There are about 7,106 languages spoken worldwide. Out of those, about 915 languages are considered to be dying. For instance, the Koro language in India, spoken by only a handful of elderly people, is on the verge of extinction. The death of a language typically occurs when a more broadly or popularly spoken language takes over the one not spoken commonly. Once younger generations move onto popular languages and are no longer taught their native language, the risk of death for the language is high. Often, a new language is considered more valuable because it better connects people with the world.
When a language isn’t broadly spoken, it is very limited in the digital world, further limiting its use. Additionally, it isn’t available on large-scale translation services like Google Translate. As a result, the language ends up significantly underserved, putting it at greater risk.
Despite the bleak situation, there is a glimmer of hope in the form of artificial intelligence (AI). The rapid advancements in AI technology have opened up new possibilities for language preservation. However, it’s important to note that AI is not a panacea. It has its limitations, and there are significant obstacles that could impede its progress. Let’s delve into how AI is being leveraged to save dying languages and the challenges it faces in this noble endeavor.
Using AI to preserve dying languages is a noble endeavor with immense potential but not without challenges. One key obstacle is more digital resources to train AI models for lesser-known languages. Compared to widely spoken languages like English or Spanish, which have abundant online content, dying languages lack the digital footprint necessary for practical AI training. As a result, AI translation tools for these languages often rely heavily on human input for accuracy improvement.
This reliance on human input poses several challenges. First, finding individuals proficient in dying languages can be difficult due to their dwindling speaker populations. Even when proficient speakers are found, soliciting feedback can be labor-intensive, mainly since most AI platforms depend on volunteer contributions rather than paid input. This lack of compensation may deter some fluent speakers from participating, potentially hindering the progress of language preservation efforts.
Moreover, the companies behind AI platforms could commercialize volunteer contributions, leading to the development of viable translation services for dying languages. While the cultural value of preserving languages may initially motivate volunteers, the prospect of commercialization may alter their willingness to contribute. This raises questions about the sustainability of volunteer-based language preservation efforts in the long term, as it could potentially exploit the goodwill of volunteers and the cultural value of the language.
Despite the daunting challenges, the importance of preserving dying languages cannot be overstated. These languages are not just words, but carriers of invaluable cultural and linguistic heritage. AI technologies offer promising solutions for their conservation, but they cannot do it alone. The key to success lies in collaborative efforts, working hand in hand with communities, providing incentives for volunteer participation, and ensuring ethical use of language data. By doing so, we can overcome these obstacles and together, safeguard linguistic diversity for future generations.