The WSJ has an interesting article on how language effects how we think. I particularly liked the example of a indigenous language where anything you discuss involves absolute cardinal directions (north, south, east, west etc.). You literally can't say "There is an ant on one of your legs". Instead you say something like "There's an ant on your southwest leg." To say hello you'd ask "Where are you going?", and an appropriate response might be, "A long way to the south-southwest. How about you?" If you don't know which way is which, you literally can't get past hello.
Dr. Kevin Lim reviewed Search Engine Society , a book which explores the effect search engines have on politics, culture and economics. He is not your typical reviewer since he also mentioned in the book, due to his recording a large part of his life using cameras (one he wears, another at his desk points at him) while a GPS device tracks his movements.
Google throws its weight behind Voice Search by Stephen Lawson discusses how voice search is based on statistical models of what sequences of words are most likely to occur, and how they train a new language model. Another example of that would be Midomi , a web site where you search for music by singing a fragment of the song.
Multilingual Search Engine Breaks Language Barriers discusses how the uses the pivot language UNL to return a precise answer in the language in which the question was formulated. This seems to be still a research project, with some related projects such as LACE trying to extract data from parallel corpora as a cheaper way to populate a lexical database.
XBRL Across The Language Divide by Jennifer Zaino discusses how XBRL (eXtensible Business Reporting Language) may be one of the few areas that benefits from the Monnet project , which attempts to "provide a semantics-based solution for accessing information across language barriers". It tries to "build software that breaks the link between conceptual information and linguistic expressions (the labels that point back to concepts in ontologies) for each language." When that works, it makes it easier and quicker to perform analytics across multiple languages.
The Cross-Language Evaluation Forum (CLEF) is working on infrastructure for testing, tuning and evaluation of systems that retrieve information in European languages, and benchmarks to help test it. One of its papers for example, compares lexical and algorithmetic stemming in 9 languages using Hummingbird SearchServer .