算法"杀熟"需多元共治 □ 刘 诚 □ 随着算法技术的演进，大数据"杀熟"现象已完成从简单粗放到复杂隐蔽的根本性形态变迁。其核心路 径是从基于静态身份的显性价格差异，转向依托人工智能、融合多元情境的隐性系统性博弈 □ 大数据"杀熟"的盛行与平台经济发展阶段直接相关。本质上，这是一种着眼于短期利润再分配的"掠 夺性增长"，而非通过创新与服务提升实现价值增量的"创造性增长"，若任由其蔓延，将从根本上动摇 市场公平原则，危及平台经济的可持续性与长期投资价值 □ 面对日益隐蔽且系统化的算法差别定价，治理须超越单一的事后处罚思维，转向涵盖法律规制、技术 审计、市场结构优化与社会监督的系统性重构。其核心在于重新平衡平台算法权力与消费者权利，引导 技术向善，保障市场公平 近期，市场监管总局依据《中华人民共和国反垄断法》，对携程集团涉嫌滥用市场支配地位实施垄断行 为立案调查，释放了强监管信号。2月1日，正式施行的《网络交易平台规则监督管理办法》更是划出红 线，明确规定平台不得在消费者不知情的情况下，对同一商品或服务在同等条件下设置不同价格或收费 标准。此举旨在根治长期存在的大数据"杀熟"乱象。 然而，现实挑战不容小觑。大数据 ...

Core Viewpoint - The rise of generative artificial intelligence is reshaping the information ecosystem, leading to the proliferation of low-quality content, termed "digital sludge," which poses a significant risk to the cognitive development and value formation of minors in China [1][2]. Group 1: Impact of "Digital Sludge" - "Digital sludge" erodes deep cognitive abilities, as exposure to fragmented and low-logic information inhibits the development of critical thinking skills in adolescents [2][3]. - It distorts values and social cognition, creating a false environment that interferes with minors' ability to discern right from wrong and build healthy value systems [2][3]. - The phenomenon exacerbates the deterioration of the digital cultural ecosystem, as low-quality content crowds out quality content, leading to a vicious cycle that undermines cultural creativity and aesthetic standards [2][3]. Group 2: Factors Contributing to the Proliferation of "Digital Sludge" - The combination of technological advancements and market logic has lowered the barriers for producing low-quality content, with platforms prioritizing user engagement through algorithms that favor emotionally charged content [3]. - The traditional filtering mechanisms of professional "gatekeepers" in media have been significantly weakened in the algorithm-driven environment, allowing low-quality content to thrive [3]. Group 3: Governance Strategies - Establish a comprehensive governance system that integrates technology, legal frameworks, education, and social forces to address the challenges posed by "digital sludge" [5]. - Implement "algorithm for good" principles to ensure platforms take responsibility for content distribution, shifting from a "traffic-first" to a "value-first" approach [5][6]. - Create a collaborative regulatory framework involving multiple departments to enhance the precision and agility of governance, focusing on proactive measures rather than reactive responses [6]. Group 4: Educational Initiatives - Enhance the digital literacy and critical thinking education for minors by integrating systematic media literacy into school curricula, focusing on algorithm awareness and information verification [7]. - Empower parents through digital literacy support programs to help them guide their children effectively in navigating the digital landscape [7]. - Foster a cultural atmosphere that values deep thinking and rational dialogue through community engagement and experiential educational projects [7].

Core Viewpoint - The integration of algorithms in the freight industry aims to enhance efficiency but raises concerns about fairness and transparency, necessitating a balance between efficiency and worker welfare [1][15]. Group 1: Algorithm Transparency and Fairness - The recent algorithm disclosure by Huolala emphasizes technical transparency and system optimization, benefiting over a million drivers and serving as a model for the industry [1]. - The complexity and opacity of commission rules contribute to driver anxiety, prompting Huolala to implement clear commission structures to alleviate costs for drivers [2]. Group 2: Cost Reduction Mechanisms - Huolala's commission reduction strategy includes differentiated reductions based on order types, long-distance orders, and supply-demand conditions, ensuring maximum benefit for drivers [4]. - A rigid commission cap has been established, limiting commissions to 50 yuan for drivers with a "reduction card" and 100 yuan for others, addressing long-standing industry issues of unlimited commission increases [5][8]. - The overall commission rate is set to decrease from 12.2% in 2023 to 10.9%, with a projected cumulative benefit of 260 million yuan for drivers by 2025, fostering a positive cycle of platform benefits leading to increased driver income and service quality [8][10]. Group 3: Operational Environment Optimization - Huolala addresses hidden costs such as complex pricing and payment risks, which contribute to driver burdens, by implementing measures for risk management and improved user experience [11]. - The introduction of transparent pricing models and peak service fees aims to enhance driver earnings and address supply-demand imbalances, with an investment of 680 million yuan in subsidies and fees by 2025 [13]. - A new "payment on delivery" service fee mechanism compensates drivers for payment risks, projected to generate 240 million yuan in additional income for drivers by 2025 [13][14]. Group 4: Industry Transformation and Collaboration - Huolala's algorithm disclosure marks a shift from an efficiency-first approach to one that prioritizes fairness and human concern, aligning with regulatory expectations for algorithm transparency [15][16]. - The ongoing digital transformation in the freight industry necessitates collaboration among leading platforms, regulatory bodies, and drivers to foster a healthy development environment [15][16].

