Islam's 'Peripheries': Digital Humanities, Algorithmic Analysis, and AI in West Africa and Central Asia

This research project (2026-2027), co-directed with Aksana Ismailbekova, uses artificial intelligence (AI) to unlock valuable historical collections about Islamic communities in West Africa and Central Asia. These archives contain thousands of documents in multiple languages (including Russian, Arabic, Hausa, and Tajik) that have remained largely inaccessible due to their volume and complexity.

The project focuses on two often-overlooked regions: West Africa (post-1960s) and Central Asia (colonial/early Soviet era and documents from the Tajik civil war, 1992-97). By comparing these regions, we explore how Islamic discourse and responses to modernity developed in different contexts.

AI-Driven Comparative History

Using AI technologies, we aim to:

1. Develop systems that recognize multilingual text and identify key information across diverse scripts and layouts.
2. Create a chatbot that answers complex questions using documents across languages, enabling researchers to ask natural language questions like "How were notions of 'reform' debated differently in these contexts?"
3. Ensure accessibility by prioritizing open-source, low-resource AI models, promoting equitable research practices that don't rely on high-resource institutional walls.

This approach will reveal previously hidden connections and demonstrate how diverse Islamic communities navigated major historical transitions. All findings and tools will be made freely available, benefiting researchers worldwide, especially in West Africa and Central Asia.

Unlocking "Peripheral" Archives

Our work focuses on two unique, multilingual archives housed at Leibniz-Zentrum Moderner Orient (ZMO):

• The Islam West Africa Collection: Covering post-1960s Islamic discourse and public engagement.
• The Reinhard Eisener Collection: Documenting colonial and early Soviet governance in Central Asia, including materials from the Tajik civil war.

By combining expertise in regional studies, history, and AI, this project will uncover important historical insights while creating new methods for studying complex archives globally.