Inferring The World's Gender and Ethnic Diversity using Personal Names
The gender gap in STEM subjects has been widely studied and it is a known fact that women are under-represented in mathematics, especially in the most reputable mathematics journals. One aspect of this gender gap, which has not yet been analysed specifically for mathematics is gender imbalance in papers’ reference lists.
We’ve used DALL-E text-to-image AI to generate portraits, based on names shared by a large number of people. This is our second blog post in our series with tag #thisnamedpersondoesnotexist, exploring how text-to-image AIs interpret personal names. We believe this project can illustrate the complexity of personal names interpretation, at the crossroads of ethnography, sociology, sociolinguistics, geography, history and, more recently machine learning.
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.
CORD is a direct messaging tool for finding work. CORD’s corporate blog offers some well researched articles and recent data on representation of different genders and ethnic minorities in the Tech industry.
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).
Researchers looked at how managers communicate with financial analysts during earnings conference calls, specifically focusing on the managers’ use of
A paper just published in the British Journal of Surgery (Oxford) sourced innovative data from Dimensions AI, a large linked scientific publications dataset, and NamSor, our name gender classification tool, to explore the current state of gender diversity in global surgery – based on the top 1000 most published researchers.
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 …)
What’s in a name? Artificial intelligence was used to classify the personal names of entrepreneurs and beneficial owners of companies in eight European countries and derive unique insights into the Contribution and Challenges of Ethnic Minority Businesses in Europe.
For International Women’s Day, one blog post and one large study by European Commission illustrate how NamSor can be used to produced an analysis of the gender gap in a particular field, using open databases.
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