Artificial Intelligence Technologies for the Analysis of Content Restrictions on the Internet
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Abstract
This paper proposes a new approach to determining the level of internet censorship. Our definition of censorship is based on the principle of accessibility of alternative viewpoints in search engine results and large language models. The calculation method involves compiling a list of 11 questions, the answers to which suggest opposite opinions depending on the country. These answers are evaluated in comparison with the government's point of view. For search engine results, calculate the number of answers to these questions from a pro-government point of view and the proportion of answers that detail an alternative point of view. The difference between these indicators is proposed to be considered an index of internet censorship. Since Internet searches are increasingly performed through chatbots of the most well-known large language models (LLMs), the level of censorship is also assessed for these models. The comparison showed that the responses of the national search engine Baidu in China are closest to the government's point of view, while the level of censorship in the United States is higher than in Russia. The effectiveness of censorship in the United States is explained by a different mechanism, whereby materials expressing alternative opinions restrict access to popular information platforms. Censorship in chatbots is much stronger than in internet search engine results are calculated.
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References
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