The legal status of artificial intelligence-generated content (AIGC) in the field of copyright is not fully clear, which provides some people with potential room for abuse. The following are several ways that may be used to circumvent copyright liability and related legal and ethical risk analysis： ###1. Status of the legal framework 1. **Ambiguity of copyright attribution** (take the United States as an example) -The U.S. Copyright Office clearly requires that works reflect "human creativity", and content generated by pure AI does not enjoy copyright protection. - China and other countries have begun to explore the copyright recognition standards for "AI+human collaboration" works 2. **International legal differences** -The UK allows computer-generated works to enjoy copyright-like protection (lasting for 50 years) -Japan adopts the principle of "fact-free ownership" of AI-generated content ###2. Potential means of abuse 1. **Content tampering strategy** - Hybrid creation: combine AI-generated content with human modifications (such as 5-10% changes) to advocate originality -Data cleaning: Use GAN network to migrate the style of copyrighted content to avoid content similarity detection 2. **Technical means of circumvention** -Metadata stripping: Eliminate traces of generation through EXIF data deletion tool -Distributed generation: use the Tor network to anonymously access AI services and cut off content traceability 3. **Use of the legal system** -Choice of jurisdiction: register a shell company to operate in a jurisdiction with loose AI copyright recognition (such as the Cayman Islands) -Reasonable use defense: Arguing that AI training data belongs to the exception clause of "text and data Mining" (Article 3/4 of the EU DSM Directive) ###3. Risks and consequences 1. **Legal liability risk** - Article 512 of the U.S. Digital Millennium Copyright Act (DMCA) may retroactively limit the liability of content dissemination platforms - Article 1195 of China's Civil Code stipulates on the joint and several liability of network Service providers 2. **Progress of technical testing** -The AI content recognition tool developed by OpenAI has an accuracy rate of 99% (2023 data) -The implantation of digital watermarking technology (such as NVIDIA's GAN watermarking) in the generated content 3. **Economic punishment cases** -Getty Images' lawsuit against Stability AI claims US11.6 billion (2023) -A domestic self-media was awarded 270,000 yuan in compensation to the original author for AI manuscript washing (2022 Hangzhou Internet Court) ###4. Compliance recommendations 1. **Content production level** -Keep a complete creation log (including prompt modification record) -Generate content using trusted timestamp authentication 2. **Commercial application level** -Establish an AI content review committee (it is recommended to include legal counsel and technical experts) - Purchase generative AI liability insurance (such as AIGC special insurance launched by Allianz) 3. **Technical prevention level** -Deploy AI detection API (such as GPTZero Enterprise Edition) -Implementation of Blockchain certificate deposit (Ant Chain has launched an AI content certificate deposit service) It is recommended that when enterprises use AI to generate content, they should establish a triple review mechanism that includes legal counsel, technical experts, and ethics examiners. At the same time, they should pay close attention to the latest guidelines of regulatory authorities such as the National Internet Information Office (such as the "Interim Measures for the Management of Generative Artificial Intelligence Services"). For individual creators, it is recommended to maintain at least 30% or more of the expression of human originality in AI-assisted creation to meet the basic requirements of the current law for "works".