In the wave of digital transformation, artificial intelligence (AI) technology is gradually penetrating into various fields, and government decision support systems have also ushered in profound changes in this wave. This article will delve into the application direction of AI in government decision support, from development history, system composition, functional application to practical cases, and comprehensively analyze how AI empowers government decision-making.
Last timeEmergency managementIn this direction, today we will talk about another application direction – government decision support; Interested friends, continue to watch!
The development process of government decision-making support
- Rule-driven decision-making intelligence stage (90s – 2010): This stage is marked by rule-based expert systems and decision support systems (DSS), which are mainly used in structured decision-making scenarios. Government departments have begun to try to introduce information technology into the decision-making process, but the degree of intelligence is limited, mainly relying on predefined rules and simple algorithms for data analysis and decision support. For example, the budget planning system developed by the United States in the 90s assisted fiscal decision-making through preset rules, and the “Golden Customs Project” and “Golden Tax Project” built in China at the same time initially realized the digitization of business processes, but have not yet formed a real intelligent decision-making ability.
- Data-Driven Intelligent Decision-Making Stage (2010 – 2020): With the maturity of big data and cloud computing technology, government decision-making has entered the data-driven stage. Governments have begun to collect, store and analyze data on a large scale, using machine learning and other technologies to tap the value of data and provide more accurate support for decision-making. In 2012, the United States issued the “Big Data Research and Development Initiative” to promote the federal government to use big data technology to improve decision-making; The EU launched an open data strategy at the same time to promote the open sharing of public data. In 2015, China issued the Action Plan for Promoting Big Data Development, which clearly proposes to promote the application of big data in government decision-making. Local governments have established data centers and smart city platforms, such as the “City Brain” project in Hangzhou, which has achieved accurate decision-making in urban management by integrating multi-domain data.
- Model-driven decision intelligence stage (2020-present): With the breakthrough of generative AI and large model technology, decision-making intelligence has entered the model-driven stage. The core feature of this stage is that artificial intelligence can not only process structured data, but also understand and generate multimodal data such as natural language and images, realizing the transformation from data-driven to model-driven. This stage of decision support systems pays more attention to adaptability in complex decision-making scenarios and dynamic environments, emphasizes the combination of technology and ethical norms, and promotes technology integration and the construction of ecological platforms.
Government decision-making support industry analysis
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Components of the government decision support system
Government data warehouse: Government Data Warehouse: The government data warehouse can realize the storage and synthesis of decision-making topic data and time trend analysis. It can provide these services: (1) data extraction, (2) data cleansing, (3) data query, and (4) data organization
Online analysis and processingOnline analysis and processing is a software technology based on data warehouse, which enables analysts to observe data in multiple dimensions and perspectives quickly, consistently and interactively, so as to achieve the purpose of in-depth understanding of data, and is an essential analysis tool for data warehouse systems. OLAP features: Rapidity, analytizability, and multidimensionality.
Government data control and mining: Government data mining technology (Data Mining) is an artificial intelligence-based data analysis technology whose main function is to automatically discover potentially useful knowledge in large amounts of data, which can be expressed as concepts, rules, laws, patterns, etc.
Government Model Library: The government model library is the core of the government’s decision support system. In general, it includes: macroeconomic regulation and control decision-making model, fixed asset investment control decision-making model, industrial support decision-making model, abnormal situation decision-making model, etc.
Government Expert System: A government expert system refers to an intelligent computer system that can solve government problems like a human expert. It can use knowledge reasoning for qualitative analysis and provide strong support for government decision-making. The government expert system has the following three attributes:
(1) Inspiring: It uses standardized government professional knowledge and intuitive judgment knowledge to solve government problems.
(2) Transparency: It enables government decision-makers to directly interact with the government expert system without knowing its system structure to understand the government’s knowledge content and reasoning process.
(3) Flexibility: It can accept new information from all levels of government and control the information, so that it can be coordinated with the entire government knowledge base.
