About
About the Workshop
The integration of digital humanities (DH) and artificial intelligence (AI) is transforming the production of knowledge in African Studies, offering new opportunities for innovative analysis, dynamic visualisation and cross-cultural research. This shift has the potential to reimagine cultural heritage, widen access to diverse narratives, and amplify marginalised voices. However, it also raises urgent questions regarding equitable access, the representation of African languages, and the suitability of methodologies. In order to navigate this rapidly evolving landscape and influence the future of the field, a targeted scoping exercise is crucial.
The workshop, "Digital Humanities and Artificial Intelligence in African Studies: Towards Sustainable and Equitable Practices", will address these developments. The urgency arises not only from accelerated advances in AI and its potential use in African Studies but also from the risk that African voices will again be sidelined, entrenching existing biases. By bringing together scholars, independent researchers and practitioners from Africa, Europe, and beyond—across DH, AI, metadata, linguistics, literature, art, and history—the event will foster North–South and South–South dialogue at the intersection of African epistemologies and digital methods. Our aim is to move from description to design: to chart practical pathways and partnerships for the ethical and equitable development of DH and AI in African Studies and across the continent.
DH has evolved dramatically from the punch cards of the 1930s (Zaagsma 2024) to today's AI-driven approaches (Meadows and Sternfeld 2023), expanding the academic toolkit and improving accessibility alongside established methods. The pandemic accelerated this shift (Araújo, Aguiar and Ermakova 2024). Building on earlier digitisation efforts that made millions of documents accessible, recent technologies now support large-scale textual analysis, pattern detection, and cross-cultural exploration (Balnaves 2024; Jaillant 2024).
Yet the same digitisation pipelines that enable AI-ready data are themselves political (Zaagsma 2023). Choices about what to digitise, how to describe it, and who controls access shape training corpora and, ultimately, what AI can "see". Institutions in the Global North often hold materials from the Global South and deploy technical solutions with limited sensitivity to local contexts (Aiyegbusi 2018), inviting critiques of a recurring "digital saviour" logic (Limb 2007; Shringarpure 2020) and renewed calls for digital sovereignty and equitable participation (Kévonian et al. 2022; Layne 2022). In short, the politics of digitisation preconfigure the possibilities and limits of AI in African Studies.
Language and epistemic representation compound these issues. Current large language models (LLMs) underrepresent African languages, and digital scholarly infrastructures remain optimised for English, reinforcing Anglophone paradigms and Western epistemologies (Fiormonte, Ricaurte and Chaudhuri 2022; Spence and Viola 2024). Closing these gaps through improved datasets, benchmarks, and adaptation would open new opportunities for African Studies and enable genuinely multilingual, cross-cultural scholarship.
To realise this potential, AI must be adapted and deployed responsibly. Here, "implementation" refers to integrating AI into research and institutional workflows, not merely training models. Foundation models and open-source tools support local adaptation, but deployment must confront entrenched inequalities in funding, infrastructure, bandwidth, language support, and skills development. Market-driven DH can exacerbate disparities, privileging tools and design choices from the Global North and raising questions of legitimacy and sustainability in resource-constrained settings (O'Sullivan 2022; Holmes, Jenstad and Huculak 2023). Moreover, open access must be balanced with community rights and epistemic justice.
Nevertheless, DH in African Studies has already reshaped how African histories, cultures, and knowledge systems are documented and analysed. Early initiatives such as the Transatlantic Slave Trade Database often framed African history through an Atlantic lens; newer projects foreground African experiences and challenge dominant epistemological frameworks (Hart 2020). Diverse approaches now thrive—from spatial analyses of historical landscapes (Fourshey, Gonzales and Saidi 2021) and computational literary studies, to multilingual ontological frameworks (Eisenhuth et al. 2023), the digital documentation of material culture (Gagliardi 2022), and community-driven archives—emphasising collaborative knowledge production and alternative conceptualisations.
Innovative, African-based initiatives such as the African Ajami Library and Open Restitution Africa signal the field's dynamism, supported by expanding institutional infrastructures such as the Centre for Digital Humanities at the University of Lagos, the South African Centre for Digital Language Resources (SADiLaR), and the Network for DH in Africa. South Africa and Nigeria (Opeibi 2021), in particular, have moved beyond basic digitisation to develop sophisticated programmes that address knowledge representation and classification, a trajectory reflected in the recent "African Digital Humanities" special issue of Reviews in Digital Humanities (Guiliano et al. 2024).
While recent initiatives on digital sovereignty in Africa have centred on policy, regulation, and digital rights, this workshop shifts attention to methodological practice. It asks how DH methods and AI transform research in African Studies, and how we can design, evaluate, and sustain these methods under African conditions. We move from governance about AI to practice with AI. Researchers across the continent already prototype multilingual, multimodal, and community-responsive workflows that change how we study African languages, texts, material culture, and place. To address these transformations systematically, our discussions are organised around three interconnected thematic axes that capture both technical innovations and epistemic shifts.
Thematic Axes
Transforming Research Methods through AI and Digital Tools in African Studies
This axis asks a fundamental question: how are AI and DH methods changing the study of African cultures, languages, and histories? Participants will present concrete uses of AI to analyse multilingual texts, employ computer vision to study visual culture and historical artefacts, and develop digital mapping to trace cultural movements and connections. We will evaluate what works for different kinds of African cultural materials, identify adaptations required for local contexts, and specify where computational approaches can complement—rather than replace—interpretive scholarship. The goal is clear: practical guidance for integrating these methods while preserving the interpretive richness that defines the humanities.
Building Sustainable Research Infrastructures from African Perspectives
Moving beyond policy discourse, this axis asks what it takes to build and sustain digital research capacity within African institutions and communities. We will examine practical obstacles—limited connectivity, unstable funding, and scarce training data for local languages—and showcase South–South collaboration models that have navigated these constraints. Participants will share strategies for developing tools that utilise available resources rather than assuming high-end infrastructure. Key questions include how to keep research outputs accessible to the communities being studied, how to train the next generation of African DH scholars, and how to secure sustainable funding that does not depend solely on institutions in the Global North. The focus is on concrete, scalable approaches to durable capacity.
Centring African Knowledge Systems in Digital Research Design
This axis poses a methodological challenge: how can digital research tools respect and incorporate African ways of knowing? Rather than retrofitting existing techniques to African materials, we explore how African epistemologies can shape the tools themselves. Case studies will show community knowledge informing database structures, oral traditions testing text-centred analytical frameworks, and local classification systems improving standard metadata schemas. We will consider protocols for culturally sensitive materials, interface design that does not privilege European languages, and criteria to ensure that AI systems trained on African data primarily serve African research needs. Here, decolonisation moves from critique to construction.