Understanding the impact of the alphabetical ordering of names in user interfaces: a gender bias analysis

TL;DR

This paper empirically analyzes how alphabetical ordering of first names in user interfaces can introduce gender bias, especially in Brazilian and Spanish datasets, highlighting the need for bias-aware design.

Contribution

It provides the first empirical evidence of gender imbalance in alphabetical name listings across multiple countries, emphasizing potential bias in interface design.

Findings

Gender imbalance is more pronounced in Brazilian and Spanish name datasets.

Alphabetical ordering can lead to gender bias in top-k displayed names.

Bias varies across countries and depends on list size k.

Abstract

Listing people alphabetically on an electronic output device is a traditional technique, since alphabetical order is easily perceived by users and facilitates access to information. However, this apparently harmless technique, especially when the list is ordered by first name, needs to be used with caution by designers and programmers. We show, via empirical data analysis, that when an interface displays people's first name in alphabetical order in several pages/screens, each page/screen may have imbalances in respect to gender of its Top-k individuals.k represents the size of the list of names visualized first, which may be the number of names that fits in a screen page of a certain device.The research work was carried out with the analysis of actual datasets of names of five different countries. Each dataset has a person name and the frequency of adoption of the name in the country.Our analysis shows that, even though all countries have exhibit imbalance problems, the samples of individuals with Brazilian and Spanish first names are more prone to gender imbalance among their Top-k individuals. These results can be useful for designers and engineers to construct information systems that avoid gender bias induction.