Topics of government decision support systems
The government comprehensive decision support system integrated by the above five methods and technologies, such as government data warehouse and government online analysis and processing, will complement and rely on each other, give full play to their respective auxiliary decision-making advantages, achieve more effective auxiliary decision-making, and become the technical basis of the government decision support system. This comprehensive decision support system encompasses three themes:
The first topic is the combination of government model library system and government database system, which is the basis of government decision support and provides auxiliary decision-making information for quantitative analysis (model calculation) for decision-making problems.
The second theme is government data warehouse and government online analysis and processing, which extracts comprehensive data and information from government data warehouses, which reflect the intrinsic nature of large amounts of data.
The third theme is the combination of government data mining technology and government expert system, government data mining technology mines from government databases and data warehouses, and puts it into the knowledge base of government expert system, and achieves qualitative analysis and decision-making by the expert system that performs knowledge reasoning.
These three themes can both complement and combine with each other. The system can decide whether to use a single topic to assist decision-making or a combination of two or three topics based on the scale and complexity of the actual problem. The auxiliary decision system using the first subject is the decision support system in the traditional sense. The auxiliary decision system using the second theme is the decision support system based on the data warehouse, and the relevant models of the government model library can be used in GOLAP to improve the data analysis ability of GOLAP. Combining the three themes, that is, using the “problem synthesis and interaction system” component to integrate the three subjects, the integrated decision support system formed in this way is a higher form of auxiliary decision-making system, and its auxiliary decision-making ability will be brought to a new level.
Functions of government decision support systems
- The basic functions of the government decision support system: With the establishment and improvement of government information systems at all levels, the amount of information processed by the government in daily business will increase geometrically. improving the quality of public policy; change the way of decision-making and promote government restructuring; improve the quality of government personnel and improve the knowledge structure of decision-makers; Promote the improvement of government information systems.
- Special functions of government decision support systems: realizing government management innovation; It helps the government to deal with emergencies in a timely manner; realize government informatization, thereby driving the construction of national informatization;
Application of government decision support system
National macroeconomic management and government public management
Since the 80s of the 20th century, our country government has invested heavily in the development of the National Economic Information System (SEIS) to support macroeconomic management. The system includes more than 100 relatively independent subsystems distributed in provinces, municipalities and villages across the country, which are used to assess and compare social, economic and ecosystem indicators in different regions or the country as a whole, and to simulate and predict development trends and analyze the impact of policies. At the same time, many government public administration departments at different levels have also begun to develop to support their work and decision-making, such as tax management, labor and employment, industrial management, urban environment management, land management, etc.
Water resource allocation and flood control
Governments and institutions at all levels have always attached importance to the rational planning, utilization and allocation of water resources, and the prevention and control of flood disasters. In the mid-80s of the 20th century, domestic scholars began to apply the method of decision support system to water resources planning and management. So far, there have been many successful applications in this field, mainly including the following four aspects:
- The Sui Resource Database system is used for mobile phone water resource data for comprehensive management and identification, for flood prevention and control, supply of urban demand and agricultural irrigation, etc.
- The flood control forecast and early warning system can quickly calculate the consequences of different flood control scheduling schemes according to the flood forecast, and provide flood control decision-makers with the option to choose the plan.
- The water resources planning and dispatch system includes a database containing millions of data, a model library system composed of conceptual models, and a flexible and convenient human-computer interaction system, which can help decision-makers make auxiliary decisions on decision-making problems in water resource planning.
- The water resources management and scheduling system is applied to some large-scale projects across regions according to the imbalance of water resource allocation in various regions.
Industry (or industry) planning and management
In terms of agriculture, agricultural water-saving decision-making support is composed of four subsystems: water resource analysis and calculation, agricultural irrigation water optimization utilization, water-saving irrigation project selection and evaluation, and agricultural water-saving information consulting, which can optimize the water resource consumption structure and improve the efficiency of irrigation.
In terms of forest product management, plant management DSS can identify seeds through fuzzy models and perform decision simulation.
In terms of marine fisheries, the “863” plan has set up a special development marine fisheries and geographic information decision-making system, which will comprehensively apply technologies such as remote sensing, geographic information systems, global satellite positioning systems and expert systems to marine fisheries, and develop an evaluation system for automatic fitting of selected resources based on rules-based models.
