The Perspective of Software Professionals on Algorithmic Racism

TL;DR

This study explores software professionals' understanding of algorithmic racism, revealing awareness of its effects but a lack of consensus on solutions, emphasizing the need for combined technical and social strategies.

Contribution

It provides empirical insights into software practitioners' perspectives on algorithmic racism and proposes integrated strategies to mitigate its impact.

Findings

Practitioners are aware of algorithmic racism's effects.

No consensus on effective solutions among professionals.

Training on structural racism is recommended.

Abstract

Context. Algorithmic racism is the term used to describe the behavior of technological solutions that constrains users based on their ethnicity. Lately, various data-driven software systems have been reported to discriminate against Black people, either for the use of biased data sets or due to the prejudice propagated by software professionals in their code. As a result, Black people are experiencing disadvantages in accessing technology-based services, such as housing, banking, and law enforcement. Goal. This study aims to explore algorithmic racism from the perspective of software professionals. Method. A survey questionnaire was applied to explore the understanding of software practitioners on algorithmic racism, and data analysis was conducted using descriptive statistics and coding techniques. Results. We obtained answers from a sample of 73 software professionals discussing their understanding and perspectives on algorithmic racism in software development. Our results demonstrate that the effects of algorithmic racism are well-known among practitioners. However, there is no consensus on how the problem can be effectively addressed in software engineering. In this paper, some solutions to the problem are proposed based on the professionals' narratives. Conclusion. Combining technical and social strategies, including training on structural racism for software professionals, is the most promising way to address the algorithmic racism problem and its effects on the software solutions delivered to our society.