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The advent of AI-powered coding assistants, such as ChatGPT, has reshaped how developers approach problem-solving, reducing reliance on traditional community-driven platforms like Stack Overflow. This study explores the decline in user engagement on such platforms, examining its impact on the volume and quality of shared knowledge and its broader implications for the developer ecosystem. Using Stack Overflow as a case study, we analyze the shift in user behavior following the release of ChatGPT in November 2022. Our findings show a significant decline in site traffic, question submissions, answers, and votes, indicating a preference for AI-driven tools over community forums. This trend raises concerns about the sustainability of collaborative knowledge-sharing platforms. The study highlights the trade-offs between the efficiency of AI tools and the collaborative value of community-driven platforms, suggesting the need for strategies that balance both. Ultimately, the research emphasizes the importance of preserving knowledge freshness and fostering innovation in an AI-enhanced coding landscape.

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Generative AI-Driven or AI-Assisted Software Code Generation and the Decline of Community Knowledge Sharing: Challenges and Future Prospects

  • 会议论文

  • 发表日期：

    2026年

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  • Muhammad Mahad Umair,
  • Patrick Mukala

摘要

The advent of AI-powered coding assistants, such as ChatGPT, has reshaped how developers approach problem-solving, reducing reliance on traditional community-driven platforms like Stack Overflow. This study explores the decline in user engagement on such platforms, examining its impact on the volume and quality of shared knowledge and its broader implications for the developer ecosystem. Using Stack Overflow as a case study, we analyze the shift in user behavior following the release of ChatGPT in November 2022. Our findings show a significant decline in site traffic, question submissions, answers, and votes, indicating a preference for AI-driven tools over community forums. This trend raises concerns about the sustainability of collaborative knowledge-sharing platforms. The study highlights the trade-offs between the efficiency of AI tools and the collaborative value of community-driven platforms, suggesting the need for strategies that balance both. Ultimately, the research emphasizes the importance of preserving knowledge freshness and fostering innovation in an AI-enhanced coding landscape.