Core Viewpoint - Ele.me is actively enhancing algorithm transparency and communication with delivery riders, focusing on optimizing delivery efficiency and rider rights protection through various initiatives [1][4]. Group 1: Algorithm Transparency and Optimization - Ele.me has publicly shared four key algorithms related to order dispatch, delivery pricing, delivery time estimation, and route planning, aiming to alleviate rider anxiety and improve operational efficiency [4]. - The company has established an expert committee for instant delivery algorithms and initiated monthly rider rights forums to gather feedback and improve algorithms [1][4]. - The current route planning algorithm has achieved a combined order route rate of 89%, indicating significant improvements in delivery efficiency [3]. Group 2: Rider Feedback and Concerns - Riders' top concerns include merchant cooking speed, accessibility to delivery locations, and route efficiency, which are critical for optimizing delivery processes [2]. - The company is addressing specific issues raised by riders, such as challenges with high-rise buildings and road closures, by continuously updating data and improving guidance systems [3][4]. Group 3: Expert Insights and Recommendations - Experts emphasize the importance of fairness, transparency, and trust in algorithm governance, highlighting the need for a feedback mechanism to address issues promptly [5][6]. - Recommendations include establishing a tiered feedback system for problem resolution and enhancing user expectation management to reduce misunderstandings with riders [5][6].

Core Viewpoint - The article emphasizes the need for a multi-stakeholder approach to algorithm governance in the platform economy, highlighting the importance of protecting the rights of new employment form workers through collaborative efforts among government, industry associations, platform companies, labor unions, and workers themselves [1][2]. Group 1: Policy and Governance - Recent policies have been introduced to protect the rights of new employment form workers, including guidelines on labor rights and algorithm management [1]. - A multi-party governance system is proposed, where the government sets baseline policies, industry associations promote self-regulation, platform companies optimize technology, labor unions coordinate rights protection, and workers express their demands [2]. Group 2: Algorithm Impact on Workers - Algorithms significantly influence the work patterns and rights of new employment form workers in sectors like e-commerce, delivery, and ride-hailing, affecting income levels, labor intensity, and job safety [1]. - Some platforms have previously relied heavily on strict algorithms, leading to issues such as unstable incomes for ride-hailing drivers and delivery workers [1]. Group 3: Company Initiatives - Leading companies like Huolala, Didi, and SF Express are responding to national policies by incorporating worker rights protection into their algorithm design frameworks [2]. - Huolala has publicly shared its algorithm rules and optimization mechanisms, marking a significant step towards algorithm transparency [2]. - Didi has upgraded its algorithms to monitor driver work patterns and enforce rest periods, while SF Express considers various factors in its delivery algorithms to improve worker experience [3]. Group 4: Communication and Collaboration - Huolala has established communication mechanisms with workers to gather feedback and optimize algorithm rules, enhancing transparency and worker satisfaction [3]. - Recommendations include strengthening government oversight, improving policies, and establishing regular negotiation mechanisms between labor unions and platform companies to address algorithm optimization and rights protection [3][4]. Group 5: Future Directions - Continuous innovation in technology and algorithm transparency is essential, with platforms encouraged to disclose algorithm principles and engage third-party oversight [4]. - Labor training and awareness are crucial, promoting worker participation in algorithm optimization and feedback processes [4]. - Huolala announced further algorithm optimization measures, including dynamic pricing adjustments and the establishment of an algorithm advisory group for ongoing consultation [5].

Core Insights - The recent algorithm changes on Xiaohongshu have significantly impacted content creators, leading to a disparity in exposure and engagement based on content quality and user interaction metrics [1][2] - The platform is now under stricter regulatory scrutiny, requiring transparency in algorithm operations and content moderation [2][3] Group 1: Algorithm Changes - Xiaohongshu's algorithm now emphasizes "contribution" metrics such as clicks, dwell time, likes, saves, comments, and shares, with varying weights assigned to each [1] - The platform has shifted from a model that favored new content to one that prioritizes user engagement and quality, making it harder for low-quality content to gain traction [1][6] Group 2: Regulatory Impact - The "Clear and Bright Algorithm Governance Special Action" has imposed strict regulations on platforms like Xiaohongshu, mandating the disclosure of algorithm logic and the elimination of low-quality content [2] - The platform must now publicly disclose the reasons for content appearing on trending lists, including whether the visibility is organic or manipulated [3] Group 3: User Engagement Features - Xiaohongshu has introduced a "content preference assessment and adjustment" feature, allowing users to customize their content feed based on interests [4] - Despite the appearance of user control, the platform has increased the weight of commercial content, with "shopping notes" gaining a 30% boost in visibility while pure sharing content sees a significant drop [6] Group 4: Content Quality Requirements - A new requirement mandates that posts must be at least 600 words to avoid being deprioritized in the algorithm, pushing creators to produce more substantial content [6]

Regulatory Developments - The Cyberspace Administration of China announced the interim results of algorithm governance, highlighting that major platforms like Douyin and Xiaohongshu have optimized their recommendation algorithms and introduced innovative features such as "Cocoon Assessment" and "One-Click Break Cocoon" [2] - Six departments, including the Ministry of Public Security and the National Internet Information Office, jointly released the "National Network Identity Authentication Public Service Management Measures," which will take effect on July 15. The measures emphasize the voluntary use of network numbers and certificates, with a focus on protecting minors and the elderly [3] - The State Administration for Market Regulation published the "Guidelines for Compliance of Charging Behavior on Online Trading Platforms (Draft for Comments)," which outlines eight unreasonable charging behaviors that platforms must avoid, including duplicate charges and price discrimination [4] - A total of 35 apps, including Zhiyu Qingyan and Kimi, were reported for illegal collection and use of personal information, as per the National Cyber and Information Security Information Notification Center [5] International Developments - The U.S. Department of Justice is investigating Google for potential antitrust violations related to its agreement with Character.AI, a chatbot manufacturer, to use its AI technology [6] - A California judge imposed a fine of $31,000 on two law firms for submitting documents that contained false and misleading legal citations without disclosing the use of AI [7][8] - A report from the International Labour Organization indicates that one-quarter of global jobs may be affected by generative AI, with high-income countries facing a higher impact rate of 34% [8] - A landmark case in the U.S. involves a lawsuit against Google and Character.AI related to a minor's suicide, with the court ruling that both companies must face the allegations [8]

