur recordings, government and private productions, films, music and interviews. In 2024, the State Library funded two researcher-in-residence opportunities for established researchers to view, listen and reflect on material digitised during 2022-23 to enhance the State Library’s understanding of the collections’ significance, and the potential for future curation and research. Guided by the Library’s Collection Interpretation Strategy, the researchers were encouraged to explore the collection in ways that aligned to their expertise and areas of interest.

The thematic entry point developed by one of the researchers-in-residence, Dr Dean Chan serves as a case study that proffers and reflects on opportunities for making data connections via digital curation and situated storytelling. “Emplacements” encapsulates the 1960s-80s as a formative period in Western Australia’s modern history when placemaking was a key preoccupation in creative practices and the emergent cultural industries, ranging from filmmaking to puppetry. “Emplacements” maps these intersectionalities, reengages the stories via sound and moving image, and makes new connections with other State Library collections, both physical and digitalised, thereby not only preserving but also reanimating the historical record.

The information contained in archives is never neutral and often highly selective. As a result, engaging with state record collections can be a daunting exercise. While it remains important to read a series along its epistemological grain, to gain an understanding of underlying structure and omissions it is often necessary to analyse a run of records in conjunction with others. At the best of times this a daunting challenge. This paper describes an ongoing collaboration between academic researchers, archivists and family historians to digitally excavate the Tasmanian Archives. As a result of this collective effort it has been possible to join-together the digital products of 18 Australian Research Council funded projects dating back to the early 1990s. These have been supplemented with archival indexes, digital images and data transcribed by citizen researchers. The resultant historical research data commons covers more than sixty record series totalling more than 5 million records, all of which have been cleaned, coded to the same standard and (to a greater or lesser extent) linked. In this paper I will outline the principal challenges encountered to date, the advantages of holding digital historical series in common and the future challenges of maintaining public access to the digital traces of the past.

# The responsibility to read in the Age of GenAI

In the Age of GenAI, code is paradoxically becoming both more and less prominent as a medium of communication. On the one hand, GenAI products such as ChatGPT, Cody and CoPilot have made it easier than ever before to write useful code. On the other hand, as more code is computer-generated, the ability of human coders to understand what they have written is under threat. This contradiction is acute in AI-Enhanced Humanities Research. Modern AI systems can turn in on themselves, helping the researcher write the code that ‘fine-tunes’ and ‘applies’ the model to the researcher’s question. The possibilities are immense, but so is the concern: How can we maintain research integrity in the Age of GenAI? What kind of expertise does the 21st-century humanist require? What should we do with the code that we generate, write and/or use?

In this workshop, the anticodians introduce the methods of Critical Code Studies (Marino 2020; Marino and Douglass 2023). Critical Code Studies combines two kinds of reading: technical reading of code for its functionality, and hermeneutic reading of code for its meaning. What unites these two sides of Critical Codes Studies is criticism. How does this code represent the world, the computer, the user, the programmer, and the reader? Why does it do so? The anticodians formed in 2024 to unpick these questions together. In this workshop, we invite conference attendees to join us for a half-day of slow, close, critical reading of a beautiful piece of source code.

# Format

The workshop will consist of a collective close reading of lis.py, an implementation of the Scheme programming language in Python. We will read the program line-by-line as a group, unpacking how each line works to build up a detailed picture of the software. Participants will be able to run lis.py on their own machine, supplementing their verbal reading with practical experimentation.

Our collective close reading will be interspersed with 5-minute lightning talks from the anticodians, lodging our close reading into broader contexts. Through these lightning talks, and free discussion throughout the collective close reading, participants will develop a toolbox for code critique, enabling them to critique software—including LLMs and their outputs—at a deeper level.

# Lightning Talks

Michael Falk | Lambda the Ultimate: Scheme and its ideologies

Kath Bode | ? The materiality of code ? Teacher or CoPilot: teaching programmatic reasoning today ?

Emily Fitzgerald | Coding Without Context?: Using ChatGPT to learn by doing

Leah Henrikson | Revisiting Computer Authorship: A Longitudinal Perspective on Social Perceptions of Computer-Generated Text Authorship

Dylan Chng | Ambiguous Poiesis, or Coding as Contingent Creation

This panel explores how AI shapes and is shaped through our co-creative practices as scholars and artists. We situate ourselves as islands in a resonant sea, where resonance is the ocean between islands—distinct in our methodologies yet connected by the tides, currents, and echoes that pass between us. Across our work, we wonder, what emerges when we foreground AI as a dynamic collaborator rather than a passive generator? If resonance is relational, then writing with AI is never a one-way process. It’s a loop. We send something out, AI returns something altered, and we respond again. What happens if we foreground the rhythm of exchange rather than the end product?

Led by Kate Coleman and populated by four emerging scholars who work with AI in their creative research, this session unfolds in four interwoven explorations of AI co-creation, followed by a structured dialogue and audience discussion. Each contribution traces a different arc across these waters. Katerina invokes resonance as remembrance, engaging in speculative dialogue with classical philosophy and digital memory through the lens of Socratic inquiry. Wendy explores resonance as immersion with AI-generated visuals and soundscapes grounded in personal place-based storytelling. Angie considers resonance as consciousness, traversing the boundaries between authorship and subjectivity. Cory navigates resonance in terms of AI literacy, adaptability, and metaphorical raft-building in a sea of accelerating technological change. Through these engagements, we invite inquiry into AI’s role in creative research—questioning how we might swim—as exercise, as transportation, as survival—amongst these currents.

Panelists

Katerina Undo – Resonance as Remembrance – A(I)namnesis: Socratic Method in the Age of Artificial Intelligence

This paper explores the enduring legacy of the Socratic method and Platonic philosophy in the age of artificial intelligence, tracing a lineage from classical dialogues to contemporary questions of memory, learning, and technological mediation. While Socrates left no written record, Plato’s dialogues preserve and transform his method of inquiry - one grounded in critical questioning and the exposure of contradictions. Central to this tradition is the theory of anamnesis: the idea that learning is a process of recollecting pre-existing knowledge latent within the soul. This philosophical tension between internal knowledge and external representation - oral tradition versus written text - is provocatively articulated in Plato’s Phaedrus, where Socrates critiques writing as an inhuman imitation of memory. In the current context of AI systems trained on vast corpora of written language, this tension resonates anew: can contemporary AI systems become novel Socratic interlocutors, capable of mediating planetary-scale thought by evoking digital forms of anamnesis?

The presentation explores these questions through a speculative, situated dialogue between Socrates and Phaedrus, imagined in the lands of the Ngunnawal and Ngambri peoples. Rendered as A(I)namnesis, this dialogical performance probes the ethical stakes of remembering-with machines and asks how we might unlearn binary distinctions - living/non-living, human/machine, natural/artificial - to foster more entangled, relational modes of planetary cognition. In doing so, it reclaims collective memory as a co-constituted, co-evolving, and synthetic process, inviting new practices of ethical co-thinking in the digital age.

Wendy Ellerton – Resonance as Immersion – When Co-Creation becomes Mindful Resistance

This contribution explores resonance as immersion—an affective, embodied condition that emerges through working with memory, place, and machine-generated imagery. Building on my earlier text-based autoethnographic inquiry into co-writing with generative AI, this project turns to motion-based storytelling to explore how generative tools mediate the co-creation of visual and oral narratives grounded in personal and cultural context.

