San Francisco-based start-up Primer has used its machine learning algorithm Quicksilver to create 200,000 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.
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.