This study investigates the role and effectiveness of machine translation (MT) tools in translating English medical texts into French within the Algerian professional and academic context. It compares the outputs of three widely used MT systems with human translations, focusing on lexical accuracy, grammatical correctness, pragmatic meaning, and contextual coherence. The methodology involves a qualitative comparative analysis of selected medical texts translated by both human experts and MT software, followed by expert evaluation using an analytical framework that considers multiple levels of linguistic equivalence. Results demonstrate that while MT provides rapid and accessible translation solutions, it frequently fails to capture the complex terminology, syntactic nuances, and contextual subtleties essential in medical discourse. Common issues include literal word substitutions, grammatical errors, loss of professional tone, and inadequate handling of cultural and situational context. Human translators (HT), by contrast, consistently deliver more precise and contextually appropriate translations, leveraging their linguistic competence, domain knowledge, and experiential understanding. The study highlights the cognitive and pedagogical implications of these results, emphasizing the need to integrate MT literacy into translation and medical training programs. It advocates for viewing MT as a complementary tool that supports rather than replaces HT, encouraging critical post-editing and context-aware use. Furthermore, the research underscores the importance of developing localized terminological resources and fostering human–machine collaboration to enhance translation quality. In the broader Algerian multilingual landscape, where Arabic, French, and English intersect within education and professional domains, the study reveals that MT’s limitations reflect not only technological constraints but also sociolinguistic and ideological tensions. Overall, this research contributes to understanding how MT tools function as cognitive and linguistic mediators, informing best practices for their application in specialized translation contexts and supporting informed language policy and pedagogy in multilingual societies.
Benhamlaoui et al. (Thu,) studied this question.