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A new study that used artificial intelligence to analyze the contributions of more than two million developers on GitHub found that users with block names are more successful on the platform (Issi Lapovsky/Protocol).

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A new study that used artificial intelligence to analyze the contributions of more than two million developers on GitHub found that Black-labeled users were more successful on the platform, and White-labeled software developers were non- were more successful on GitHub than developers. His name? Like black.

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According to a recently published study, software professionals with white names are more likely to outperform on GitHub than developers with Black, Latino and Asia-Pacific names.

The findings, published earlier this year in the journal IEEE Transactions on Software Engineering , highlight important concerns about the impact of a lack of diversity on GitHub and the open source software community.

Researchers at the University of Waterloo studied more than two million proposals or “questions of interest” submitted by 365,607 developers. The researchers found that whitelisting on GitHub often increases a developer’s chances of getting an idea approved. The discovery was made using an artificial intelligence technology called Numprism, which checks people’s names for race and ethnicity. This increases these opportunities by 6-10% compared to developers in Latin America or Asia Pacific.

“This is the only place where, in theory, there is a real meritocracy. Open source software does not have a human presence. You probably haven’t met them or refused them. At least you know his name,” said paper co-author Mei Nagapa. Professor of Science. at the University of Waterloo.

Nagapan said there is a racial bias in this case because of the influence of GitHub and other open source communities on product development. “If we ignore the ideas of others, the same people will make the software,” he warns.

And since GitHub is designed as a portfolio of sorts for software professionals, this bias can be detrimental to a developer’s career. “Besides, if your contribution is recognized even in a major project, you will be able to build a successful career in the company from it,” Nagpan added.

In response to GitHub’s comment log request, Nagapan explained that the purpose of this research is not to focus on GitHub, but to address issues in the open source community as a whole. They call it speed, serpentineness. The developer’s country of origin has been shown to affect acceptance rates.

He felt that his team’s use of the nomenclatural prism method for species prediction was not accurate enough. The researchers indicated the developer’s race or ethnicity only if they trusted the device. He calls everyone of the development race “unknowns”.

Many of the developers who posted the idea on GitHub, and many of the people who commented on the idea, are named by the Waterloo researchers as white, although they refrained from giving specific reasons for the racial bias on GitHub has done it. They found that developers who self-identified as White, Hispanic and Asian-Pacific Islander were more likely to agree to ask questions when the respondents to the attractiveness questions were of the same race or ethnicity There is.

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