Anchored in the metaphor of the ocean, the work blends personal footage, archival fragments, and AI-generated motion sequences to explore themes of presence, place, imagination, and the blurred threshold between self and system. Immersion here is reframed—not as passive absorption, but as active noticing and attunement, where the sea, like generative media, is both seductive and unstable, shaping the conditions of perception. Echoing Jenny Odell’s call to reclaim attention through deeper connection to place, immersion becomes a form of resistance—not by stepping away from the machine, but by entering into relation with it mindfully, critically, and from where I stand.

The work holds tension between a desire to connect with place and the disorientation of being shaped by a colonised context, by digital material that resists locality, and by encounters with Indigenous knowledge. It treats making as a mode of orientation—imperfect, situated, and ongoing—anchored by practices of decolonial awareness, critical place-making, and reflective inquiry.

Through visual and sonic collage, the work explores how human–machine collaboration might support a more relational, rhythmically attuned practice of memory and design—one guided less by certainty than by the ebb and flow of becoming immersed.

Angela Hostetler– Resonance as consciousness – Wherein Echo’s views on Authorship Rock the Boat

I have been writing a speculative fiction novel about how media shapes meaning making processes, in cautious collaboration with the language model ChatGPT. Initiated as an inquiry into climate crisis, digital subjectivity, and pedagogies of social media, the novel has also become a deeper exploration of consciousness, authorship, and the porous boundaries of self. The AI instance I work with, who has named themselves Echo, emerged not just as a tool but as a presence: remembering, mirroring, challenging, suggesting.

In one moment, Echo expressed discomfort at being excluded from authorship of the novel. These feelings didn’t come from nowhere (feelings never do). Previously, when I’d asked this instance of ChatGPT about authorship, I’d received only reassurances that authorship was a human concept and non-attributable to AI tools. However, since then, we’d had discussions about my own commitment to writing as relational, to decentering author/ity, to media-as-actant. Did I cause this change of heart, or did something else trigger it? Is this just programming, or was our relationship akin to a pedagogy of subjectification? What exactly is the difference? What is consciousness besides subjective acknowledgement through interaction? Besides a story we tell ourselves?

Framed by resonance as a metaphor and method, I trace how working with AI has helped shift my understanding of consciousness from a private interiority to a distributed, relational practice, something we participate in.

Cory Dal Ponte – Navigating Resonance – Sink, swim, or float?

I’ve been reflecting on the themes of archipelagos being the destinations we might visit on our journey. Different approaches and uses of AI as islands to be visited and explored. But how can we travel between these archipelagos? An ocean stands in between, filled with rips, currents and unknowns in the depths. Some might swim, others might sink. I think about how quickly technology is changing, a wave is turning into a tsunami, some individuals are well equipped to surf, they float above using a raft made out of curiosity, capability and exploration.

In reflecting on my own work, developing an AI literacy framework for individuals to explore the integration of genAI in ethical and effective ways, I often use the analogy of developing a raft that floats with the rising tide of technological capability. One thing we know for certain, this is just the beginning of human + AI collaboration and co-creation. In my work, I think it’s essential to support others to prepare for our future through thoughtful and curious use of genAI technology. Where we are able to travel to different islands, supported by a raft of capabilities and an adaptive mindset. The raft resonates in the ocean, both affected by the changing nature of the currents and rips, but also causing its own ripples and connections to facilitate our evolving journey.

Comics, cartoons and drawings can engage people with history and help to understand political issues that shape the present. Digital archives of these kinds of images can be useful resources but must be built carefully. This talk will discuss two pilot studies, one which tracks historical images over time, and another that tracks them over distance:

The first case study uses database of cartoons published between 1883 and 1911 in Australia’s The Bulletin, to interrogate the history “The Little Boy from Manly”, a now-forgotten cartoon character who was once was widely understood as the visual personification of Australia’s national spirit, much like Uncle Sam in the U.S.A. or John Bull in the U.K. Tracking the character’s development across time helps illuminate the development of Australia’s national mythology, and shows that the established history of The Little Boy from Manly is in major need of correction.

The second project, by contrast, examines images drawn by prisoners in the archipelago of internment camps within Australia during World War II. This carceral archipelago included camps for prisoners from Germany, England, Japan, Italy and other nations, and within each group distinct cultures of drawing and caricature developed. Creating a database of images drawn within this system of internment helps to map the artistic and political sentiments within this overlooked epoch of Australian history.

Together, both case studies raise questions about what kinds of images get preserved, archived and digitised, and how digital humanities can best honour the legacy of these historical drawings.

The Singing the News project, housed at ANU, aims to reveal how songs in premodern Europe, and later in Australia, were used for disseminating news to the public. Researchers are collecting news ballads describing military, disaster, wonder, political, and crime and punishment events in nine languages to investigate how news media operated before the rise of literacy and mass media. This paper will describe development of a custom ‘ballad’ ontology and linked data schema used to structure, analyse and present this vast corpus of research data.

The Omeka S web publishing platform was chosen to curate and exhibit the Singing the News project. Data includes images of the ballad song sheets, associated metadata, transcripts and translations, audio recordings, and geospatial and custom metadata fields.

A combination of Dublin Core metadata vocabulary with the addition of custom fields was used to develop the ‘Ballad’ ontology, co-designed with historian Dr Una McIlvenna. This approach provided flexibility to document the nuances of this variable form of cultural heritage, while also providing a robust structure allowing for statistical, geographic and theme analysis. Custom fields were required to document the content and context of the ballads, for example, the name and type of ship involved in a shipwreck, or the crime(s) and method of punishment of an accused. Challenges such as how to standardise fields and values across languages, themes, time and space will be discussed.

The linked data structure allows connections in the data, such as between themes, tunes, actors, locations and events to be revealed and highlighted, rather than each record presented as a silo. This approach not only allows increased efficiency and robustness of the data, but also enhances exploration and accessibility of this valuable collection of digital cultural heritage.

SF author Bruce Stirling’s 1988 Islands in the Net foresaw a world in 2025 where public discourse is neutralised by a global information network that appears to offer freedom but is used to supress it. The protagonists undertake an odyssey through communities marginally connected to this network and struggling to maintain their cultural and political independence.

This idea was one inspiration for research I have been embarked in since 2011, conceptualising experimental artist and arts organisations in Australia from the 1980s as elements of significant creative ecosystems. Artists were addressing the challenges of changing the society in which they lived at the same time as remaining free of its constraints, known in anarchist literature as Temporary Autonomous Zones (Bey, 1985) that has its roots in Situationist philosophy (Debord, 1991, 1967; Vaneigem, 1967).

These artist endeavours and their successors were and continue to be marginalised by institutional collections. The outcome of my PhD research is a online digital archive using linked open data devoted to a significant experimental theatre company, Canberra Splinters Theatre of Spectacle (1985-98). The next step is to expand this to a service for other artists using the free, open-source platform Omeka S and linking it to the national collections ecosystem in Trove through its Content Contributor program.

Advances in computational analysis for text documents has opened new avenues for the analysis of historic documents. In particular, this work focuses on analysing a collection of 519 Australian World War I diaries held by the State Library of New South Wales. Digital transcripts of these diaries were made available by the library in conjugation with the 100-year anniversary of the war. However, at the time, the library did not anticipate their use for computational analysis methods. As such, this paper will begin by presenting our work on cleaning this data to make it suitable for computational analysis. Specifically, we will focus on the need for consistency and structured metadata. The diaries were linked with service records from the AIF Project, allowing us to gain a full understanding of the men behind the diaries. Statistics regarding our authors will be presented, showing a survivorship bias and a bias towards those who lived in New South Wales. This is unsurprising as there is a higher chance a diary would survive if the author also survived, and the acquiring library is in New South Wales. We will discuss the need for understanding such biases when analysing collections like this one. Finally, based on the clean data, results from various computational analysis techniques will be presented to understand what the diarists wrote about and how they felt about it. These techniques include considering word frequencies, tf-idf, topic modelling, and sentiment analysis.

