Knowledge sharing is an essential part of internet culture, and it is enabled by sharing licenses that allow people to access content and create derivative works. However, the rise of generative AI and large language models is threatening the principles of knowledge sharing.

The large-scale collection of online content, which has become commonplace with the advent of generative AI and large language models, is threatening the principles of knowledge sharing. This data, which is collected by web scrapers, is used to develop AI models. However, this content is often not fully authorized by the creators, which raises concerns about the principles of knowledge sharing and is contrary to the idea of knowledge sharing.

Generative AI and large models have unprecedented data requirements. The market is gradually reaching a consensus that whoever has the data owns the world, and data is the key to competition for large models. There are two main sources of AI training data: self-collection and crawling. Self-collecting data requires a lot of manpower, material resources, and time, and is expensive. Scraping data, on the other hand, is relatively easy to obtain. In 2023, the amount of data collected by web scrapers worldwide will reach 190 billion records, of which more than 80% is unauthorized. Web scrapers typically use programming to automatically access websites and obtain user information or data. This behavior not only violates user privacy but also causes huge economic losses to enterprises. It is estimated that in 2024, the illegal collection of data by web scrapers will continue to increase.

Measures to Combat Large-Scale Plagiarism in News Website

In the face of this problem, news websites can take the following measures to combat large-scale plagiarism:

Utilize robots.txt。

News websites can use the robots.txt file to block access by web scrapers. However, this method is not foolproof as determined web scrapers can bypass these rules.

Implement anti-scraping technology。

Employ anti-scraping technology to detect and prevent unauthorized access by web scrapers. Dingxiang provides a comprehensive anti-scraping solution for news and information platforms, effectively preventing malicious data theft by web scrapers. Their Dingxiang Invisible Verification, based on AIGC technology, can prevent threats such as AI brute force cracking, automated attacks, and phishing attacks. This effectively prevents unauthorized access and intercepts web scraper theft.

trengthen copyright protection。

Strengthen copyright protection measures to safeguard the rights of content creators. This includes enforcing copyright laws and pursuing legal action against copyright infringers.

The rise of AI poses new challenges to the protection of intellectual property and the promotion of knowledge sharing. News websites, along with the technology industry and content creators, must work together to explore effective solutions to combat large-scale plagiarism and protect the rights and interests of content creators.hts and interests of content creators.