Core Viewpoint - The article emphasizes the importance of algorithm transparency in the freight industry, highlighting that while algorithms drive efficiency, they must also address fairness and sustainability to protect drivers' interests and comply with regulatory requirements [1][21]. Algorithm Transparency and Driver Benefits - The recent sixth algorithm disclosure by Huolala focuses on technical transparency and reducing burdens, benefiting over a million drivers and providing a model for the industry [1]. - Complex and opaque commission rules are a major source of anxiety for drivers, with some smaller platforms exacerbating confusion through low commission gimmicks and hidden fees [2]. Clear and Predictable Cost Reduction System - Huolala implements a multi-scenario commission reduction strategy, covering all order types and differentiating reductions based on order category, long-distance travel, and supply-demand conditions [6]. - A rigid commission cap has been established, limiting commissions to 50 yuan for drivers with a "reduction card" and 100 yuan for others, addressing the long-standing issue of unlimited commission on high-value orders [7][9]. - Continuous fee reductions are part of Huolala's long-term strategy, aiming to lower the overall commission rate from 12.2% in 2023 to 10.9%, with a projected cumulative benefit of 260 million yuan for drivers by 2025 [11]. Systematic Operational Environment Optimization - Drivers face not only explicit costs like commissions but also implicit risks such as complex pricing and delayed payments, which are common industry challenges [14]. - Huolala has introduced measures to enhance pricing transparency, allowing drivers to better understand their earnings and providing a peak service fee during high-demand periods [15]. - The introduction of a "payment on delivery service fee" addresses the risk of delayed payments, charging users an additional 2%-3% fee to compensate drivers, which is expected to generate 350 million yuan in additional income by 2026 [17]. - Huolala also commits to covering overdue payments for eligible drivers, having already paid over 1 million yuan in overdue fees, with plans to increase this amount to 1.5 million yuan in 2026 [19]. Industry Transformation and Future Outlook - The sixth algorithm disclosure by Huolala represents a shift in the freight industry from an "efficiency-first" approach to one that prioritizes fairness and human concern, aligning with regulatory expectations [19][21]. - The ongoing digital transformation in the freight industry requires collaboration among major platforms, regulatory bodies, and drivers to foster a healthy development environment [21]. - As algorithm transparency becomes a consensus in the industry, it is anticipated that more platforms will follow suit, leading to reduced burdens on drivers and improved income stability, ultimately moving the industry towards a more equitable, efficient, and sustainable future [21].

Group 1 - The core issue revolves around a live streamer who disrupts public spaces for personal gain, highlighting the negative impact of algorithm-driven "traffic-first" logic [2] - The current algorithmic rules favor outrageous content over compliant material, leading to a cycle where violations generate more visibility and engagement [2] - Platforms are complicit in this issue by designing algorithms that promote controversial and inappropriate behavior, creating a toxic environment for public order [2] Group 2 - To address the chaos in public spaces caused by live streaming, algorithms must be restructured to favor compliant content and limit the exposure of violations [3] - Regulatory bodies need to impose stricter guidelines on algorithms to ensure platforms take responsibility for their content distribution [3] - A shift towards "benevolent" algorithms is essential for maintaining order both online and offline, as continued favoritism towards rule-breakers undermines enforcement efforts [3]

Core Viewpoint - The term "digital slop" has gained significant attention, representing low-quality digital content that poses risks, especially to minors, and highlights the need for governance in the digital ecosystem [1][3]. Group 1: Impact on Minors - "Digital slop" is a product of the combination of technological benefits and the greed for traffic, leading to the spread of low-quality content that targets minors' curiosity and trends [3]. - It diminishes cognitive abilities and causes mental dullness, as the instant gratification from "digital slop" can lead to a loss of interest in quality content and degrade critical thinking skills [3]. - It distorts value recognition, creating psychological hazards for minors by blurring the lines between right and wrong, and promoting unhealthy behaviors as trends [3]. Group 2: Strategies for Resistance - To combat "digital slop," it is essential to establish three defensive lines, starting with a technological defense that involves optimizing algorithms to promote quality content and reduce the spread of low-quality material [4][5]. - Regulatory measures must be strengthened, including the development of a legal framework for AI-generated content and clear guidelines to address issues like vulgar modifications and false scripts [5]. - Encouraging community involvement, particularly through educational institutions and families, is crucial for fostering critical thinking and helping minors navigate digital content effectively [5][6].

