Google's linguistic prosthesis have become common mediators between our intended queries and their actual expressions. By correcting a mistyped word or extending a small string of letters into a statistically plausible continuation, Google offers a valuable service to users. However, Google might also be transforming a keyword with no or little value into a keyword for which bids are more likely. Since Google's word bidding algorithm accounts for most of the company's revenues, it is reasonable to ask whether linguistic prosthesis are biased towards commercially more interesting expressions. This study describes a method allowing for progressing in this understanding. Based on an optimal experiment design algorithm, we are reconstructing a model of Google's autocompletion and value assignment functions. We can then explore and question the various possible correlations between the two functions. This is a first step towards the larger goal of understanding how Google's linguistic economy impacts natural language.