- Generative AI may have unintentionally driven away some of the highest-quality “expert” contributors to sites like Stack Overflow, as users increasingly adopted trained tools based on their feedback.
- The problem arises because such users feel that their experience and effort are not rewarded, and AI often offers the same solutions at a faster pace.
- The move is not limited to online coding communities, but threatens to spread to other areas such as classrooms, corporate workplaces, and scientific communities.
Research from the University of Auckland into the demise of Stack Overflow in recent years points to an increasingly worrying trend in the software community: the best, or most skilled, contributors are leaving in droves.
Arguably bridging the gap between most entry- and mid-level programmers and some of the best in the business, AI could actually be accelerating the latter’s exit from online communities as they feel their efforts are no longer as valued as they once were.
Stack Overflow has seen a nearly 76% decline in monthly questions posted since the arrival of ChatGPT in 2022, indicating that both new and existing users are leaving the site.
A much broader problem than just Stack Overflow?
Stack Overflow’s problems and the reason for its decline were multifaceted; However, many users felt that the site and some of its most talented contributors incurred a degree of arrogance.
This, coupled with strict moderation that many called “moralistic,” meant that users who found a viable option would inevitably leave the platform.
ChatGPT and its AI alternatives became considerably more flexible and, over time, doubled as search engines for many coders with routine, repeatable queries, even as AI increasingly handled issues like syntax issues better than before.
This, in turn, reduced the number of questions asked on the platform and, despite a ban on generative AI enacted shortly after ChatGPT went online, led to a loss of responders that may prove impossible to replace in the long term.
The problem may no longer be limited to online coding communities; The researchers indicate that it could be extended to other areas, such as classrooms, offices and other research communities, where low-effort answers are more difficult to discern from those of subject matter experts thanks to retrained and constantly evolving AI models.
“If everyone can create a good quality answer or result using AI, some people may think, ‘Why should I make an effort to share my experience and participate?'” explained the study’s editor, Dr. Kenny Ching.
Ching called this “signal compression” as expert and non-expert solutions became harder to separate, even as it became less rewarding to be an expert on topics that AI could also easily influence.
However, the question that comes to mind here is simpler: if AI was trained on user-contributed data, and an increasingly smaller amount of it exists on platforms like Stack Overflow, where will the next knowledge reset take us in terms of AI capabilities?
While future AI models won’t get “dumber,” so to speak, they could turn to different training avenues, such as Slack chats, Discord servers, or even users currently asking them the same coding-related questions they were once asked on Stack Overflow.
Whether this replaces experts who no longer wish to contribute or simply makes AI more error-prone over time, thanks to how its feedback loop works, is an interesting question in a society that finds it increasingly difficult to discern between AI and human responses.
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