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The Artificial Intelligence (AI) revolution has become a reality in today’s world and its importance for linguistics was recognized very early. Despite its unprecedent surge and integration into various academic fields including language teaching and translation, surprisingly, little work has been done by scholars in advancing discussions on the profound impact of the AI on the diversity of widely available languages in both developed and developing world. Africa is linguistically diverse continent with about one third of the world’s languages that are vastly underrepresented in the global digital data pool. AI translation machine is supported in only 25 languages out of over 2000 languages in the continent. The paper deploys homomorphism model of AI theory to interrogate the natural language data drawn the African languages to present the current and future challenges, opportunities and potential for developing AI algorithms that could fit neatly into the translation of the African languages. Most of the discussions in the paper focuses on the seven patterns of the AI, the usage and implementation of AI algorithms in the translation science. The research findings show some of the complexities of the African languages in which their syntactic categories have multiple corresponding semantic objects. Unlike English, the findings also reveal that syntactic operation in the African languages do not always have one corresponding semantic operation as postulated by the homomorphism model of AI theory. the study contributes to scholarly literature by stressing the limits and opportunities that relate to using AI in translation science and supplying input from NLP algorithms practitioners to expand the AI applicability operation in the translation science.
Ahmed Mohammed Bedu (Sun,) studied this question.