Inferring The World's Gender and Ethnic Diversity using Personal Names
Burkina Faso is a multi-cultural and diverse country with a rich history. In this article, we would like to explorer how personal names can be interpreted to reflect regional, ethnic appartenance within the country. Then we would like to illustrate how the use of a personal name can affect a black-box Artificial Intelligence – such as OpenAI’s DALL-E. This is a first article in our series of blog posts with tag #thisnamedpersondoesnotexist.
DebunkEU.org analysts Aleksandra Michałowska-Kubś and Jakub Kubś conducted an analysis of social media posts related to sanctions imposed on the transit of goods to Kaliningrad. They used NamSor machine learning classification to assign a likely country of origin for the social account names (real or fake).
We’ve used a non-supervised clustering algorithm to identify Russian (Ivanov, Popov), Korean (Kim, Pak) and other names in Kazakhstan and differentiate them from Kakakh names (AZAMAT ABDRAKHMANOV, ERLAN AHMETOV, AIGUL ABDRAKHMANOVA / AYGUL ABDRAKHMANOVA …)
Romanization of Japanese names is easy, but translating a Japanese name back to its original form in Kanji with the correct probabilities is hard. There are many Kanji variants for a single Japanese name in its romanized form.
We’ve released a new version of the opensource Java Naive Bayes Classifier (JNBC), so it can now run on RocksDB
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