CHANG TSI
Insights
The Importance of AI Technology and Its Impact on Humanity
Artificial Intelligence (AI) technology plays a crucial role in the development of modern science and technology. It not only drives innovation and transformation across various industries but also profoundly changes human lifestyles. AI applications in fields such as healthcare, transportation, finance, and manufacturing significantly improve productivity and service quality, solving many problems that traditional methods struggle to address. For example, AI can assist doctors in diagnosing diseases more accurately through big data analysis and machine learning algorithms, optimize traffic flow, enhance financial risk management, and enable intelligent manufacturing and personalized customization.
Latest Data on China's AI Patent Applications
According to data released at the "Promoting High-Quality Development" series press conference held by the State Council Information Office on July 29, 2024, the number of patent applications in the field of artificial intelligence in China continues to grow. By the end of 2023, the number of effective AI invention patents in China reached 378,000, with a year-on-year growth rate exceeding 40%, which is 1.4 times the global average growth rate. These figures indicate significant progress in AI technology research and application in China, positioning it as a major force in global AI technology innovation.
Implementation of the Revised Patent Examination Guidelines: The China National Intellectual Property Administration (CNIPA) has been continually improving the standards for examination of patent applications related to AI technology. The revised Patent Examination Guidelines, effective January 20, 2024, include the following key points:
(1) Addition of Patentable Subject Matter Examination Criteria and Examples for Algorithm-Implemented Improvements in Computer System Performance (Part II, Chapter 9, Sections 6.1.2 and 6.2)
Section 6.1.2 of the guidelines has been revised to include criteria for examining subject matter involving improvements to AI and big data algorithms. If the claimed solution involves improvements to AI and big data algorithms (e.g., deep learning, classification, clustering) that have a specific technical association with the internal structure of the computer system, solving technical problems such as enhancing hardware computation efficiency or execution performance, it is considered a technical solution under Article 2, Paragraph 2 of the Patent Law. Section 6.2 includes Example 5, illustrating the application of these criteria using a method for training a deep neural network model.
(2) Addition of Patentable Subject Matter Examination Criteria and Examples for Big Data Processing (Part II, Chapter 9, Sections 6.1.2 and 6.2)
Section 6.1.2 also includes criteria for big data processing. If the claimed solution processes big data in a specific application field, using techniques such as classification, clustering, regression analysis, or neural networks to uncover inherent relationships in the data that conform to natural laws, so as to address the technical problem of improving the reliability or accuracy of big data analysis in specific application fields and achieve the corresponding technical effects, it is considered a technical solution. Section 6.2 includes Examples 6, 7, and 10, illustrating the application of these criteria with methods for analyzing electronic coupon usage tendencies, knowledge graph inference, and financial product price prediction.
(3) Addition of Inventiveness Examination Criteria and Examples for Algorithm-Implemented Improvements in Internal Performance of Computer System (Part II, Chapter 9, Sections 6.1.3 and 6.2)
Section 6.1.3 of the Examination Guidelines has been revised to include inventiveness examination criteria for algorithm-implemented improvements in the internal performance of computer systems. If the algorithm claimed in the patent has a specific technical association with the internal structure of the computer system and achieves improvements in the system's internal performance, such as enhancing hardware computation efficiency or execution effectiveness (including reducing data storage, decreasing data transmission, and increasing hardware processing speed), then it can be considered that the algorithmic features and technical features functionally support each other and interact. During the inventiveness examination, the contribution of the algorithmic features to the technical solution should be taken into account.
Section 6.2 of the Examination Guidelines adds Example 15, which uses "a method for adapting neural network parameters" to illustrate the application of the inventiveness examination criteria for algorithm-implemented improvements in the internal performance of computer systems.
(4) Addition of Inventiveness Examination Criteria for User Experience Enhancement and Modified Examples (Part II, Chapter 9, Sections 6.1.3 and 6.2)
Section 6.1.3 of the Examination Guidelines has been revised to include inventiveness examination criteria related to the enhancement of user experience. If the solution claimed in a patent application can improve user experience, and this improvement is brought about or generated by technical features, or by technical features along with algorithmic features or business rules and methods that functionally support and interact with each other, then this should be considered during the inventiveness examination. Section 6.2 of the Examination Guidelines has been revised to modify Example 13, which uses "a logistics delivery method" to illustrate the application of the inventiveness examination criteria related to the enhancement of user experience.
We believe that the revised guidelines can enhance the quality and efficiency of patent examinations in cutting-edge fields such as AI, strengthen patent protection, support the development of emerging technologies, improve the legal and policy framework, and protect public interests. Overall, these revisions are crucial for advancing China's intellectual property system and fostering an innovative environment.
On December 6, 2024, the CNIPA released the "Guidelines for Patent Applications Related to Artificial Intelligence (Draft for Public Comment)," providing specific guidance for AI patent applications. Key points include:
(1) Definition of AI-Related Patent Application Types
AI-related patent applications typically involve AI algorithms or models, and their functions or applications. With continuous breakthroughs in AI technology, applications related to AI-assisted inventions and AI-generated inventions are becoming new hotspots. Specific types include:
(2) Legal Issues Related to AI Patents
Inventor Eligibility: The inventor must be a natural person who has made an inventive contribution to the substantive characteristics of the invention.
Patentable Subject Matter: The claimed solution must not merely involve rules and methods of mental activities. It should solve technical problems using technical means that follow natural laws and achieve technical effects.
Sufficiency of Disclosure: The content of the specification should be drafted based on the type of contribution to the prior art. Different types of contributions require different approaches to drafting the application documents.
Inventiveness Considerations: AI-related inventions often contain many algorithmic features. When considering inventiveness, algorithmic features that support and interact with technical features should be considered as a whole.
Ethical Issues: Applicants should pay attention to whether the application of the algorithm or model in specific scenarios violates relevant laws and regulations, social ethics, or public interests. When it comes to the acquisition and utilization of data by artificial intelligence, it is necessary to ensure that all aspects, including the source of the data, application scenarios, security management, and usage norms, comply with relevant laws and regulations. In addition to the content of the data itself, specific methods of data collection, storage, and processing must also conform to relevant legal requirements and must not violate social ethics or harm public interests.
Overall, the release of the "Guidelines for Patent Applications Related to Artificial Intelligence (Draft for Public Comment)" marks a significant step for China in the AI field. It provides clear guidance for the industry, helps improve the quality and efficiency of AI patent applications and examinations, promotes AI technology innovation, and lays a solid foundation for future technological development and protection. We will continue to monitor the progress of these guidelines and provide timely updates on our observations.
