University libraries flooded with AI bots, threatening public access
| Source: HN | Original article
University libraries are overwhelmed by AI data‑scraping bots, causing site slowdowns and crashes that threaten public access to resources.
University libraries across the Nordics and beyond are grappling with an unprecedented surge of automated data‑scraping bots, according to a wave of reports this week. The bots, driven by AI developers seeking large‑scale text corpora for model training, are flooding open‑access repositories, overwhelming servers and, in some cases, knocking entire collections offline. Library staff describe the traffic as “persistent streams of unruly bots” that “bombard us with trying to grab as much material as possible,” says Jill Strykowski, a cataloguing specialist.
The onslaught matters for several reasons. First, it threatens the public’s ability to access academic, historical and government documents that libraries traditionally make freely available. Second, the sheer volume – more than two billion connection attempts recorded in a single 30‑day window – forces institutions to divert staff and technical resources to traffic classification and defensive measures, diverting attention from core services. Third, the bots are not merely crawling web pages; some probe library card numbers, check out digital items, and even scan physical books, with reports of rare volumes being damaged or destroyed in the process. The episode spotlights a growing tension between open‑access policies and the commercial appetite of AI firms for training data.
Looking ahead, librarians are likely to push for stronger safeguards, ranging from stricter authentication for digital lending to coordinated legal action against unauthorized scraping. Policymakers may consider regulations that balance open scholarship with the protection of cultural heritage. Meanwhile, AI companies could face pressure to adopt more transparent data‑acquisition practices or to contribute resources that help libraries harden their digital infrastructure. The unfolding dispute will test how the research ecosystem adapts to the data demands of next‑generation AI.
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