Core Viewpoint - The article highlights the challenges and needs of new employment groups in Jinan, focusing on their social security, legal rights, and integration into urban life, while exploring solutions to enhance their legal protections and overall well-being [3][4][8]. Group 1: Social Security and Legal Support - Jinan has established 21 legal service contact points to provide accessible legal assistance to new employment groups, addressing their unique needs due to high mobility and concentration [4]. - In 2023, these contact points have provided legal consultations and assistance 296 times, with 45.6% related to social security issues [4]. - The lack of formal labor contracts and social security coverage for gig workers, such as delivery riders, has led to significant concerns about their long-term welfare [4]. Group 2: Transparency in Platform Operations - Drivers in the ride-hailing sector express concerns over opaque commission structures, with platform fees ranging from 20% to 27%, impacting their earnings [6]. - The Ministry of Transport's initiative requires platforms to disclose commission rates, yet many drivers still find the rules unclear and inconsistent [6]. - The disparity in pricing between traditional taxis and ride-hailing services raises questions about fair competition and cost distribution among drivers [6]. Group 3: Community Integration and Support - Jinan has formed associations for various new employment groups, fostering a sense of belonging and providing a platform for addressing industry challenges [7]. - Community initiatives, such as summer care programs for children of gig workers, demonstrate a commitment to supporting the personal lives of these workers [7]. - The city has engaged 810 riders as community grid workers and 166 as food safety supervisors, promoting active participation in local governance and community service [7].

Core Insights - Douyin's Safety and Trust Center held a communication meeting in Shanghai to promote algorithm transparency and the practice of "algorithm for good" through interaction between academia and the platform [1] Group 1: Event Overview - The communication meeting featured experts from various universities, including Fudan University and East China Normal University, discussing algorithm principles, content ecology, and platform responsibilities [3] - The event was divided into two parts: an introduction to Douyin's algorithm and content ecosystem, followed by a discussion addressing public concerns regarding core algorithm issues [3] Group 2: Expert Opinions - Professor Lu Ye from Fudan University highlighted the need for algorithms to cater to diverse user needs, emphasizing the importance of addressing criticism and the impact of algorithms on public discourse [3] - Professor Zhang Zhian stressed that public understanding of algorithms should consider the broader social context, advocating for problem-oriented approaches and collaboration with the public and academia [4] - Lecturer Huang Fuyuan suggested enhancing user control over recommendations to improve user experience and algorithm transparency [5] Group 3: Recommendations for Algorithm Governance - Director Fang Shishi from Shanghai Academy of Social Sciences noted that current algorithm transparency practices focus on technical explainability but lack accessibility for the general public, recommending a shift towards governance transparency [7] - Professor Zhou Zhou from Fudan University proposed incorporating more social objectives into recommendation algorithms to balance social responsibility and commercial interests [8] - Assistant Professor Wang Yilin emphasized the need for clear communication frameworks for creators, differentiating between short video and live streaming recommendation mechanisms [8] Group 4: Douyin's Commitment - Douyin's representative stated that the communication meeting is part of ongoing efforts to enhance algorithm transparency, with over 20 specialized communication meetings held in various cities this year [8] - The Douyin Safety and Trust Center launched in March, providing public access to algorithm principles and governance policies, along with an upgraded "Usage Management Assistant" for user content preference management [8]

Core Viewpoint - The Central Committee's proposal emphasizes the promotion of new mass arts under internet conditions, encouraging widespread cultural activities and creative participation from the public [1] Group 1: Development of New Mass Arts - The proposal aims to support and guide the development of new mass arts, leveraging the creativity and innovation emerging from the internet [1] - The rise of new mass arts is attributed to improved living standards and the deepening of information technology, leading to unprecedented public engagement in artistic creation [1] Group 2: User Engagement and Market Trends - By June 2025, the user base for short videos and micro-dramas in China is projected to reach 1.068 billion and 626 million, respectively [1] - There is a concern regarding creators prioritizing short-term commercial gains, resulting in trends of superficial entertainment and homogenization [1] Group 3: Research and Development Ecosystem - It is suggested to enhance research on the development patterns, value logic, and ethical technology use in new mass arts to create a favorable development ecosystem [2] - Emphasis is placed on the importance of quality in new mass arts, focusing on meeting the spiritual and cultural needs of the public [2]

Core Points - The first national platform algorithm and labor rules agreement in the food delivery industry was established by Ele.me, focusing on the rights and welfare of delivery riders [1][3] - The agreement will benefit over 4 million urban riders, addressing issues such as rest, remuneration rights, and optimizing delivery algorithms [3][7] Group 1: Agreement Details - The agreement includes provisions for labor remuneration, rest and vacation rights, labor protection, and welfare guarantees [7][9] - The platform ensures that the hourly remuneration for delivery riders will not be less than the local minimum wage, taking into account local CPI and average hourly wages [7][9] - The platform will gradually eliminate penalties for exceeding delivery time, promoting positive incentives and enhancing safety and efficiency [7][9] Group 2: Welfare and Insurance - The agreement introduces nationwide coverage for pension and medical insurance subsidies for riders, marking a first in the industry [9] - By the end of 2025, the platform will subsidize at least 50% of insurance costs for stable riders, with full subsidies for team leaders and honor riders [9] - The platform's data indicates that the average weekly order volume for Taobao Flash Delivery reached 80 million in August, with over 200,000 active riders daily, contributing to job creation [9]