Structural Silence

Bengali is the seventh most spoken language in the world — approximately 242 million native speakers and 285 million total speakers, a 1,400-year literary history, and UNESCO recognition of International Mother Language Day, commemorating those who died defending their right to speak it.

When you try to build an AI tool that teaches in Bengali, you discover the entire infrastructure of modern machine learning was designed around a different language. That is not a coincidence. It is a policy outcome.

Bengali by the Numbers: Where Speakers and AI Resources Diverge

The Double Burden: Why Language of Instruction Matters

This is not only a technical problem.
It reflects deeper asymmetries in resources, infrastructure, and design.

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If you use this work, please cite:

Paper Citation

            @article{roy2026structural_silence,
              title   = {Structural Silence: When AI Infrastructure Fails Speakers of Underrepresented Languages},
              author  = {Roy, Avijit and Roy, Proma},
              year    = {2026},
              journal = {SSRN Electronic Journal},
              publisher = {Elsevier BV},
              doi     = {10.2139/ssrn.6522858},
              url     = {https://doi.org/10.2139/ssrn.6522858}
            }
          

Poster Citation

          @misc{roy_2026_structural_silence_poster,
            author       = {Roy, Avijit and
                            Roy, Proma},
            title        = {Structural Silence: When AI Infrastructure Fails
                            the World's Underrepresented Languages —
                            Poster Presented at ILA 2026},
            month        = may,
            year         = 2026,
            publisher    = {International Linguistic Association (ILA)},
            doi          = {10.5281/zenodo.19991979},
            url          = {https://doi.org/10.5281/zenodo.19991979}
          }