AI-Augmented Research in the Social Sciences & Humanities

AI Stack Setup Sprint

Issam Ourrai ()
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Issam Ourrai: GRANEM - Groupe de Recherche Angevin en Economie et Management - UA - Université d'Angers - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement

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Abstract: This course equips researchers and advanced students in the Social Sciences and Humanities with a rigorous, practice-grounded framework for integrating artificial intelligence across the scholarly research lifecycle. It is not a survey of AI tools. It is an epistemological training in AI-augmented inquiry: how to deploy generative AI and semantic search in ways that are methodologically sound, ethically defensible, and disciplinarily appropriate. The 24-hour format is structured as six cumulative sessions, each comprising theoretical framing, a live demonstration, two hands-on application labs, a structured debrief, and an optional stretch challenge. Students leave every session with a tangible artefact that contributes to their final research portfolio. The course emerges from active PhD research practice at GRANEM (Université d'Angers) — every technique is currently in use in real manuscript preparation, conference submission, and systematic literature review workflows across France, Morocco, and the United States.

Keywords: AI; Social Sciences &; Humanities; Applied research; Lab Fab (search for similar items in EconPapers)
Date: 2026-03-05
Note: View the original document on HAL open archive server: https://hal.science/hal-05610625v1
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Published in Doctoral. AI-Augmented Research in the Social Sciences & Humanities, France. 2026

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