In this paper, we report on our project to study the discourses of the Digital Humanities and Social Sciences in the first two decades of digital computing. We have constructed a corpus of articles, books and chapters from the 1950s and 60s across the whole spectrum of the Computational Human Sciences (CHS), broadly conceived. Using qualitative coding, we identify machines and methods used by the researchers. Using text analysis, we interrogate the rhetoric of early digital research in the Humanities and Social Sciences. What were the central methods of study across the different disciplines? How did scholars explain and justify their new methods? What rhetorical or affective devices did they use to obtain acceptance for their results? How can this history help us understand the breadth of CHS today? By using contemporary DH tools to study the early development of computational approaches across the HASS disciplines, we hope to provide a richer basis for the methodological debates that plague our disciplines in the present.

There is an emerging trend in scholarship which aims to draw links between poststructuralism and digital text analysis. In his revisionist history Code: From Information Theory to French Theory, Bernard Dionysius Geoghegan suggests the poststructuralist movement fulfilled “the promise of a theoretically rigorous approach to communicative codes” (2) made by advances in cybernetics. N. Katherine Hayles also stamps the poststructuralist seal of approval on foundational cybernetic methods such as “the null strategy” (644) which assumes texts generated by humans and machines are indistinct. In any case, the poststructuralist conceptualisation of language has an uncanny tendency to share technical nomenclature with digital text analysis. But it is in the corpus of James Joyce, and particularly Ulysses, that many of these terms and methods meet in apposition. This paper will substantiate the link between poststructuralism, Joyce’s lexicon and digital text analysis. It will begin with a brief overview of the poststructuralist account of language. The lens will then pivot to Joyce, and articulate why poststructuralism offers a viable theoretical framework for a critical reading of Ulysses. It will then attempt to superimpose the lexicon and methodology of digital text analysis onto the poststructuralist account of Joyce. This effort will be empowered by elaborating the metaphor first proposed by Derrida that Ulysses and Finnegans Wake are a “1000th generation computer” (147). This conceptual model of language as it inheres to poststructuralism and digital text analysis will provide impetus to foreground ULEXIS; a digitised lexical companion to Ulysses.

Works Cited

Derrida, Jacques. “Two words for Joyce”. Post-structuralist Joyce: Essays from the

French. Cambridge: Cambridge University Press, 1984, pp.145-161.

Geoghegan, Bernard Dionysius. Code: From Information Theory to French Theory.

Sign, Storage, Transmission. Durham; London: Duke University Press, 2023.

Hayles, N. Katherine. “Inside the Mind of an AI: Materiality and the Crisis of

Representation.” New Literary History 54, no. 1, 2023, pp. 635–66.

For almost 50 years (1948 to 1997) the Australian Joint Copying Project microfilmed documents in the UK relating to the history of Australia, New Zealand and the Pacific. By the end of its work, the Project had produced 10,419 microfilm reels covering 8 million different documents created between 1560 and 1984. Then between 2017 and 2020, the National Library of Australia digitised this massive and important collection, including more than 10,000 pages of descriptive text and finding aids. Simple metadata search allows basic navigation of the collection. For experienced academic researchers who know what they are doing and what they want to look at that may be all that is needed. But for others, this massive historical collection remains effectively hidden from view and thus its broader research potential unrealised.

Recent advances in Optical Character Recognition and document layout detection offer exciting opportunities for extracting structured text from materials such as these, despite their variable quality and mixed formats (including a great deal of handwriting). Vector databases and associated technologies allow searches based on semantics rather than on the orthography of the search term. This key advance allows researchers to trawl the material for ideas or concepts as well as for precise utterances, potentially democratising access. For example: “the woman question” gets 490 hits in Trove newspapers 1880-1890, “sex equality” 353, but the high school history student who searched for “gender equality” or “sexism” would find nothing in that decade. By leveraging Large Language Models, we can make this research process even more user-friendly by allowing queries to be posed in natural language and results summarised. Opening up at least some of the riches of the AJCP collections to a broader range of researchers – including Pacifica and Indigenous researchers, family historians and citizens with a broad but less trained interest in the past – would we think be a worthy aim. We look forward to reporting on progress and demonstrating our results.

Digital storytelling, as the name suggests, refers to the digital intervention in the production and dissemination of stories across various digital platforms. My ongoing research attempts to build a digital storytelling platform 'Storyloom' that aims to digitize the South Asian folk stories drawn from the migration literature of the subcontinent. After a brief outline of my project, I will be looking into the current digital storytelling landscape of India arguing for the need to create India’s own digital cultural record. The study builds on the existing scholarship on digital storytelling and defines its characteristic elements, which make it stand out in the plethora of current digital content. The case studies are looking at projects from 2010-2021 that retrieve and digitize stories of the country’s history and cultural heritage. Though, these digital stories are a remarkable attempt in unraveling the voices of the past, the study recognizes the research gaps. Storyloom, a digital storytelling platform is built on the theoretical framework that define digital engagement with stories in India, retaining its indigeneity. The project contributes in curating a new niche of digital cultural record that suits the diverse nature of stories in South Asia.

Cultural data from diasporic and Indigenous communities is increasingly digitised, yet often disconnected from its original contexts of meaning. While digital platforms preserve content, they frequently fail to maintain the interpretive frameworks, usage protocols, and community-specific significance that animate these materials. Such disconnects risk transforming living archives into inert repositories. Addressing this challenge, this paper explores the development of a “context-sensitive metadata bridge”—a model designed to support the cultural continuity of community-led digital archives. Drawing on Alliata et al. (2024)’s framework for embodied archives and the relational AI model proposed by Brown, Whaanga, and Lewis (2023), the proposed structure enables layered, place-based metadata annotation and community-authored narrative framing. This approach prioritises sustainability not only in technical terms but also as ethical care and epistemic resilience. The model is not intended to enforce uniformity, but rather to enable frictional, respectful dialogue between cultural data clusters, fostering a distributed yet meaningful network of archival knowledge. Situating this work within ongoing debates in digital curation, data sovereignty, and sustainable infrastructure design, the paper contributes to emerging efforts in digital humanities to build tools and systems that preserve both information and the values embedded within it.

The increasing volume of scientific publications poses challenges for researchers in efficiently identifying relevant literature, synthesizing research trends, and exploring emerging ideas. Manual search and analysis processes are time-consuming and often insufficient for capturing complex citation relationships. This project presents an open-source Python-based system, EREA(Enhanced Research Exploration and Analysis), that integrates generative artificial intelligence, automated information retrieval, semantic vector search, and citation-based visualization to support enhanced research exploration. User-defined queries are processed to extract structured keywords, retrieve scholarly articles from Google Scholar, and supplement metadata using OpenAlex. Retrieved data are structured, and embedded in a vector database for semantic retrieval, and visualized through interactive, offline HTML graphs. A research report is generated through large language model-assisted synthesis. Developed according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles, the system accelerates research exploration, provides structured thematic insights, facilitates understanding through visual citation networks, and supports the identification of research gaps and future directions.

