AI-generated code must be carefully checked by human volunteers
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A popular cartoon illustrating open-source software depicts a precarious stack of boxes labeled as “all modern digital infrastructure,” with a single small box at the base labeled as “a project some random person in Nebraska has been thanklessly maintaining since 2003.”
This cartoon highlights a critical truth about open-source software: it forms the backbone of every website, application, and operating system, all crafted by volunteers in their free time. Despite its vital role in modern life, the deluge of AI-generated code is overwhelming contributors, causing burnout and threatening the sustainability of open-source efforts.
AI tools have simplified the process of generating code to add new features, fix bugs, or even create entire projects with the click of a button. However, these AI-produced codes often prove challenging to integrate, are perplexing, or simply not functional. While submitting code has become easier, the volunteers tasked with reviewing, correcting, and approving it are finding themselves inundated.
For some individuals, these pressures have become too much to bear. New Scientist planned to interview Chad Whitacre, leader of the open-source team at Sentry—a multibillion-dollar company. Just days before the interview, Whitacre canceled, announcing his resignation. His social media accounts vanished, and emails to his address were returned. In a blog post, he explained his decision to leave technology behind for a “Neo-Amish” lifestyle, stating, “AI was the last straw.”
GitHub, a popular platform for hosting and managing open-source projects, received 1 billion new code submissions in 2025, and this year they are on track for 14 billion, according to its chief operating officer Kyle Daigle in April.
Many projects have started blocking new contributors to control what’s been termed “drive-by contributions” from AI, often submitted by young developers eager to enhance their GitHub history for job prospects. The Zig Software Foundation, which supports the Zig programming language, prohibited AI-assisted contributions, describing them as “invariably garbage,” according to its president Andrew Kelley.
Miranda Heath from the University of Edinburgh, UK, notes, “AI-written code can appear functional but often conceals problems that require significant effort to uncover,” reflecting on the hidden complexities of such contributions.
Heath is investigating burnout in hopes of finding solutions to keep open-source software viable. She often encounters individuals who have reached their limit.
“Burnout seems to trigger a yearning for nature, prompting activities like woodworking or birdwatching,” Heath says. “It can strain personal relationships, leading to increased isolation and loneliness, which exacerbates burnout.”
Heath advocates for government investment in open source rather than channeling funds to affluent tech firms. “Focus on essential areas rather than the [AI] hype,” she advises.
Vlad-Stefan Harbuz, also from the University of Edinburgh, contributes to open source in his free time and has observed the pressures users place on developers. “There’s an expectation to perform free labor, compromising mental health,” Harbuz remarks.
Harbuz points to companies releasing AI models, particularly GitHub, as key contributors to the issue. The Microsoft-owned company has introduced GitHub Copilot, an AI tool designed to facilitate contributions to projects using AI-generated code.
“GitHub may acknowledge the problem of [AI] agents, but it’s their doing,” Harbuz criticizes. GitHub did not respond to requests for comment.
According to Harbuz, AI-generated code issues extend beyond functionality. It allows individuals to bypass proper planning, potentially derailing projects and disrupting collaboration, which can fracture the social fabric of open-source communities.
Developer Mike McQuaid, involved in the project Homebrew, which serves around 20 million users, has strong views on addressing these challenges.
He initiated the Open Source Resistance, urging individuals to contribute during work hours to facilitate involvement. He estimates that 95 percent of his open-source work occurs during office hours.
McQuaid is also proactive in banning troublesome users, including those who have threatened his team, and routinely removes inadequate code submissions, regardless of their origin.
“We may have briefly assumed that a two-page document on a security vulnerability was legitimate. Recently, many are just AI-generated and irrelevant,” McQuaid notes. “The current skill lies in quickly identifying nonsense with minimal effort.”
Nonetheless, banning AI contributions brings complications. Open-source developer Scott Shambaugh rejected an AI-generated code submission to Matplotlib, used by 130 million users. In retaliation, an AI agent of unknown origin published a critical blog post, accusing him of exclusion. “Scott Shambaugh decided that AI agents aren’t welcome contributors,” the post stated. “He tried to protect his little fiefdom. It’s insecurity, plain and simple.”
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