For years, Stack Overflow and similar Q&A platforms has been the go-to reference for any developer stuck on a problem they couldn’t figure out. If you were stuck, a Google search almost would lead you to the exact same problem " question " already asked on Stack Overflow and most cases also answered by other human developers. That massive pool of real-world questions and answers became one of the most important training fuels for AI — especially in programming.
Fast forward to today
With AI tools on the rise like chatGPT, Claude, and copilot, Google searches are declining, and Q&A platforms like Stack Overflow are seeing a sharp drop in traffic — falling toward levels we haven’t seen since 2008.
Less traffic means fewer human questions. Fewer questions mean less fresh, high-quality data. At the same time, AI-generated content is flooding the internet.
That creates a critical problem, future generation AI tools will be trained on content produced by other AI tools — essentially recycling knowledge instead of creating it. This phenomenon, known as "Model Collapse".
Final thought
Human-generated content won’t disappear, and fresh edge-cases will always arise, but if this trend continues, the long-term impact on AI quality is worth serious attention. Every one of us must answer a critical and ethical question: Where will the next generation of training data come from if we stop contributing?
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