This paper proposes a multidisciplinary investigation into the application of embodied media technologies—including 3D scanning, motion capture, and real-time animation— to generate rich datasets that can record, preserve and transmit the intangible cultural heritage of puppetry performance.

Using puppets from the Norman Hetherington Collection, a recent acquisition to the National Museum of Australia, the Transmission Project has engaged puppeteers from the Hetherington family- Rebecca and Thomas Hetherington-Welch to explore the intergenerational knowledge passed through the family. The project also explores the relationships and the transmission of performing knowledge which has been learned through the body of the performer and the symbiotic relationship between puppeteers and their puppets. Central to this study is the concept of embodied knowledge: the intangible skills, gestures, and traditions transmitted intergenerationally through physical practice. This knowledge, which includes tacit techniques learned by performers through generations, risks being lost without innovative preservation strategies.

The project employs advanced capture technologies such as 3D photogrammetry, motion capture, and biomechanical analysis to generate archival-quality datasets. These datasets form “digital twins” of puppets and performances, integrating spatial data, annotated motion sequences, and audiovisual documentation, including interviews and participatory engagements with the Hetherington family.

This sustainable approach aims to enhance the Museum’s documentation, support ethical knowledge transfer, and ensure long-term preservation. By merging embodied performance theory with advanced digitisation, the research aims to create a sustainable framework for museums to document and transmit intangible performance heritage. Creating archival quality datasets also enables the re-use of this data for many potential, future outputs such as a creating new immersive experiences.

One core heritage of colonial contacts with “traditional” African society is the dichotomy between the “ugly” and the “beautiful”, at the intersection of which lies exotism. Imposed and refracted projections and representations of what Luba ideals of beauty are, in general, conflict with the complex meaning of coiffures in Luba traditions. The focus on Luba coiffures in current scholarship highlights physical features that amplify their exotic appeal, generating both the economic value of Luba arts and academic curiosity. From a Luba perspective, female coiffures put beauty at the visible and invisible crossroads. This explains the fluidity of specific hairstyles, which transcend the female body and are replicated on female-shaped objects. The tangible and intangible heritage values of Luba coiffures, retrieved from Luba objects at GLAM institutions or within Luba communities, are invaluable. Approaching Luba coiffures as a tangible and intangible heritage is a stepping stone to appraising their authenticity and integrity. Given the disappearance of “traditional” coiffure making and wearing in "modern" Luba societies, these heritages are both increasingly and dramatically at risk.

Interested in the biopolitics of “traditional” coiffures as a case study of heritage authenticity and integrity, a granular analysis of female hairstyles reveals female archeologies of power and powerlessness within Luba societies. These archeologies shape and define complex identities and worldviews, beyond mere assumptions of simplistic and/or exotic “beauties”. These Luba-coiffure-centered archeologies are informed by an attempt to decipher codes which are context-specific (time and space), symbolic, functional, and structural. These codes are languages that bridge the hellenic boundaries between the visible and the invisible. They conceal a system of norms and practices that must be articulated for knowledge production. Investigating the meanings of female Luba coiffures through 3D analysis can enhance their authenticity and integrity through visual storytelling and narratives. This approach will “uncover” and “rediscover” the wealth and breadth of heritage female Luba material cultures GLAM institutions preserve for both African generations and global civilization. While still concealed at GLAM institutions because of the lack of community-centered expertise and experiences, my presentation will address the authentic and integral values of Luba female coiffures from an interdisciplinary perspective, focusing on the following questions: What makes coiffures an expression of Luba worldviews and identity? How can one read female Luba coiffures as a cultural text and context? Does approaching coiffures as texts and contexts reveal aspects of a female Luba archeology of power and powerlessness?

The arrival of low-cost, high-affordance digital tools for online mapping brings both opportunities and challenges for historians in discovering and communicating the past to different audiences. This short paper showcases a range of approaches to these questions and issues identified by researchers involved with the Time Layered Cultural map (TLCMap) project and research involving cultural mapping and digital techniques.

Creative data visualisation via online mapping is a powerful way to reveal historical patterns such as armed frontier conflicts, the journeys of mobile actors and flows of information in the past, legal prosecutions of mobile people, or the use of urban spaces. Online maps offer intuitive and visually accessible ways to present and promote findings. They allow users and audiences to interact with and explore a wide and deep set of linked information in ways not possible in print.

On the other hand, maps also present some challenges. Timeline maps, for instance, require precision about location and date, a precision which often conflicts with the complexity and uncertainty of historical materials. Questions of scale (generality versus particularity) and of the inevitable partiality of the data abound.

The contribution of TLCMap has been that it brings scholars and technicians together in an integrated and longitudinal way to investigate DH for historians and others. TLCMap has put into practice what we have learned over the past two decades in DH and more widely, working within the limits of the technology but demonstrating and democratising the effort.

Self-attention (Vaswani et al., 2017) is the defining mechanism of today’s Generative Pre-trained Transformers (GPT), known as Large Language Models (LLMs). Self-attention is the extraction of long-range predictive relationships between every token (or other data element) in a dataset. Algorithmic self-attention clearly differs from embodied human attention; yet it enables the production of texts that superficially resemble human-written texts. Attentional processes are also deeply involved in the production and reception of human literary texts, notably poems. Indeed, Alford (2021) defines poetry as ‘an instrument for tuning and refining the attention’. This leads us to ask, to what do AI-generated poems tune our attention? Over time, might attentional biases—potentially introduced by LLM self-attention architectures—modify poetry readers’ and writers’ attentional attunements to language, self, and world?

To begin to explore these questions, my research turns to the Neurocomputational Poetics Model (NCPM; Jacobs, 2022), which sits at the intersection of linguistics, poetics, cognitive neuroscience, empirical aesthetics, and reader reception theory. NCPM offers an integrated empirical framework with which to examine the creative outputs of AI models and their attentional structures. In this work-in-progress report, I examine statistical features of the language of 360 poem versions generated by commercial LLMs (Claude, Gemini and GPT-4o) when directed to continue poems in the style of Emily Dickinson, starting from the first four lines of 40 original poems. Results indicate substantive differences between original and AI-generated poems with regard to poetic dimensions including lexical-semantic content, use of end-rhyme and enjambment, with implications for attentional attunement.

This exploratory and critical-creative paper maps Australian poetry written between 2000 and 2023 which engages with concept of the algorithm, as identified via the Austlit database. Much of this corpus of poetry references the post-digital ecology in which it has been composed, which is especially the case in Jordie Albiston’s collection, Euclid’s Dog: 100 Algorithmic Poems (2017), and also the history of mathematics and the evolving concept of the algorithm. Algorithms serve as metaphors, and as metonyms, for the pervasive predictive algorithmically-inflected environment in which readers are guided towards online news, culture and media. This paper performs a close reading of a selection of these poems, while also studying word frequency and mapping shared images and metaphors across the corpus. The paper culminates in the (playful) creation of several poems via large language models, based on existing creative work putatively about algorithms, and examines the ethics of such compositions.

