Generative AI can adversely impact news publishers by lowering consumer demand. It can also reduce demand for newsroom employees, and increase the creation of news "slop." However, it can also form a source of traffic referrals and an information-discovery channel that increases demand. We use high-frequency granular data to analyze the strategic response of news publishers to the introduction of Generative AI. Many publishers strategically blocked LLM access to their websites using the robots.txt file standard. Using a difference-in-differences approach, we find that large publishers who block GenAI bots experience reduced website traffic compared to not blocking. In addition, we find that large publishers shift toward richer content that is harder for LLMs to replicate, without increasing text volume. Finally, we find that the share of new editorial and content-production job postings rises over time. Together, these findings illustrate the levers that publishers choose to use to strategically respond to competitive Generative AI threats, and their consequences.

翻译：生成式人工智能可能通过降低消费者需求对新闻出版商产生不利影响。它还会减少对新闻编辑室员工的需求，并增加新闻“垃圾内容”的创作。然而，它也可以成为流量引荐源和信息发现渠道，从而增加需求。我们使用高频粒度数据分析了新闻出版商对引入生成式人工智能的战略回应。许多出版商利用robots.txt文件标准战略性地阻止了大型语言模型对其网站的访问。通过双重差分方法，我们发现，与不阻止相比，阻止生成式AI机器人的大型出版商经历了网站流量的减少。此外，我们发现大型出版商转向更难被大型语言模型复制的更丰富的内容，而未增加文本量。最后，我们发现新的编辑和内容制作岗位招聘份额随时间上升。综合来看，这些发现揭示了出版商为战略性地应对生成式人工智能的竞争威胁而选择使用的杠杆及其后果。