Examples
This is the heart of the wiki. Instead of prescribing rules which cannot possibly fit the wide heterogeneity of community goals, we work from concrete examples: tools, collaborations, and approaches, each with its upsides and downsides.
We came to this work from very different perspectives and our goal was never to agree on whether a given tool or project is, on the whole, "good" or "bad." We didn't reach that kind of consensus, and we don't think you should have to either.
What we found, though, is that narrower statements are much easier to agree on. "Consulting the speaker community before publishing was the right call." "Deploying the tool with no documentation of how it worked was a mistake." These are situated, specific judgments about particular choices, not verdicts on the example as a whole. Each example below is an attempt to put terms into a concrete context and collect the specific statements we could stand behind together.
We hope these examples can be a resource for communities, researchers, and practitioners to have more productive conversations about this topic.
| Name | Summary |
|---|---|
| Chatbots with Human Likeness | Systems that give a tool a real person's face, voice, or words — powerful and personal, but raising questions of consent, context, and cultural taboo. |
| Glosbe | A large crowd-sourced multilingual dictionary. It is transparent and community-sourced, but its data can be wrong or contributed without a community's consent. |
| Ojibwe Chat | A public Ojibwe translation chatbot that confidently returns incorrect output. |
| Putting Data Online | Putting community language materials online — weighing access against protection and consent. |