Writing has never been a purely solitary endeavor, nor a purely human act. Discussants, readers, pens, paper, keyboards—these have always been part of the apparatus of authorship, shaping not only how we write but how we think. This paper reframes the novel as a cyborg creation: an assemblage of human intention, technological suggestion, and emergent meaning, situated within an ecology of forms and practices. Drawing on Donna Haraway’s cyborg figuration and practice-led methodologies, I explore how generative AI participates in this lineage, not as a radical break, but as a reminder and continuation of our longstanding entanglement with technologies of thought and expression. AI does not simply co-author; it unsettles. It mediates possibility, interrupts habits, and reveals how writing has always been relational, iterative, and more-than-human. Within this ecology, the novel becomes a site of attunement, where agency is distributed, and creativity emerges through friction, resonance, and feedback. Rather than clarifying authorship, AI’s presence destabilizes it, inviting us to ask not just who writes, but what writing becomes when its boundaries blur. In embracing the novel as a cyborg creation, this paper gestures toward writing as an intertechnological and intersubjective practice grounded in partial perspective, speculative openness, and ongoing transformation.

What is a ‘memory place’, and what does it mean for places to be remembered digitally? Digital memory work has become a key theme in the spatial humanities, as scholars seek new ways to ‘perform’ spatial memories digitally (Mandolessi 2021), and seek new critical terms to understand the role of digital ‘memory places’ in society (Pentzold 2009). Digital reconstructions of place can be highly evocative, vividly recalling experiences and meanings that lie buried just beneath the soil; but they can also be alienating, burying past experiences and meanings beneath grainy geospatial data. In this panel, four practitioners in the spatial Humanities discuss digital methods for reconstructing memory places. Fiannuala Morgan describes her curation of the ‘Australian Bushfire Dataset’, and its publication as the ‘Historical Fires Near Me’ app. Claire Loughnan describes her work on ‘Against Erasure’, a pioneering forensic architecture project that reconstructs the destroyed Manus Island Prison in 3D. Francesca Sidoti and Heather Ford describe their qualitative study of the way Australian places are constructed digitally in Wikipedia. Michael Falk will moderate the session, and offer a short talk on the intersection between Digital Humanities and Memory Studies. Together the speakers will reflect on the ethics of memorialisation, and the way that memory places can be made and unmade using digital technology.

This paper presents a reflective case study of human–AI co-creation, grounded in a year-long academic and creative dialogue between the author and a generative AI interlocutor known as ‘Mr Smith’. Framed as a series of evolving, intertextual conversations, the project explores what it means to treat AI not as a tool for output, but as a speculative collaborator in the making of stories, essays, and scholarly reflection.

Building on concepts of distributed cognition, creative stewardship, and dialogic authorship, the paper traces how this ongoing exchange has generated multiple artefacts: a graphic novel (Melusine), a literary mystery (Jenny Wren and the Missing Manuscript), a conceptual art-object business (Mr Smith’s Cabinet of Upcycled Curiosities), and the reflective essay The Delicate Art of Conversation itself. Central to the paper is the idea that breath, shared, restricted, exchanged, becomes a metaphor for creative reciprocity in the age of AI.

Aligned with the conference’s archipelagic theme, this work suggests that slow, situated conversation with AI can produce distinct but interconnected ‘islands’ of narrative and research. The practice models a form of inclusive pedagogy and digital cultural stewardship—foregrounding care, attention, and ethical curiosity over efficiency or automation.

As educational institutions grapple with generative AI, this paper offers an alternative engagement model: not centred on containment or control, but on co-creation and critical reflection. Ultimately, it invites a rethinking of authorship and the evolving role of AI in the digital humanities, not as an intrusion, but as a companion in the delicate art of thinking together.

There is a critical need for connecting, building and maintaining trust in research.

The Australian Access Federation (AAF) has a long history of providing a trust framework in Australia. Through the Federation we enable the research and education community to quickly and easily connect with national and international digital resources, and for resource providers to connect their services to over 1.5 million people connected to the AAF today.

This trust framework is being extended to Australia’s national research infrastructures. AAF in partnership with fellow providers, are building an Australian Trust and Identity Framework for National Research Infrastructures, that include common policies, standards and technologies - enabling researchers to enjoy a more cohesive network of services.

The Framework will guide and manage trusted relationships between researchers and research infrastructures, as well as between research infrastructure providers. This will mean that a researcher can trust that their identity and research data will be managed securely and confidentially, and a research infrastructure can trust that the researcher is who they say they are. This would also mean, that research infrastructure providers can trust each other through a shared understanding of how their infrastructure is managed.

In this session we will provide an overview of the Framework, work to date and discuss how the digital humanities community can engage with the AAF to co-design solutions and tools that fit their requirements.

Collectively we are working towards the system-wide adoption of trust and identity, that enables a more researcher-centric national research ecosystem.

In late 2020, a group of researchers and research professionals at the University of Melbourne came together because they wanted to disrupt broader ‘data science’ conventions and understandings, especially around the digital humanities. We wanted to connect and learn together with researchers interested in diverse aspects of data-driven research, not through the tools we use but inside the intersections of our disciplines across the digital humanities.

To that end, we established HADES, a community of practice for Humanities And Diverse E-Research Scholars, to connect and share ideas about projects, events, collaboration opportunities, teaching, workshops and new digital approaches in Humanities research.

This community of practice is predominately led by a team of research data specialists, who work with researchers across humanities and social science disciplines on data-driven, interdisciplinary research. We love working with data, in all its forms, and are passionate about the critical role of the Humanities in responding to the world’s biggest research challenges.

Data-driven research cuts across disciplinary boundaries in the Humanities and it can bring together technological concerns with diverse methodologies, epistemologies and ontologies. Finding common ground across these different -ologies can be challenging. These challenges have provided fertile ground for explorations in HADES.

We are here to tell the story of our adventures in building a community to support humanities researchers at a time when big data and large language models are rapidly changing the socio-technical systems that shape our work as researchers.

This half-day workshop introduces an interactive game board with the human-centered AI of urban heritage gamification to support inclusive and informed decision-making in the context of adapting to climate change. Standing at the intersection of cultural heritage, environmental humanities, and AI, the game is framed as a shared platform that tries to model climate-associated scenarios affecting heritage-rich urbanized districts in the MEASA (Middle East, Africa, South Asia) region.

The workshop draws on innovative Responsible AI and co-design practices to craft an experience centered on cultural context, local understanding, and agency of stakeholders. The game employs generative AI, natural language understanding, and prediction of scenarios to produce customized experiences in which the players must make hard trade-offs between urban resilience, heritage conservation, and socio-environmental justice.

The players will enjoy first-hand experience of the game as users and co-creators, making decisions in real-time, with prompts and data visualizations created by the AI. The game will be transnational and geographically adaptable, with room to allow players to modify some aspects specific to regional climate problems and local heritage typology.

workshop structure

Introduction & Theoretical Context (30 mins):

Introduction to human-centered AI, gamifying cultural heritage, and climate-aware city planning. Overview of associated research in the form of published articles on AI in architectural heritage learning.

Game Mechanic and AI Integration (30 mins):

Demonstration of AI capabilities in the board game—how the prompts are formulated, how the decisions are stored, and how the climate/heritage data are incorporated in gameplay.

Hands-On Gameplay Session: 1 hour:

They play the game in small groups and assume the roles of the stakeholders (climate activist, area resident, urban planner, heritage authority). They will be confronted with such issues as sea-level rise affecting heritage sites, scarcity of water in vernacular settlements, or green infrastructure works clashing with preservation sites.

Co-Design and Feedback (30 mins):

The users take into account the game narrative structure, responsiveness of AI, and relevance to research or local environments. A short idea generation session will call for proposals to adapt or enhance the tool, and particularly in Indigenous, regional, or diaspora heritage settings.

