The Zhitong Finance App learned that Everbright released a research report overseas saying that overall, domestic and foreign copyright protection technology for model training data has yet to be mature, policies have yet to be improved, and the stock prices of copyright providers are expected to be intensively catalyzed in the future. Looking ahead to the maturity of data attribution technology, copyright revenue is closely linked to the amount of AI-generated content. As the commercial potential of AIGC downstream applications is unleashed, it is expected to continue to drive the increase in license revenue for copyright providers. AIGC's development is more beneficial than bad for copyright holders, and poor expectations drive stock price recovery. I am optimistic that copyright protection for domestic model training data will continue to be improved, driving the performance growth of various information media copyright providers such as news media, film and television. Recommended attention: 1) AI+ Publishing: China Publishing (601949.SH), China Science and Technology (601858.SH); 2) Photo Copyright Library: Vision China (000681.SZ); 3) Film and TV Copyright Library: Jiecheng Co., Ltd. (300182.SZ), Huace Film and Television (300133.SZ).

Everbright Overseas's main views are as follows:

Data sets used for AI model training have various ways to avoid infringement or directly compensate copyright holders.

Proprietary data: 1) Copyright cooperation agreements: various copyright providers such as Shutterstock and Axel Springer establish cooperation with AI companies; 2) Paid API access: Some highly specialized data providers will charge for API access. In 23, API access on Reddit and Twitter switched from free to paid.

Open source data: 1) Open license agreements: including CC, ODC, CDLA, etc.; 2) Specific data scraping strategies: such as complying with the website's Robot.txt file; 3) Community supervision: improving the transparency of data sets.

Direct compensation for creators: 1) Pre-compensation: Low technical difficulty, but it is difficult to define a reasonable amount of compensation, such as the contributor fund established by Shutterstock; 2) Post-facto compensation: AI-generated content is traceable, the pricing is reasonable but the technology is not yet mature, such as the attribution model algorithm published by Carnegie Mellon University.

Private data sets: directly sell data sets suitable for model training, or package them as MaaS services.

The profit model of overseas copyright cooperation agreements is stable, and the prospects for commercialization are initially showing.

AI generates content or poses a certain threat to the traditional business of copyright providers. Cooperation between copyright providers and AI companies is mutually beneficial and win-win. 1) Multimedia material library Shutterstock: Generates revenue by selling model training materials, launches an AI-generated image section, and provides AI tools supported by OpenAI; 2) Publisher Axel Springer: sells its publications to OpenAI as training materials to jointly use AI technology to enhance the user experience.

Looking at Shutterstock's cooperation with AI companies: the overall benefits of AIGC are stronger than the disadvantages.

1) Benefits: Shutterstock's data licensing revenue is clearly reflected on the performance side, driving valuation repair and stock price recovery. Revenue from the sale of model training materials in 23Q3 accounts for 19.5% of the company's total revenue;

2) Negative: Shutterstock's traditional business slump over the past 23 years has been more affected by competition in the same industry. Similar company Getty Image has performed well, and the threat and replacement of AIGC to the copyright library industry is not obvious.

Copyright regulations for domestic and foreign model training data have yet to be improved, and copyright agencies' stock prices are expected to be intensively catalyzed.

A 22M12 paper shows that Stable Diffusion replicates the details of famous paintings at the pixel level. Disputes over AIGC's copyright issues and related regulations can be divided into two main categories:

1) Copyright definition of AI-generated content: The United States does not recognize the copyright of AI-generated content, while China tends to protect the copyright of AI-generated content;

2) Copyright regulations for model training data: The United States and the European Union clearly require the use of copyrighted materials to train models, while Japan determines that training data is not protected by copyright.

Risk warning: AI technology development and product iteration fall short of expectations; competition in the AI industry increases risks; risks where commercialization progress falls short of expectations; domestic and foreign policy risks.