Reading this story brings to mind the history of algorithms in the field of machine translation. Early attempts at the problem attempted to explicitly define the rules of converting between tongues using meticulously laid out systems of vocabulary and syntax. This approach proved untenable, in part due to the complex and ever changing nature of language. Modern systems such as Google Translation make use of machine learning algorithms that are fed large amounts of source material and computationally discern relationships between them.

I wonder if a similar approach could be taken with language construction. Instead of spending 25+ years fleshing out the details of a language in painstaking detail, computer programs could be devised that, using large amounts input, determine the most "efficient" means of expressing information. The approach would not only be far less labor intensive, it could also accommodate the rapidly evolving nature of language, for example adding to its "dictionary" in response to new phenomena in need of naming.