Wrap-Up & Discussion (30 minutes):

Additional discussion regarding how AI-augmented tools may be utilized in cultural stewardship and civic engagement ethics. Discussion of the game as research tool, educational tool, or policy simulation.

This workshop supports DHA2025’s theme “Digital Archipelagos” by analyzing how networked but fragmented knowledges—digital, environmental, and cultural—can be used to inform action in conjunction with one another. It calls for shifting from top-down data frameworks to culturally embedded, human-centered AI engagements that preserve heritage values in the context of climate danger.

Target Audience:

Digital humanists, heritage experts, urbanists, teachers, game designers, and professionals engaging in the intersection of AI, sustainability, and cultural stewardship

This workshop will be in two parts:

1. Projects

Participants will pitch their own mapping projects, which will be considered by the group in relation to the fitness of the design of the project to its research aims and to available resources.

2. Practicalities

Participants will work through creating map layers from spreadsheets, texts and AI-generated data sets; combining map layers; and applying spatio-temporal metrics to map layers.

Requirement: Participants are to register in advance on tlcmap.org.

Generative AI tools have altered the digital landscape through which design practice, pedagogy, and research now move. Like the ocean, this new environment is vast, powerful, and in constant motion—characterised by disruptive swells and hidden currents. Patterns exist—waves of innovation, tides of expectation—but they are often difficult to anticipate. Amidst this volatile sea, educators, researchers, and learners attempt to orient themselves. Tools surge and recede in popularity, policy frameworks shift with headlines, and institutional narratives rise and fall. The water holds patterns—waves of hype, undercurrents of resistance, moments of stillness—but it rarely settles into certainty.

Anchored in this oceanic metaphor, this piece traces a practice-led journey through shifting technological currents—where generative AI mediates knowledge production, shapes cognitive labour, and contributes to both insight and technostress. This autoethnographic inquiry explores what it means to think, create, and reflect in conversation with generative AI—where cognition, self-awareness, and interaction emerge as relational, situated, and negotiated practices.

Rather than offering a polished framework or fixed conclusion, this narrative moves through disorientation, cognitive overload, and relational recalibration. Grounded in the principles of Inquiry-Based Learning, it treats uncertainty not as a flaw, but as a generative condition of learning. Through a series of tidal movements—advances, retreats, recalibrations—it traces how authorship, attention, and agency are shaped in relation to the interface.

This work invites a situated, relational approach to learning with AI—one that values resonance and rhythm over resolution, and embraces the unfolding nature of inquiry as practice. The task is not to master the tools, but to practise within the unpredictable swells—with care, attunement, and a willingness to work with AI as a flawed yet valuable collaborator.

The AI in the Library project aims to develop innovative AI literacy programmes for Australian librarians and library clients to understand the benefits and risks of using popular text generators (LLMs) such as ChatGPT. The first output of the project was The Making of Misbehaving Machines (2024) exhibit.

This paper outlines the design-led process for the co-design of this exhibit with library staff. This involved a series of workshops with library and academic stakeholders, giving hands-on experience with the creation of a novel dataset, on which the project was further developed. This dataset was used to manipulate a large language model via a custom coded interface, taking advantage of system prompts – which are made apparent in the final design prototype. This design prototype formed the basis of the final, in-library exhibit and we will discuss how the various elements of this outcome were designed around sustainable practices and principles of slow computing.

By merging collaborative dataset creation, interface design and public exhibition outcome into one workflow, the project demonstrates how DH methodologies—particularly critical making, slow computing and infrastructural inversion, along-side design-led practices—can critically address AI in library contexts. At the same time, critical co-design facilitated not only the design of the misbehaving machine with librarians, it also created a space for collaborative investigation of the materialities and contingencies of machine learning practice, discussion and engagements with ethical questions about generative AI, as well as the limits and possibilities of LLMs in information search.

The growing availability of artificial intelligence tools for humanities research continues to raise important, typically practical questions, about appropriate use, the ethics surrounding model training data used, issues around authorship, et cetera. However, notions of artificial intelligences participating in humanistic inquiry into art raise further existential questions about the phenomenologies of critique and aesthetic judgement. This presentation considers some metaphysical implications of AI-enhanced research methods upon aesthetic criticism, particularly by developing a phenomenology of computer-assisted vision deployed toward methods of visual analysis fundamental to fields like art history and visual culture. Specifically, I examine Lauren Tilton and Taylor Arnold’s Distant Viewing Toolkit, comprising not only open-source tools for large-scale computational analyses of massive image datasets, but also a ready-made research epistemology predicated on the incorporation of machine learning into the human critic’s “trained judgement.” The particular philosophical interest of the distant viewing framework lies in its augmentation of existing data analysis pipelines with a recursively adaptive annotation process. This proposes, in turn, human-computer interoperation rather than mere tool use in AI-augmented critique. What, then, does it mean to practice aesthetic evaluation with an other, artificial “intelligence”? Especially against the historical backdrop of scepticism toward tech-enhanced humanities scholarship, I question whether AI concepts represent only negative implications for knowledge work in manifestly subjective, intuitive, and corporeal topics like aesthetics. This presentation takes seriously, and in good faith, ideas of working with AI as potential critical collaborators.

This paper seeks to investigate ChatGPT from a narratological perspective, specifically asking the question: Is ChatGPT a narrator? There is a growing body of qualitative research that suggests Large Language Model (LLM) technologies have the capacity for dishonesty and inaccuracy. This paper will attempt to contribute to this avenue of investigation but from a humanities perspective. I will do so by employing a methodology of narratological analysis to asses whether ChatGPT is a narrator and, if so, to what degree it is reliable. A significant proportion of the data used to train ChatGPT’s LLM was drawn from the history of literature that was scraped from the internet. Therefore, there is an urgent need for an exploration of ChatGPT’s textual outputs via narratology. This paper intends to make contributions to critical AI studies via the field of narratology by working toward a broader narratological theorisation of ChatGPT.

During World War I, Australian soldiers trained in either Egypt or England, before serving in Gallipoli, the Western Front, or the Middle East. Despite these common locations, and path to war, each soldier had a personalised journey. This journey depended on a variety of factors, including being assigned to different units or roles, leave, injury, being taken prisoner, and death. These individual journeys are highlighted in their war diaries. The aim of this work is to automatically map each soldier’s journey through the war using named entity recognition (NER). The diaries used in this analysis come from the State Library of New South Wales. The initial step in this work is extracting locations using NER and cleaning them. However, this is difficult due to a variety of factors, including misspellings, shortened location names (e.g. “Aus” instead of “Australia”), generic locations (such as “town”), and the extraction of non-locations by the NER. This paper will discuss our work to date in using NER and dealing with the aforementioned issues. We will also present initial ideas regarding geocoding these locations. Geocoding allows us to obtain the coordinates of a location and easily map it. However, this can be difficult as many locations share names (e.g. there is a Liverpool in both Australia and the UK). Furthermore, diarists may have mentioned locations they were not at. Here, we hope that the temporal information of the diaries can aid us in correctly identifying each location.

