35%的网站文本由AI生成,但未发现其降低事实准确性或风格多样性。
The Impact of AI-Generated Text on the Internet

- 基于互联网档案馆数据,用先进检测器分析2022-2025年网页文本
- 2025年中,35%新发布网站被判定为AI生成或辅助,此前为零
- 公众担忧与实证结果不符,使用频率低者更易相信负面假设
人工智能生成和辅助文本在互联网上的泛滥引发对其语义多样性、风格多样性和事实准确性的担忧(常被归入‘死网理论’)。然而,由于缺乏对实际生成比例的认知,这些疑问难以解答。为此,我们利用互联网档案馆构建2022至2025年间具有代表性的网站样本,并应用最先进的AI文本检测器进行分析。结果显示,截至2025年中,约35%的新发布网站被分类为AI生成或辅助,而在此前(2022年底之前)这一比例为零。我们还发现部分假设具有统计显著性:如互联网上AI文本增加与语义多样性下降呈负相关,且与积极情绪盛行正相关。但并未发现其导致事实准确性或风格多样性下降的统计显著证据。值得注意的是,这与公众认知相悖——我们在用户研究中发现,多数美国成年人相信上述四项假设。不使用或极少使用AI的人群,以及对AI持负面看法者,更倾向于相信这些负面影响。
原文摘要 · Abstract (English)
The proliferation of AI-generated and AI-assisted text on the internet is feared to contribute to a degradation in semantic and stylistic diversity, factual accuracy, and other negative developments (sometimes subsumed under the Dead Internet Theory). What has hindered answering these questions is that it has not been understood just how much of the internet is actually AI-generated or AI-edited. To this end, we construct a representative sample of websites published on the internet between 2022 and 2025 using the Internet Archive, and apply a state-of-the-art AI text detector on them. We find that by mid-2025, roughly 35% of newly published websites were classified as AI-generated or AI-assisted, up from zero before ChatGPT's launch in late 2022. We also find statistically significant evidence for some of the identified hypotheses; for example, that increases in AI-generated text on the internet correlate negatively with semantic diversity and positively with the prevalence of positive sentiment. We do not, however, find statistically significant evidence supporting the hypothesis that an increased rate of AI-generated text on the internet decreases factual accuracy or stylistic diversity. Notably, this diverges from public perception, which we measure in a user study, where the majority of US adults turned out to believe in all four of the above-mentioned hypotheses. Individuals who do not use AI or use it infrequently tend to believe in these negative impacts more than those who use it frequently; similarly, individuals who hold negative views of AI tend to believe in these hypotheses more than those with favorable views of the technology.
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