可以在源代码上运行人工智能，使用提示“查找低于平均水平的脏话率文件”吗？
因为“包含更多脏话的代码质量更高”，这意味着有很多人查看了这段代码，而查看这段代码的人越多，平均来说能找到的脏话就越多。
如果这是真的，那为什么不通过在开源代码上运行人工智能来进行测试，并给它一个提示：“找到低于平均脏话率的文件”（为了节省字数，这个提示被缩短了）呢？
此外，某人可以制作一个程序，添加补丁，将随机的脏话分布到开源代码中，概率与人类输入的相同。
我只是想问问是否有人愿意去做这个，因为我负担不起运行昂贵的人工智能，或者将这些随机的脏话注释添加到所有开源代码项目中，然后等待，因为许多人可能会拒绝我的补丁。如果有人愿意做这件事，那就太好了。
是的，这属于“通过模糊性来保证安全”，但这可能会让人工智能不再提交关于“这段代码存在漏洞”的问题，即使它并不存在（参见curl作者对人工智能生成问题的回应），因为它会想：“嗯，脏话的平均数量，代码一定不错，反正我去别处看看。”
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Because “code with more swear words is higher quality”, meaning lots of humans looked at that code and the more humans look at that code, the more swear words could be found on average.<p>If this is true, then why not put it to the test by running an A.I. on open source code and giving it the prompt of “Find below-avg swear rate files” (This prompt was shortened to save on tokens.)<p>Also, someone could make a program add patches that would distribute random swear words into open source code with the probability of a human typing it in.<p>Just asking whether someone wants to run this, because I can’t afford to run expensive A.I. or add these randomized swear word comments to all open source code projects and then wait as many might refuse my patches. I’d like for someone else to do this if they want to, because if you want to, then cool.<p>Yes, this is “security through obscurity”, but this might discourage AIs from submitting issues about how “this code is vulnerable” when it’s not (see curl author’s response to AI created issues) because it’ll go: “Hmm, average amount of swear words, must be good code, anyway, let me look somewhere else.”