Caroline Meinhardt, Thomas Mullaney, Juan N. Pava, and Diyi Yang | How Can AI Support Language Digitization and Digital Inclusion?

That might mean few websites exist in that language, for example, or keyboards don’t have the necessary characters. Language communities excluded from digital systems can only participate minimally in a world increasingly mediated by technology. They also can’t generate enough data needed to be represented in AI. And without access to AI, communities face further barriers to digital participation.

Empowering digitally disadvantaged language communities requires holistic progress on a range of foundational language tools (from script encoding to keyboard layouts) and supporting language tools (from grammar checkers to accessibility features). Progress on this language digitization work is often slow due to chronic underfunding and a lack of coordination. 

AI has the potential to scale and accelerate language digitization. In recent years, scholars have increasingly leveraged AI — and especially natural language processing tools — to sidestep major bottlenecks in the field, particularly when it comes to compiling, organizing, and reviewing digital records.

In this seminar, researchers from HAI and SILICON will present key findings from their recent white paper charting the varying ways AI tools and techniques can support language digitization work and digital inclusion efforts more broadly. They explain how AI alone can’t solve the field’s fundamental bottlenecks and highlight what is needed to advance language digitization and digital inclusion in the age of AI while centering community needs and contexts.