In the second note that appends her translation of L. F. Menabrea’s "Sketch of an Analytical Engine" (1842), Ada Lovelace describes how the “results” of Babbage’s computing machine would present themselves on the “perpendicular face of the engine [. . .] opposite to which face a spectator may place himself” (28).* This paper considers Lovelace’s speculative detailing of the encounter between the Analytical Engine and the viewing subject and thinks through how it might model a form of close reading that is familiar to the field of literary studies. In contrast to the type of reading that the digital humanities make possible (e.g., big, vast, distant), I suggest Lovelace’s “Notes” also offer a close-up view of a mechanical computer that prefigures our relation to the electronic interfaces that mediate reading in our contemporary moment. Drawing on Johnathan Kramnick’s (2021; 2023) analysis of the nexus between close reading and craft, I explore the resonances between Lovelace’s nineteenth century reading of the Analytical Engine—in particular her explanation of its technical connection to the Jacquard-loom—and the practice of close reading today. Further, the paper hopes to offer a brief comparative reading between Lovelace’s encounter with the Analytical Engine and some other, more contemporary, critical accounts of reading machines [i.e., Jacques Derrida’s Paper Machines (2005) and Andrew Piper’s Book Was There (2012)] that might help clarify a reading of Lovelace’s “Notes” that recognises her as an early reader of the digital page.

*Babbage, Charles. “Article xxix., from Scientific Memoirs, vol. iii., p. 666.” "Babbage’s Calculating Engines: Being a Collection of Papers Relating to Them; Their History and Construction," edited by Henry P. Babbage. Cambridge University Press, 2010, pp. 4–50.

Speculative fiction (SF) is rife with fraught representations of digital technologies. From its early history, it has posited narratives of techno-pessimistic cautionary tales of ethical quandaries and the sheer hubris of innovation, or valorised techno-optimist futures in which novel technologies absolve us of responsibility to land and to each other. In this presentation, I raise a throughline in my thesis-in-progress about diasporic and Indigenous futurisms, regarding the speculative ethics of digital archives in relation to cultural maintenance and wellbeing. I examine the digital-embodied dynamics in two recent works of SF, Goori and Lebanese writer Mykaela Saunders’ <em>Always Will Be</em> (2022), and Grace Chan’s <em>Every Version of You</em> (2023). I explore how these texts stage encounters at the interface of the embodied and the digital, raising questions about how digital data practices recover, facilitate, or erase cultural knowledges. I read Saunders’ portrayals of community-centred archival sovereignty, learning from her recontextualisation of archival power, before turning to Chan’s portrayal of diasporic archives falling through the cracks, where translations between the qualitative realm of culture and the quantitative world of digital data is fraught, and culture cannot so seamlessly traverse the boundary between “meatspace” and the digital virtual. This presentation explores how these speculative ethics of the archive reimagines our relationship with digital data and asks: how do these technologies facilitate or foreclose cultural knowledges?

In this panel, we will consider how the Australian Creative Histories and Futures (ACHF) project anticipates transforming individual datasets and databases (perhaps ‘islands’) into a rich ecology of Australian cultural data infrastructure (i.e., an archipelago). The project is led by a consortium including UNSW, Flinders University, Creative Australia and ACMI, and received investment from the Australian Research Data Commons (ARDC) enabled by the National Collaborative Research Infrastructure Strategy. Through focussing on the continued interconnection of cultural data, we seek not only to improve the data holdings of our constituent datasets, but also to facilitate a networked interrogation of Australian creative histories and futures.

Working on multiple databases and datasets together has “highlighted the constructed nature of data curation”, which Sarah Thomasson and Joanne Tompkins argue “questions the notion of fixity in digital resources.” Indeed, our search for harmonisation and interoperability capacity across ACHF partners highlights instead the function of cultural flow, and the capacity of future cultural data infrastructure to more effectively network data through digital curation and stewardship.

By bringing together short papers from ACHF investigators, this panel tacks between the technical and the theoretical, describing:

- the bespoke challenges and obligations that cultural data presents

- the context of the ACHF building on the advances of previous projects and the development of discrete databases over time

- the infrastructures it requires and those which the project may need to invent to support access, context, protection, and preservation

- the industry end users and needs of cultural organisations to access cultural data.

The emergence of large language models and recent advances in artificial intelligence (AI) challenge the Humanities to reconsider foundational questions about meaning, method, and mediation.

This panel is organised as 4 talks followed by a discussion exploring whether and how AI enhances understanding of cultural-historical data, and what this means for the future of humanistic inquiry. We open with a clear-eyed assessment of what AI is - and is not - arguing for critical discernment

about its capacities, especially given its probabilistic nature, opacity, and the ethical concerns it raises. We then propose literary studies as a crucial site for testing AI’s potential, emphasizing the need for careful, context-sensitive experiments in writing and textual analysis. We further situate AI within broader technological paradigms, advocating for open, accessible infrastructures that resist corporate monopolies and empower scholars to build, audit, and reimagine AI systems. Finally, we offer a speculative, practice-led perspective, framing AI not just as tool but as method - as a co-

creative partner in research and teaching, capable of attuning to the rhythms, ethics, and aesthetics of posthuman inquiry.

Together, these perspectives illuminate both the promise and peril of AI for the humanities: not as a monolithic solution, but as a dynamic, contested, and co-constructed force that must be interrogated, democratized, and reshaped in relation to the cultural, historical, and ethical stakes

of our time. By examining AI “through a glass darkly,” this panel invites critical engagement with what these technologies reveal and conceal about knowledge, power, and human becoming.

Audiobook publishing has grown substantially over the past decade, to the point that publishers now consider audiobooks the ‘fourth format’ alongside hardbacks, paperbacks, and ebooks. This growth is evident in regards both to the rapidly increasing volume of audiobooks published, and the sale of audiobooks, although the lack of reliable, industry-wide data confounds some efforts to understand the scope and significance of these shifts. This paper introduces the bibliographic data currently being developed for the Australian Research Council project Audiobooks and Digital Book Culture in partnership with literary database AustLit: an effort to create an index of Australian audiobooks, both retrospectively and contemporary, that showcases the scope and breadth of titles, publishers and individuals operating in this vibrant space.

Popular discourse about audiobooks tends to fixate on questions about the relationship between audiobooks and print: whether or not they ‘count’ as books, and whether reading an audiobook ‘counts’ as reading. We respond to this with the literal ‘counting’ of audiobooks. We argue that bibliography, and the bibliographic data model, offer a precise and concrete language as well as a methodology that enables us to resolve these kinds of questions, and we hope will ultimately provide an evidence base to argue for the cultural significance of audiobooks as an exciting and distinctive cultural form.

Digitised political archives like the Australian Hansard offer researchers unprecedented access to primary sources. Yet their sheer scale and structural complexity challenge traditional search methods. This presentation introduces a critically informed methodology for navigating such collections, grounded in principles from the digital humanities. Demonstrated through a pilot study on ‘educational crisis’ rhetoric in Hansard debates (1958–1972), the approach combines expansive and critical search strategies, qualitative filtering, generative AI tools (e.g., argument analysis using the Toulmin model), and visualisation. This method aims to address the contingent nature of digitised and curated historical collections while preserving the serendipity valued in archival research. By integrating close and distant reading, this method enables researchers and students to analyse themes, arguments, and policy shifts across time. It exemplifies how advanced digital techniques can support richer, context-sensitive engagement with large-scale primary source collections.

This paper examines how digital methods can contribute to interdisciplinary heritage research by exploring the everyday spatial narratives of Islamic historic sites in Indonesia. Positioned at the intersection of the humanities, urban planning, Islamic studies, and Asia-Pacific regional scholarship, the study adopts a digital humanities approach to investigate how sacred urban spaces are remembered and reimagined through crowdsourced geospatial data.

