Assessing the Adequacy of Artificial Intelligence Tools for African Narratives: Towards Responsible and Culturally Inclusivity

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dc.contributor.authorIsiaka, Mope Rafiu
dc.contributor.authorJimoh, Muhammed Kamaldeen
dc.contributor.authorAbdulsalam, Olaniyi Sulaiman
dc.contributor.authorOlanrewaju, Olaitan Toyyib
dc.date.accessioned2026-05-16T19:46:44Z
dc.date.available2026-05-16T19:46:44Z
dc.date.issued2025-11-28
dc.description.abstractThe increasing reliance on Generative Artificial Intelligence (GenAI) across diverse domains has sparked global attention regarding its adequacy and accuracy. Specifically, its capacity to capture and represent African narratives remains underexplored. Most AI systems are developed within Western contexts fail to align with Africa's diverse sociocultural realities, thereby perpetuating biases, misrepresentation, and the erasure of indigenous knowledge systems. This study critically evaluates the performance of the ChatGPT, DeepSeek, Gemini, and Perplexity large language models in processing and representing African narratives. Using a mixed-methods approach, it incorporates systematic assessments of selected popular AI tools and qualitative input from domain experts in African linguistics, culture and technology. A survey involving academic staff from state and federal universities in Nigeria’s North-Central region contributed 24 relevant prompts, which were combined with 15 research-generated prompts, totalling 39. These prompts were executed concurrently on the selected AI models, and the resulting outputs were evaluated by subject-matter experts for accuracy, adequacy, and credibility. Perplexity consistently achieved the highest ratings across all parameters, whereas the other models displayed varying degrees of effectiveness. Notably, the findings revealed a “white as default” bias and a tendency to prioritise content from Eastern and Southern Africa. The study also identified serious gaps in the handling of African languages, idioms, and culturally embedded expressions, stemming from the poor representation of low-resource languages, limited infrastructure, skill deficiencies, and weak governance. In response, this study proposes roadmaps for responsible AI development tailored to African contexts, advancing ethical practices and amplifying African voices in the digital era.
dc.identifier.issn24085162
dc.identifier.urihttps://kwasuspace.kwasu.edu.ng/handle/123456789/7238
dc.language.isoen
dc.publisherFUW Trends in Science & Technology Journal
dc.titleAssessing the Adequacy of Artificial Intelligence Tools for African Narratives: Towards Responsible and Culturally Inclusivity
dc.typeArticle
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