Advancing Sustainable Agricultural Practices in Africa with AI: Interdisciplinary Approaches to Inclusivity and Resilience
Artificial intelligence (AI) is increasingly positioned as a transformative tool in agriculture, yet existing solutions primarily cater to large-scale farms in the Global North, often overlooking the socio-cultural and infrastructural realities of smallholder farmers in Africa. This workshop interrogates how AI can be reimagined to enhance sustainability and resilience in African agriculture by centering farmer agency, cultural knowledge and community and social practice. Building on HCI and CSCW scholarship, we bring together researchers, AI practitioners, NGOs, agronomists, and community stakeholders to explore locally grounded, inclusive, and ethically responsible AI applications. Key themes include trust and skepticism in AI, the role of local languages and epistemologies in model design, strategies for decolonizing AI development and integrating indigenous knowledge and the application of methodologies such as co-design, and participatory AI. The workshop directly aligns with AfriCHI 2025’s theme, "Re-centering African Wisdom in HCI," by fostering interdisciplinary dialogue that embeds African perspectives into AI research and practice. We welcome a variety of contributions including papers, case studies and hands-on demonstrations. Outcomes include a collaboratively developed research agenda, and a white paper synthesizing insights from the workshop. By prioritizing African epistemologies and farmer-centered innovation, this workshop aims to shift AI discourse, ensuring that AI-driven agricultural technologies are not only technically robust but also culturally resonant and socially just.
Authors
- Samuel C. Maina (ORCID: https://orcid.org/0000-0002-0754-2553)
- Jacki O’Neill (ORCID: https://orcid.org/0000-0002-3065-0579)
- Merja Bauters (ORCID: https://orcid.org/0000-0001-8501-5751)
- Steven Sam (ORCID: https://orcid.org/0000-0002-4353-6118)
- Stephanie Nyairo (ORCID: https://orcid.org/0000-0001-7847-4116)
- Najeeb Gambo Abdulhamid (ORCID: https://orcid.org/0000-0003-4519-2379)
- Abiodun Afolayan Ogunyemi (ORCID: https://orcid.org/0000-0002-1851-0442)
- Mark Perry (ORCID: https://orcid.org/0000-0003-1573-1255)
- Millicent Ochieng (ORCID: https://orcid.org/0000-0003-4769-7039)
- Rikin Gandhi (ORCID: https://orcid.org/0009-0004-9958-5113)
- Mercy Muchai (ORCID: https://orcid.org/0009-0009-3528-5775)
- Jona Rephisti (ORCID: https://orcid.org/0009-0005-4866-0424)
Institutions
- Microsoft (United States) (US)
- Tallinn University (EE)
- Digital Science (United States) (US)
- Microsoft Research (United Kingdom) (GB)
- Brunel University of London (GB)
Publication Details
- Published
- 2025-11-04
- DOI
- https://doi.org/10.1145/3757232.3757277
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00