How language gaps constrain generative AI development

Article by Regina Ta and Nicol Turner Lee: “Prompt-based generative artificial intelligence (AI) tools are quickly being deployed for a range of use cases, from writing emails and compiling legal cases to personalizing research essays in a wide range of educational, professional, and vocational disciplines. But language is not monolithic, and opportunities may be missed in developing generative AI tools for non-standard languages and dialects. Current applications often are not optimized for certain populations or communities and, in some instances, may exacerbate social and economic divisions. As noted by the Austrian linguist and philosopher Ludwig Wittgenstein, “The limits of my language mean the limits of my world.” This is especially true today, when the language we speak can change how we engage with technology, and the limits of our online vernacular can constrain the full and fair use of existing and emerging technologies.

As it stands now, the majority of the world’s speakers are being left behind if they are not part of one of the world’s dominant languages, such as English, French, German, Spanish, Chinese, or Russian. There are over 7,000 languages spoken worldwide, yet a plurality of content on the internet is written in English, with the largest remaining online shares claimed by Asian and European languages like Mandarin or Spanish. Moreover, in the English language alone, there are over 150 dialects beyond “standard” U.S. English. Consequently, large language models (LLMs) that train AI tools, like generative AI, rely on binary internet data that serve to increase the gap between standard and non-standard speakers, widening the digital language divide.

Among sociologists, anthropologists, and linguists, language is a source of power and one that significantly influences the development and dissemination of new tools that are dependent upon learned, linguistic capabilities. Depending on where one sits within socio-ethnic contexts, native language can internally strengthen communities while also amplifying and replicating inequalities when coopted by incumbent power structures to restrict immigrant and historically marginalized communities. For example, during the transatlantic slave trade, literacy was a weapon used by white supremacists to reinforce the dependence of Blacks on slave masters, which resulted in many anti-literacy laws being passed in the 1800s in most Confederate states…(More)”.

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