Hidden Gender Bias in Big Data as Revealed Through Neural Networks: Man is to Woman as Work is to Mother?

Abstract

Social events become big data. The big data analysis becomes knowledge about society. If big data is biased, the bias is transmitted to the analysis and to our knowledge. We propose here a tool to discover gender biases and, potentially, eliminate them from big data before analysis. We use the neural network analysis and the words embedding.

This is the first time that this technique is tested on a body of data in Spanish. As proof of concept, the neural network was fed with half of Wikipedia in Spanish. More than 28 million words.

We describe the techniques and specialized knowledge necessary to discern gender and it is evaluated whether it is possible to divide the analysis work into externalizable microtasks.