A system created by MIT researchers could be used to automatically update factual inconsistencies in Wikipedia articles, reducing time and effort spent by human editors who now do the task manually. Wikipedia comprises millions of articles that are in constant need of edits to reflect new information. That can involve article expansions, major rewrites, or more routine modifications such as updating numbers, dates, names, and locations. Currently, humans across the globe volunteer their time to make these edits. In a paper being presented at the AAAI Conference on Artificial Intelligence, the researchers describe a text-generating system that pinpoints and replaces specific information in relevant Wikipedia sentences, while keeping the language similar to how humans write and edit.

The English Wikipedia has over 6 million articles, and the combined Wikipedias for all other languages contain over 28 billion words in 52 million articles in 309 languages. It's an incomparably valuable resource for knowledge seekers, needless to say, but one that requires pruning by the over 132,000 registered active monthly editors. In search of an autonomous solution, researchers at MIT developed an AI and machine learning system that updates inconsistencies in Wikipedia articles. Thanks to a family of algorithms, it's able to identify and use the latest information from around the web to produce written sentences corresponding to articles that reflect updated information. The algorithms in question were trained on a data set containing pairs of sentences, in which one sentence is a claim and the other is a relevant Wikipedia sentence.