WILL AI KILL LANGUAGE LEARNING?
WILL AI KILL LANGUAGE LEARNING?
In a rapidly evolving digital landscape, the question of whether artificial intelligence (AI) will render foreign language learning obsolete looms large. Marc Fleischmann and Andrej Sokolow explore this intriguing topic in their recent article, "Is AI about to end the need to learn foreign languages?" featured in The Star, dated Sunday, March 3, 2024 (link below).
Drawing inspiration from the iconic British sci-fi novel "The Hitchhiker's Guide to the Galaxy," which introduces the concept of a Babel fish—a creature capable of instantaneously translating alien speech—Fleischmann and Sokolow argue that with the advancements in machine learning, particularly in the realm of simultaneous speech translation systems, the prospect of eliminating the arduous task of learning a foreign language seems increasingly plausible. One also remembers Star Trek and their ‘Universal translater’… Is this already a reality?
In the article, the author mention linguist Anatol Stefanowitsch, a professor at Freie Universität Berlin, who sheds light on the transformative potential of AI in language translation. He highlights the existing capabilities of computer-based speech recognition and translation, noting the progress made by instant speech translator apps on modern smartphones, notably Samsung. Stefanowitsch emphasizes the ultimate goal of achieving real-time machine translation with minimal delay—a feat made possible by recent technological advancements.
To counterbalance the argument, the authors state that the Goethe-Institut, a German cultural association dedicated to promoting learning German, offers insights into the distinction between translating one language into another and attaining foreign language proficiency. According to the authors, the Goethe Institut argues that while technological innovations have facilitated tasks such as translating in near-instant time, challenges remain in achieving accurate translations of complex sentences, idiomatic expressions, and cultural nuances. According to Fleischmann and Sokolow, an overarching concern is the potential homogenization and pauperization of language as well as the erosion of cultural diversity resulting from widespread adoption of AI-driven translation systems.
My personal background in Sociolinguistic Research has taught me that these fears have little foundation. Linguistic diversity is highly linked to the human need for identity. This uniformizing pressure stemming from AI language learning will be met with ‘localised social identification’ forces which are as strong if not stronger than standardizing ones. Furthermore, AI will have a hard time constantly updating its databases as localized forms and accents develop and change quickly. Take the example of French for instance. French has been highly standardized in the last 100 years by political will and policies, but hasn’t been able to ‘crush’ the birth of highly localized forms of ‘inner city’ French (français des banlieues) since at least the 1980s. Indeed since that period, the children of migrants born in France haven’t been able to ‘fit in’ the French model of integration and therefore have had a need for new identity. Some of these ‘inner-city’ forms become adopted by the mainstream which in turns prompts inner-city speakers to drop them and invent new ones to distinguish themselves from the mainstream (see Jamin, 2005).
So will AI kill language learning needs? I agree with the authors that while AI tools may complement traditional language learning methods and are useful for ‘transactory exchanges’, they cannot fully replicate the depth, diversity and authenticity of human communication. Yes, AI holds promise in revolutionizing language learning and communication, but the value of human connection and cultural understanding remains irreplaceable.
Happy learning!
Mike
Storyinteracters.com
Jamin, M. (2005). Sociolinguistic Variation in the Paris Suburbs, PhD thesis. University of Kent at Canterbury.
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