What Makes a Fairness Tool Project Sustainable in Open Source?
Sadia Afrin Mim, Fatemeh Vares, Andrew Meenly, Brittany Johnson
TL;DR
Open-source fairness tools are increasingly important for mitigating AI bias, but their long-term viability varies. The authors build and extend a GitHub-based dataset of 61 fairness tools, applying keyword-driven discovery, manual validation, and a Random Forest maintenance classifier to assess engagement, maintenance, and lifespan. They find a diverse landscape with industry-backed tools showing stronger engagement and maintenance, while many projects become inactive or archived within a few years; domain-specific tooling emerges as a key lever for stability. The work provides a publicly available dataset and actionable insights to improve visibility, domain alignment, and the sustainability of fairness interventions in open source.
Abstract
As society becomes increasingly reliant on artificial intelligence, the need to mitigate risk and harm is paramount. In response, researchers and practitioners have developed tools to detect and reduce undesired bias, commonly referred to as fairness tools. Many of these tools are publicly available for free use and adaptation. While the growing availability of such tools is promising, little is known about the broader landscape beyond well-known examples like AI Fairness 360 and Fairlearn. Because fairness is an ongoing concern, these tools must be built for long-term sustainability. Using an existing set of fairness tools as a reference, we systematically searched GitHub and identified 50 related projects. We then analyzed various aspects of their repositories to assess community engagement and the extent of ongoing maintenance. Our findings show diverse forms of engagement with these tools, suggesting strong support for open-source development. However, we also found significant variation in how well these tools are maintained. Notably, 53 percent of fairness projects become inactive within the first three years. By examining sustainability in fairness tooling, we aim to promote more stability and growth in this critical area.