From market supervision to financial regulation, from food safety to intellectual property protection, AI technology is bringing unprecedented changes to the traditional regulatory model. This article will delve into the application direction of AI in the field of G-end regulation and risk prevention and control, analyze its development history, industry pain points, policy support and typical application scenarios, and discuss the current challenges and future development trends.
Last time I talked about the direction of intelligent security, and today I will talk about another application direction – supervision and risk prevention and control; Interested friends, continue to watch!
The development history of supervision and risk prevention and control
Market supervision
Exploration Phase (2004-2010)
At this stage, represented by the “Red Shield Agricultural Protection Action”, industrial and commercial organs at all levels have carried out preliminary exploration of the construction of agricultural materials market supervision and informatization based on local conditions. For example, some places have explored the establishment of a provincial agricultural materials market supervision system, and carried out information exploration through QR codes for agricultural commodity labeling.
Pilot phase (2010-2020)
Since 2010, the State Administration for Industry and Commerce has launched the construction of national agricultural materials market supervision and informatization, organized many meetings and investigations, and fully demonstrated the feasibility of the national agricultural materials market supervision and informatization construction. This stage of work has laid the foundation for subsequent comprehensive promotion.
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Rapid development stage (2020-present)
In 2020, in the face of the complex international situation and domestic reform and development tasks, the State Administration for Market Regulation formulated a top-level plan for a unified national information system, promoted the work of “Internet + government services” and “Internet + supervision”, and vigorously promoted the construction of smart supervision. The focus of this stage is the construction of a smart regulatory information platform and a unified national information system, formulating relevant systems and standards and specifications, promoting the construction of a unified application support platform for market supervision, and carrying out technical docking and data sharing with other government departments.
AI market regulation industry definition
Industry pain points
- Supervision is difficult: Market supervision involves many fields, including food safety, product quality, intellectual property protection, etc., and there are many regulatory objects in these fields, and there are various illegal acts, which increases the difficulty of supervision.
- Illegal acts are highly concealed: Some illegal acts, such as illegal addition of drugs, counterfeit and shoddy products, etc., have a high degree of concealment, and the regulatory authorities need to invest a lot of resources to investigate and deal with them.
- Cross-regional collaboration is insufficient: Market supervision involves multiple regions and departments, and insufficient cross-regional cooperation may lead to regulatory loopholes and affect the overall regulatory effect.
- Technical means are backward: The technical means in some areas are relatively backward, and it is difficult to effectively respond to the detection and investigation of new illegal acts.
- Insufficient law enforcement forces: The personnel and resources of the market supervision department are limited, and it is difficult to cover all regulatory fields, resulting in some illegal acts not being investigated and dealt with in a timely manner.
- Weak corporate compliance awareness: Some enterprises lack compliance awareness, resulting in frequent violations of laws and regulations, increasing the difficulty and cost of supervision
Measures taken
- Special actionFor example, the “Iron Fist” action of the Shanghai Municipal Market Supervision Bureau improves the quality and efficiency of supervision through case investigation and service development.
- Technological innovationUse modern information technology to improve regulatory efficiency and accuracy, such as using big data, artificial intelligence and other technologies for intelligent supervision.
- Collaborate across regions: Strengthen cooperation with other regions and departments to form a joint force to jointly crack down on cross-regional violations.
- Policy support: Introduce relevant policies to support market supervision, such as increasing penalties for illegal acts and promoting enterprise compliance operations.
AI market supervision policies are sorted out
In December 2021, the State Council issued the “Notice of the State Council on Printing and Distributing the 14th Five-Year Plan for the Modernization of Market Supervision”, which mentioned that it is necessary to accelerate the promotion of smart supervision. Make full use of modern technologies such as the Internet, cloud computing, big data, and artificial intelligence to accelerate the improvement of market supervision efficiency. Establish a catalog of market supervision and service information resources and a standard specification system, comprehensively integrate information resources and business data in the field of market supervision, and further promote the sharing and openness of market supervision information resources and the collaborative application of systems.
In September 2024, the State Administration for Market Regulation announced the “Key Measures for Market Supervision Departments to Optimize the Business Environment (2024 Edition)”, which pointed out that the goal is to improve the ability of smart supervision, and proposed to adhere to inclusive and prudential supervision for new technologies, new industries, new formats, and new models, study and explore sandbox supervision and other models, and improve fault tolerance and correction mechanisms. Research the use of information technology to reduce the frequency of sampling of the same type of products in the same production enterprise. Accelerate the construction of a unified registration management system for enterprises, a national online transaction supervision platform, a smart supervision platform for special equipment, and a “double random, one open” supervision platform. Improve regulatory technologies and means, use the Internet of Things, artificial intelligence and other technologies to empower supervision, and explore the implementation of off-site smart supervision by means of remote supervision and non-inductive supervision.
Typical applications of AI market supervision
In July 2024, the Chinese Society for Market Regulation released seven typical application scenarios of artificial intelligence in the field of market supervision, namely intelligent decision-making, intelligent supervision, intelligent licensing, intelligent review, intelligent law enforcement, intelligent measurement, and intelligent detection.
