宋李民 编者按： "十五五"规划建议提出，健全数据要素基础制度，建设开放共享安全的全国一体化数据市场，深化数据 资源开发利用。国家数据局多次发声，呼吁全社会加大对数据领域的投入，着力培育"为数据付费买 单"的市场意识。这一倡导，不仅是对数据要素市场化配置的顶层指引，更是打通数据价值转化堵点、 构建健全数据要素市场的关键一步。多位专家将深入解读数据资源开发利用的市场培育逻辑与实践路 径。 随着人工智能技术从"以模型为中心"向"以数据为中心"转变，高质量数据已成为决定AI系统能力上限、 驱动产业智能化升级的核心要素。在此背景下，培育数据付费意识，建立健全科学高效的付费机制，不 仅是深化数据要素市场化配置改革的关键举措，更是"十五五"时期全面实施"人工智能+"行动的重要保 障。 数据付费是激活"人工智能+"新动能的必然要求 数据的价值并非蕴藏于静态存储之中，而是在具体应用场景中被激活和创造，只有当市场愿意为高质量 数据支付合理费用时，其潜力才能充分释放。 在人工智能迈向高质量发展的重要阶段，加快培育"为优质数据付费"的市场意识尤为迫切。这不仅关乎 能否构建健康、可持续的商业模式，更关乎我国能否在数智时代把握发展主动 ...

Core Viewpoint - The articles emphasize the importance of establishing a data payment mechanism to activate the value of high-quality data, which is crucial for the development of artificial intelligence and the overall digital economy in China [1][2][3]. Group 1: Data Payment Mechanism - The establishment of a data payment mechanism is essential for addressing the core bottlenecks in the marketization of data elements and ensuring a continuous supply of high-quality data [2][3]. - A clear and reasonable payment mechanism serves as a "market benchmark" for data value, guiding efficient resource allocation by reflecting the true demand and value of data across different industries and applications [3][4]. - The payment mechanism is vital for solidifying the foundation of the artificial intelligence industry and mitigating security risks by incentivizing the production of high-quality data [3][4]. Group 2: Building a New Data Payment Ecosystem - A new data payment ecosystem should be constructed around three core aspects: quantifying value, ensuring circulation, and incentivizing application [4][5]. - A dynamic pricing mechanism based on scientific assessment and contribution recognition should be established, including a quality certification system and innovative pricing models [4][5]. - A secure circulation system supported by trustworthy data infrastructure is necessary to facilitate data transactions, including the establishment of a national-level secure circulation platform [5]. - The cultivation of application scenarios that demonstrate the tangible benefits of data is crucial for realizing data value, which includes creating benchmark projects and encouraging enterprises to manage data as core assets [5].

Core Viewpoint - The establishment of a scientific data payment mechanism is essential for building a sustainable data factor market, which will ensure the legitimate rights of data providers and promote efficient and compliant data circulation, thereby unleashing the value of data factors and empowering the development of the digital economy [5] Group 1: Data Market Development - The "14th Five-Year Plan" emphasizes the need to improve the foundational system for data factors and build an open, shared, and secure national integrated data market, which is crucial for deepening the development and utilization of data resources [1] - The National Data Bureau has called for increased investment in the data sector and the cultivation of a market awareness of "paying for data," which serves as a top-level guide for the market-oriented allocation of data factors [1][2] Group 2: Challenges in Data Quality and Pricing - The core obstacle in the development of the data factor market is the lack of a payment mechanism that accurately identifies and rewards data value, leading to market failure and stifling innovation in the AI industry [3] - The current market faces fundamental issues such as "bidirectional value uncertainty" and pricing failure, which hinder the circulation of high-quality data [3][4] - Insufficient incentives for high-quality data production result from the absence of a payment mechanism, leading to a severe shortage of specialized data sets necessary for deep AI development [4] Group 3: Proposed Solutions for Data Payment Mechanism - A technology-driven and mechanism-supported data payment system is essential to overcome existing challenges, focusing on quantifying value and ensuring fair distribution [6][7] - The transition from "fuzzy pricing" to "precise quantification" is necessary to address data pricing challenges, utilizing advanced technologies to measure the marginal contribution of specific data to model performance [7] - The establishment of a "data billing" system is crucial, which should balance cost compensation and fair profit sharing, ensuring that contributions determine rewards [8] Group 4: Strategic Importance of Data Payment Mechanism - Establishing a scientific payment mechanism for quality data is a strategic and long-term investment for the future of digital economy development and the healthy growth of the AI industry [9] - A fair and effective data evaluation and pricing system is fundamental to resolving the "lemon market" effect and "bidirectional value uncertainty" issues, providing a clear technical solution to implement the "data twenty articles" [9]