Unveiling Inclusiveness-Related User Feedback in Mobile Applications

Inclusiveness problems are widespread and visible in user feedback: Analysis of 22,000 posts across Reddit, Google Play Store, and X revealed that users frequently report inclusiveness concerns about popular apps, indicating this is a systemic issue affecting major software platforms rather than isolated cases.

Five main categories of inclusiveness issues exist: The research identified that inclusiveness problems fall into five distinct areas—Algorithmic Bias, Technology, Demography, Accessibility, and Other Human Values—suggesting that responsible AI and inclusive design require attention across multiple dimensions, not just one or two.

Users are actively communicating their exclusion: The study found that affected users are already discussing inclusiveness problems on public platforms, meaning companies have accessible data about who feels excluded and why—they need better systems to listen and act on this feedback.

AI tools can help identify inclusiveness issues at scale: GPT-4o-mini successfully identified inclusiveness-related posts in user feedback, suggesting that companies can use automated systems to monitor and flag potential inclusiveness problems before they affect large user populations.

Current software development overlooks inclusiveness: The research emphasizes that inclusiveness "is frequently overlooked during software development," indicating that responsible AI requires intentional processes and tools to surface and prioritize diverse user needs throughout the development lifecycle.