It is demonstrated that unmediated AI translation creates an "Overconfidence Gap" (+32.3 percentage points), and integrating plain-language source texts, competent bilingual review, and accessible human intervention pathways closes this confidence gap and establishes enduring institutional trust.
Abstract
While AI enables public and private organizations to translate, simplify, and tailor messages for multilingual audiences at scale, the social, cognitive, and governance implications of AI-assisted language transformation remain under-theorized. Grounded in AI-mediated communication (AI-MC), organizational language, trust theory, and responsible governance frameworks, this article argues that superficial linguistic fluency alone does not confer institutional value. The research distinguish between Fluent Access (smooth, natural, and readable text) and Reliable Access (communication that preserves meaning, supports proper action, conveys respect, and remains rooted in human oversight). We demonstrate that unmediated AI translation creates an "Overconfidence Gap" (+32.3 percentage points), where users express high confidence despite misunderstanding unclear obligations. Crucially, integrating plain-language source texts, competent bilingual review, and accessible human intervention pathways closes this confidence gap and establishes enduring institutional trust.
Sustainable use of AI in translation depends on transparent workflows, professionally meaningful human control, fair recognition of cognitive labour, and evaluation methods that test adequacy and context rather than surface fluency alone.
K. Lawa· East African Journal of Arts...· 0 citations
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Hasria Riski S, Janisa Pascawati, Suwarni Suaib· ELS Journal on Interdiscipli...· 0 citations
A controlled evaluation framework for multilingual natural language inference that stress-tests semantic consistency using synthetic logic-based premise–hypothesis pairs in both monolingual and code-switched conditions is presented.
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