Research on Risks and Governance Pathways of False and Harmful Information in the Application of Generative Artificial Intelligence

In the era of artificial intelligence, the governance of false and harmful information in cyberspace has become more urgent due to the development of content generation technologies. Therefore, the monitoring techniques for false and harmful information has become an important research topic. The core principle of false and harmful information monitoring technology is the integration of content feature extraction and monitoring algorithms. Allowing the generation and dissemination of false and harmful information poses potential threats to social stability and the legitimate rights and interests of others. The technical reasons for the generation of false and harmful information are that the quality of training data sets affects the authenticity of output content, the capabilities of deep learning models accelerate the generation of false and harmful information, and the lag in the update of training data sets makes it difficult to detect false news in new contexts. Therefore, it is necessary to address these issues through a comprehensive governance approach combining technology and law to achieve the healthy development of cyberspace in the era of artificial intelligence.