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by jp_monteiro
1173 days ago
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People usually perceive a trade-off between precision and ease of use. I think that, if done naively, natural language interfaces will indeed lead to imprecise and inconsistent answers. But it doesn't have to be like this. From my experience building Veezoo[1], natural language interfaces for data can be very powerful for business users as long as it explains back understandably what the query does, allows to modify them by clicking and it relies on a set of vetted dimensions/measures, e.g. in a semantic layer. Also, UX solutions[2] like Autocompletion (for discovery and disambiguation) are way more important for these more specific use cases of natural language interfaces than for an open-domain chatbot like ChatGPT. This usually helps a lot with the issues you've mentioned. There are many questions that are hard to write a query for but are simple to formulate in a relatively precise way (or allow the user to correct it by clicking). This is especially useful for the average business user that doesnt know SQL or struggles with "precise" tools for data analytics. [1] https://www.veezoo.com [2] https://www.veezoo.com/reliability-and-accuracy/ |
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