San Francisco-based start-up Primer has used its machine learning algorithm Quicksilver to create 40,000 summaries for Wikipedia, aiming to rebalance its gender bias. Research has revealed only 18% of the biographies on the site are about women, while between 84% and 90% of contributors are men. Primer's John Bohannon said the algorithm scours existing news reports and other forms of data to compile summaries, seen as a jumping-off point for Wikipedia editors to then clean up or expand them. The company is also working with Google to build an online encyclopedia that will be searchable by gender, ethnicity, age and location.
San Francisco-based start-up Primer has used its machine learning algorithm Quicksilver to create 40,000 summaries for Wikipedia, aiming to rebalance its gender bias. Research has revealed only 18% of the biographies on the site are about women, while between 84% and 90% of contributors are men. Primer's John Bohannon said the algorithm scours existing news reports and other forms of data to compile summaries, seen as a jumping-off point for Wikipedia editors to then clean up or expand them. The company aims to make Quicksilver multilingual and expand to profile politicians.