How can we mitigate the risks that come with machine translation, and who holds the responsibility for them?
In order to mitigate the risk of low-resource MT exacerbating inequalities, there needs to be close collaboration with marginalized language communities. Even tech giants with seemingly unlimited funding, resources, and expertise recognize the need for local linguists’ involvement in the process of improving and expanding their massive state-of-the-art MT systems.
Research teams from Google, Meta (Facebook), and latvia mobile database Microsoft all emphasize that incorporating low-resource languages into multilingual neural machine translation models necessitates substantial input from local linguists. But free-to-use online NMT services still come with a number of significant risks that end users aren’t necessarily aware of. And even though these free MT services are increasing their coverage of low-resource languages, it would be much better to develop MT systems that marginalized language communities can operate somewhat independently.
If MT experts want to assist local communities from the outside, they could jumpstart or guide the creation of low-resource MT systems, then promote independent use by offering workshops or developing open-access training materials, such as INTERACT’s crisis translation tutorials or the recently published book Machine translation for everyone (2022). Any external support would aim to help marginalized language communities eventually achieve independent management of MT systems.
Ultimately, the responsibility of mitigating MT risks would fall on the communities themselves, but that increased responsibility would go hand in hand with an increased ability to control their own development.