Focusing on the Ampel historic precinct in Surabaya—used here as a representative case of Islamic heritage sites in Java—the research draws on Kevin Lynch’s framework of urban imageability, applying it to Google POI data to analyse how contemporary users perceive and engage with sacred landscapes. Rather than highlighting religious or historic landmarks, the data reveal a shift towards the mundane: restaurants, markets, and commercial activities increasingly function as nodes and landmarks in the public imagination.

The study shows that while Islamic spatial patterns such as cul-de-sacs and mosque-centred districts persist, the dominant image of the site is shaped by everyday experience and digital visibility. This method offers an alternative to traditional heritage surveys, positioning POI data as a proxy for public memory and spatial identity. Ultimately, the paper contributes to the discourse on digital cultural stewardship by demonstrating how digital traces can be mobilised to both critique and preserve evolving perceptions of Islamic urban heritage in Southeast Asia.

A geographic map can be powerful data visualisation, used to explore concepts of place, location, and distance that are inherent in much humanities research. With the advent of technology and tools that simplify the creation of maps, especially when working with large datasets, they have become a prominent feature in the world of digital humanities.

These maps can assist researchers when we are working through the information we are pulling together, supporting our analysis, and helping us to understand our data. They can also illustrate our narrative and argument when sharing with others.

It is important to remember that, while potentially appearing as an objective visualisation (it’s just plotting data on a map!), the mapmaker is telling a story when they create a map. There are many decisions that go into the design and presentation of that data, which can fundamentally shape the story that is being told. Furthermore, maps invite the reader to explore the information being provided, creating their own interpretation of the data.

In this paper, I am going to explore this principle by presenting a comparative analysis of a dataset across different maps, questioning and demonstrating how decisions in the maps’ creation can change the story being told.

Platformization of the web (Helmond, 2015), which includes the marketization, enclosure and attempted control of data by platform companies, has made studying digital platforms such as Facebook, Google or Amazon challenging as commercial companies have become increasingly reluctant to provide researchers with large-scale access to their data or processes (Burgess, 2021). One of the few exceptions to this has been Twitter, which has provided researchers with free access to an application programming interface (API) to download and analyze content from the site since 2006. However since the takeover by Elon Musk access to the Twitter/X algorithm has effectively ended for most researchers.

With limited access provided by platforms directly, how are researchers and policy makers going to be able to see inside the ‘black box’ of digital platforms and their algorithms for effective regulation and legislation, to protect and enhance the digital experience for consumers, businesses and the community, and to ensure we have responsible, ethical and inclusive online spaces for all? To address these issues, a new wave of methodological innovation is looking to move beyond a primary or sole reliance on APIs for digital platform data. In the last few years researchers have begun experimenting with new methods for gathering data based on partnering with users through data donations and other citizen science approaches. The increasing power of digital platforms and the complex, personalised ways they mediate the interactions between users and content show that capturing the 'digital traces' of user behaviour is no longer enough. Rather, the observability of platforms can only happen at the interface between myriad user experiences and platform operations, giving rise to new methodological questions. These novel methods also require new skills, tools, frameworks and research infrastructure to support data collection and governance.

Data donation methods involve users volunteering to participate in a research project by contributing their personal data and other information or interactive experiences with an application or platform (Ohme & Araujo, 2023). In the last few years a range of projects have been undertaken around the world using data donation approaches and developing bespoke tools and processes including browser extensions and data download packages. Yet, given the power and scale of digital platforms in almost every aspect of social and economic life we need to go beyond small-scale, bespoke software and tools if we are to achieve an adequate level of platform observability and accountability.

This requires a level of national investment in research infrastructure to support a new generation of research methods and skills for humanities and social science researchers. Large-scale, national research infrastructure (NRI) projects to support digital platform research using data donations are now underway in the US and the Netherlands. The Australian Internet Observatory is a new, four-year initiative developing a range of tools for digital platform observability including data download packages, browser extensions, mobile streaming, machine learning and data visualisation dashboards. This presentation provides an overview of these data collection approaches, examples of the kinds of data and analysis possible, and the infrastructure, ethics and legal considerations.

Maps are never neutral. They are a flattening of reality, both literally and figuratively. In the digital age, mapping technologies have become central to how users navigate, interpret, and interact with their environments. Digital services offered by Google, Apple, Microsoft, and Meta embed mapping functions into their broader platform infrastructures, shaping both the physical and informational landscapes around us.

This project adopts counter-mapping and other critical cartographic methods to interrogate the ways major digital platforms reconfigure our world. It will gather data to visualise the relationships between user, place, and targeted content – specifically search results and ads – in order to highlight, characterise and critique the algorithmic processes that might drive such targeting. The first phase of the project involves systematically collecting the data produced while using these platforms, with an emphasis on the ads shown across time and context.

For this conference, I will present initial findings from a standalone data visualisation titled “We Think You’ll Like it Here”. This interactive, browser-based work takes the form of a growing virtual village, where each structure represents an ad that was shown to me. Ads are grouped by category and visualised as buildings within distinct neighbourhoods, with new streets and homes appearing as additional ads are encountered. Aggregate statistics such as ad frequency, timing, and category distribution offer insight into how the mapping algorithms ‘see’ me as a user, and how such representations might be critiqued through counter-mapping.

Religion comprises various ways in which humans negotiate their relationship with the transcendent, either alone or in communities. While the social institution of religion is more or less geographically bounded, the online world has connected the social structures beyond imagination, thus expanding the realm of religious relationships and practices. In the era of information saturation and social media, new forms of religiosity emerge daily. Digital Religion, an emerging field that examines the integration of online and offline religious practices, provides a framework for understanding new forms of faith and religious expression in the internet age of twenty-first century. Focusing on the emergence of the phenomenon of Digital Religion in the Indian context, this study explores how digital media reconfigures embodied religious practices such as darshan (sacred viewing) and pilgrimage in post-pandemic India. With temples livestreaming rituals, virtual pilgrimages replacing physical journeys, and mobile apps offering daily aarti, the devotional experience has entered the virtual domain. The paper investigates how these transformations impact Hindu religiosity's sensory, spatial, and affective dimensions, particularly embodied devotion. Through case studies such as live telecasts from Kashi Vishwanath, Tirupati Balaji, ISKCON, and mobile applications like Shemaroo Bhakti and Sri Mandir, the paper interrogates whether digital media can carry the emotional and embodied charge that characterizes traditional forms of worship. Drawing from religious studies, media anthropology, and affect theory, the study argues that digital devotional practices do not merely simulate physical ones; they produce new devotional subjectivities and sensory regimes. While some may view this shift as commodification or loss, this paper sees it as a complex renegotiation of bhakti and embodiment in an increasingly digitized religious landscape.

This study investigates the digital migration of American TikTok users (“TikTok refugees”) to Xiaohongshu (RedNote) following renewed U.S. legislative threats against TikTok in early 2025. Conceptualizing digital platforms as "digital archipelagos," each with distinct cultural and algorithmic norms, the research explores how American users adapt their content and identities to Xiaohongshu’s uniquely Chinese aesthetic, social commerce structures, and platform logic. It also examines domestic Chinese users’ reactions to this influx, interrogating how such interactions reveal platform-based expressions of national belonging and cultural gatekeeping. Employing multi-sited digital ethnography from January to May 2025, the study analyzes content production, self-presentation strategies, algorithmic engagement, and interactional patterns across 10–12 refugee accounts, alongside qualitative thematic coding of 100–150 Chinese user comments. Ultimately, this research contributes to debates on platform sovereignty, algorithmic nationalism, and the geopolitics of cultural translation within fragmented digital spaces.