In terms of metal mineral resources, the resource strategy DSS can predict the resource characteristics and guarantee degree of ferrous non-ferrous metals in our country in the next 10 years, and analyze the technical and financial factors affecting the degree of security of our country’s main metal resources.
Ecological and environmental control
DSS in ecological environment construction and sustainable development has great development potential. Forest and ecosystem intelligence DSS that helps users specify forest structure protection decisions in a specific area. The DSS for the protection and development of the ecosystem in the western region in the national “863” plan can comprehensively evaluate the factors affecting the ecosystem and analyze the influence of policies, which has played a positive role in promoting the ecosystem and sustainable development in the western region.
Investment decision and risk analysis of financial systems
Typical applications of decision support in the field of finance and investment: project investment decision-making, securities investment analysis, financial early warning and banking management.
How AI empowers government decision-making
The first is to improve research efficiency. While AI can greatly improve the efficiency of information collection, data review, data processing, policy comparison, etc., the public sector can be liberated from tedious information sorting and text processing, devote themselves to practical investigation and creative thinking training, and promote in-depth reform and innovation.
The second is to broaden the field of research. Traditional policy decisions often rely more on empirical judgment, expert opinions, and limited historical data, while AI technology can discover potential laws and trends through the comparison and analysis of massive data and information, identify implicit associations in complex systems, provide a more comprehensive and scientific basis for policy formulation, and improve the systematization of public policies.
The third is to simulate the effect of the policy. AI technology can help the public sector study and judge the effectiveness of policy implementation and possible problems through simulation and prediction, and then make dynamic adjustments in advance to improve the accuracy and effectiveness of policies. For example, Tsinghua University has successfully built a “large-scale social simulator AgentSociety” based on a large model, which can accurately simulate the communication of public opinion, the polarization of cognitive views, and the response of public policies.
Government AI decision support application cases
Intelligent upgrading in the field of government services
(1) Intelligent approval system: The ‘Zhejiang Liban’ platform launched by Zhejiang realizes automatic verification of materials through NLP technology, and the approval time for industrial and commercial registration is reduced from 5 days to 30 minutes. Beijing’s Haidian District piloted the ‘AI civil servant’ system, which can handle 300+ high-frequency approval tasks at the same time.
(2) Accurate policy push: The AI policy matching engine built by the Shenzhen Human Resources and Social Security Bureau realizes the policy of ‘free application’ based on enterprise portraits, and automatically cashes out more than 5 billion yuan of preferential funds for enterprises in 2022.
(3) Virtual government assistant: Shanghai’s intelligent customer service handles an average of 200,000 consultations per day, with an accuracy rate of 92% (data from the Municipal Big Data Center in 2023)
Breakthroughs in AI practice in urban governance
(1) Intelligent traffic scheduling: Hangzhou City Brain analyzes 100,000 cameras through video analysis and optimizes 1,300 intersection signal lights in real time, reducing the peak congestion index by 15% (2022 “Smart City Development White Paper”).
(2) Environmental monitoring network: AI environmental sensors deployed in Singapore can predict PM2.5 concentrations 48 hours in advance, with an accuracy rate of over 85% (2023 National Environment Agency Annual Report).
(3) Emergency response system: Japan’s earthquake early warning system uses AI algorithms to issue warnings 10-30 seconds before the arrival of the earthquake wave, and successfully warns of earthquakes of magnitude 6 or above three times in 2023.
AI empowerment for public safety management
(1) Crime prediction model: The PredPol system used by the Chicago Police Department uses machine learning to analyze historical case data, reducing crime rates in key areas by 33% (Nature 2022 study).
(2) Food supervision network: The AI food traceability system established by the European Union can monitor 500,000 food companies 24 hours a day, 7× and successfully intercept 1,200 batches of problematic food in 2023.
(3) Border intelligent security check: The intelligent security check channel deployed at Dubai Airport improves customs clearance efficiency by 400% through millimeter-wave imaging and behavior recognition technology (IATA 2023 report).
