Researchers found that being perceived as white on GitHub generally increases a developer’s odds of having their ideas accepted.
Software developers with names with a white sound could have more satisfaction on GitHub than those whose names are interpreted by users as Black, Hispanic or Asian-Pacific Islander, as per the results of a study recently published.
The results, published within IEEE Transactions on Software Engineering, raise important questions regarding the implications of the lack of diversity on in GitHub and within an open-source community.
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Researchers from University of the Waterloo University of Waterloo analyzed more than 2 million contributions or “pull requests” that were submitted by 365,607 developers on GitHub. Making use of an AI tool known as NamePrism that analyses people’s names according to their perceived ethnicity and race, the researchers discovered that being considered”white” on GitHub generally improves a developer’s chance of getting their ideas accepted. In contrast to developers that are perceived to be Hispanic or Asian Pacific Islanders, the odds increase between 6 to 10 per cent.
“Theoretically this is the only area where there is the possibility of full meritocracy. It’s rare to see someone working in open-source software. You’re unlikely to have had a conversation with them or have an opinion about them. At best you know their name.” explained Mei Nagappan, an assistant professor of computer science at the University of Waterloo who co-authored the study.
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A racial prejudice could still be present in this context which is worrying, given the power that open-source communities like GitHub influence product development, Nagappan said. “If we don’t consider the voices of different people that’s when software becomes designed by and for the same people,” he said.
In addition, GitHub has evolved into a type an online portfolio of software engineers. This means this tendency could have a negative effect on the development careers of developers. “If you’ve contributed to any of the most popular projects, as a fresher you can turn that into a lucrative career with a company,” Nagappan said.
GitHub hasn’t responded to Protocol’s request to comment, and Nagappan explained that the aim of the study isn’t to focus on GitHub specifically and to address the issues within the open-source community in general. Nagappan stated that the findings are based on previous research that has shown some developers who are perceived to be women use GitHub and are less accepted. Acceptance rates also have been discovered to vary based on the developer’s country of birth.
He says it’s true that the NamePrism tool his team utilized does not have the best accuracy in making predictions about people’s race or ethnicity. Researchers did not assign a race or ethnicity to developers in cases where the tool had the highest level of confidence. In all other cases, they classified the race’s perception as “unknown.”
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Although the Waterloo researchers did not shy away from the possibility of attributing this discrimination based on race on GitHub to a specific source, they did observe an overwhelming majority of the developers who contribute ideas to GitHub and the majority of those who respond to these contributions have names that, according to the research were white. Additionally, they discovered those developers viewed by GitHub users as Black, Hispanic and Asian-Pacific Islanders are more likely to get their pull requests approved in the event that the people who reply to them are members of the same ethnic or racial group.
To eliminate this bias, researchers suggest that GitHub use an unblinded or double-blind system similar to how research is evaluated in the academic world. Another suggestion is to need multiple people to evaluate an individual contribution to ensure that no one individual’s biases are impeded.
The issue of how the perceptions of race influence people’s online interactions aren’t exclusive to GitHub. In the year 2000, Airbnb launched a research project known as Project Lighthouse, which also sought to study how racial discrimination can manifest in the social media platform and how users’ names influence other users’ perceptions.