- Intelligent decision-making: Intelligent analysis, real-time monitoring and processing of data in the field of market supervision through artificial intelligence large models can improve the accuracy and intelligence level of market supervision decision-making, predict market trends and risks, and help market supervision departments grasp market dynamics in a timely manner.
- Intelligent supervision: Using artificial intelligence technology, market supervision departments can realize intelligent supervision of business entities and market behavior, such as real-time monitoring and complaint analysis of advertising, price and online transaction behavior, timely detection of illegal acts and price changes, and determining the focus of administrative law enforcement.
- Intelligent licensing: Through artificial intelligence technology, intelligent recommendation of entered information, intelligent verification of false addresses and linkage disposal of risk warnings can be realized, and problems such as insufficient human resources and service model limitations faced by current registration can be solved.
- Intelligent review: The fair competition auxiliary review platform established by artificial intelligence technology can achieve comprehensive access to policy documents and bidding announcements, accurate identification of suspected illegal documents, and one-click generation of auxiliary review reports.
- Intelligent law enforcement: Through the administrative law enforcement AI intelligent case handling system, grassroots law enforcement personnel only need to enter the cause of the case or case clues in law enforcement and case handling, and the system can conduct intelligent pre-research and judgment, provide recommendations for similar cases, qualitative punishment basis, etc., greatly improving work efficiency.
- Intelligent metering: In the field of measurement, the application of artificial intelligence large models can accelerate the intelligence of measurement equipment and management, improve the accuracy and efficiency of measurement, and prevent cheating.
- Intelligent detection: In the production and product quality defect detection of industrial enterprises, the general vision model can semantically segment images of circuit boards and other products and identify various defects with strong generalization capabilities.
Problems in AI market supervision
Data privacy and security concerns
When using artificial intelligence technology for market regulation, regulators need to collect a large amount of personal and business data, which involves privacy and trade secrets, and is vulnerable to hacking or improper use.
Strengthen data security measures, including encrypted storage, access control, identity verification, and other technical means, and establish strict data management and supervision systems to ensure that data is used only for legitimate regulatory purposes.
Algorithmic bias and unfairness
Problem, artificial intelligence algorithms may be biased, leading to unfair regulatory behavior and affecting market order. For example, algorithms may make unfair decisions based on factors such as race, gender, etc.
Countermeasure. Regulators should review and test algorithms to ensure their fairness and neutrality. Establish mechanisms to monitor the use of algorithms, while strengthening the requirement for algorithm transparency so that their decision-making processes are interpretable and traceable.
Technical barriers and uneven development
The application of artificial intelligence technology requires a large amount of technical support and professional talents, and some regulators may not be able to effectively apply these technologies due to insufficient technical capabilities, leading to the unbalanced development of market supervision.
Strengthen talent training and technical support, provide training and technical support to regulatory agencies, and promote the popularization and application of technology. At the same time, a cooperation mechanism should be established to promote information sharing and technical exchange among regulatory agencies.
Data quality and reliability
The performance and accuracy of AI systems are highly dependent on the quality and completeness of input data, and if the data is inaccurate or incomplete, it will affect the accuracy and effectiveness of regulatory decisions.
Countermeasures, strengthen data quality management, including data cleaning, deduplication, annotation, etc., to ensure the accuracy and completeness of data. At the same time, the method of multi-source data fusion is adopted to improve the reliability and comprehensiveness of the data.
Regulatory transparency and accountability mechanisms
The use of artificial intelligence technology has made regulatory decisions more complex and difficult to understand, and regulators need to establish transparent decision-making mechanisms and accountability systems to ensure the legality and fairness of regulatory behavior.
Countermeasures, establish a transparency mechanism for regulatory decision-making, including disclosing information such as decision-making basis, algorithm principles, and regulatory results, so as to make the regulatory process more interpretable and trustworthy. At the same time, establish an accountability mechanism to supervise and evaluate regulatory behavior, and correct mistakes and misconduct in a timely manner.
The future development trend of AI market supervision
Rule of law supervision: The Decision of the Third Plenary Session of the 20th Central Committee of the Communist Party of China proposes to improve the development and management mechanism of generative artificial intelligence and establish an artificial intelligence safety supervision system. This indicates that our country will strengthen the governance of AI on the track of the rule of law and ensure its healthy development. The rule of law has the characteristics of fundamentality, stability and predictability, which can maintain production relations, optimize economic structure, and stabilize social order1.
Multi-departmental joint governance: The Cyberspace Administration of China, the Ministry of Industry and Information Technology, the Ministry of Public Security, the State Administration of Radio and Television and other departments have jointly issued the “Measures for the Identification of Artificial Intelligence-Generated Synthetic Content” to further standardize the identification of artificial intelligence-generated synthetic content. In addition, local public security organs are also stepping up their crackdowns to deal with the use of AI technology to produce and publish rumors2.
Special action: The Cyberspace Administration of China recently deployed a three-month special action to “clear and rectify the abuse of AI technology”, aiming to strengthen the governance of AI technology at the source, clean up relevant illegal and bad information, and deal with and punish illegal accounts and platforms2.
International cooperation and standard setting: With the global application of AI technology, international cooperation and standard setting are also particularly important. Governments and international organizations are working together to develop relevant standards and guidelines to ensure the safety, ethics, and sustainable development of AI technology.