Group 1 - The core viewpoint of the articles emphasizes the need for effective governance of algorithmic recommendations to address issues such as the promotion of low-quality content, information bubbles, and polarization of opinions [1][2][3] - The Chinese government has initiated a special action called "Clear and Bright: Governance of Typical Algorithm Issues on Online Platforms" to tackle algorithm misuse, which includes addressing problems like information bubbles and the infringement of workers' rights [1][2] - The implementation of the "Internet Information Service Algorithm Recommendation Management Regulations" in 2022 has set user rights protection requirements for algorithm service providers, prohibiting excessive recommendations and manipulation of rankings [1][2] Group 2 - Algorithm governance is recognized as a long-term and systematic project that requires a balance between promoting technological innovation and effective regulation [2][3] - The rapid iteration and self-learning capabilities of algorithms outpace existing regulatory measures, leading to gaps in oversight for emerging technologies and risks [2] - There is a call for a regulatory framework that adapts to technological advancements, with increased scrutiny on mature applications while allowing innovation space for nascent technologies [2] Group 3 - The challenge of algorithm governance is a global issue that impacts not only the online ecosystem but also national economic development and social stability [3] - Individuals are encouraged to enhance their digital literacy and critical thinking skills to create their own information defenses [3] - The articles advocate for improved algorithm regulation to ensure that technological innovation occurs alongside the management of potential social risks [3]

Core Insights - The article discusses the challenges and developments in algorithm governance, particularly in addressing issues like information silos and viewpoint polarization caused by recommendation algorithms [1][2][3] - It highlights the ongoing efforts by the Central Cyberspace Administration of China to optimize algorithm functions and enhance transparency, including the introduction of features like "cocoon assessment" and "one-click breaking the cocoon" [1][2] - The article emphasizes the need for continuous innovation in regulatory concepts and technologies to effectively manage algorithmic governance [3] Group 1: Algorithm Governance Challenges - The "Cocoon Room" phenomenon and viewpoint polarization are significant risks associated with algorithm recommendations, prompting regulatory actions [1] - The rapid growth of internet users, reaching 1.259 billion with an average usage time of over 175.8 hours per month, highlights the increasing influence of platforms and the challenges in governance [2] - Experts predict that platforms may assume quasi-legislative, quasi-judicial, and quasi-administrative powers, complicating oversight efforts [2] Group 2: Regulatory Innovations - The Central Cyberspace Administration has made strides in algorithm governance by publicly releasing hundreds of algorithm registration details [1][2] - A collaborative governance mechanism involving government, enterprises, media, research institutions, and users is essential for effective oversight [3] - The establishment of a multi-party algorithm governance experimental verification platform is proposed to enhance transparency and accountability in algorithmic processes [3]

Core Viewpoint - The article discusses the efforts of major online platforms in China to optimize their algorithm recommendation systems in response to government initiatives aimed at addressing issues such as the promotion of vulgar content, the exacerbation of "information cocoons," and the polarization of viewpoints [1][2]. Algorithm Transparency - Major platforms have taken steps to enhance algorithm transparency by publicly disclosing their operational rules and promoting user awareness [3]. - Douyin has established a "Safety and Trust Center" to explain its recommendation logic and governance outcomes [4]. - Weibo has improved the transparency of its trending search algorithms by publicizing ranking rules and data metrics [4]. - WeChat Video Account has utilized simple graphics and videos to inform users about its algorithm recommendations [4]. Breaking "Information Cocoons" - Platforms have introduced innovative features like "Cocoon Assessment" and "One-Click Break Cocoon" to help users mitigate the risks associated with "information cocoons" [5][6]. - Douyin has upgraded its "Usage Management Assistant" to visually present users' recent browsing content [6]. - Xiaohongshu has implemented features for content preference assessment and exploration of diverse recommendations [6]. - Kuaishou has enhanced its algorithm to promote positive and useful content [6]. Content Review Mechanism - Platforms are continuously improving their content review mechanisms to strengthen the promotion of positive content and prevent the recommendation of vulgar or harmful information [7][8]. - WeChat Video Account has refined its dual mechanism of "Friend Recommendations" and "Algorithm Recommendations" to better identify and eliminate inappropriate content [8]. - Douyin has introduced a verification mechanism for trending topics to prevent the spread of misleading or fabricated content [8]. User Empowerment - Platforms are optimizing features related to user interest management and content feedback to allow users to adjust their algorithmic recommendations [9]. - Kuaishou offers detailed interest preference management tools for users to customize content delivery [10]. - Weibo has provided various negative feedback options for users to express disinterest in certain content or creators [10]. - The government acknowledges that while progress has been made in algorithm governance, there are still gaps in functionality and content quality that need to be addressed [10].

资料图。本文来源： 中央网信办持续加强信息推荐算法治理 是一项长期性、系统性工程，网信部门将开展常态化巡查，督导信息推荐算法平台持续优化算法运 行机制和管理规则，不断提升推荐内容质量，探索多样化"破茧"路径，创新用户赋权功能，切实维 护网民合法权益。 ■ "清朗·网络平台算法典型问题治理"专项行动开展以来，针对网民反映强烈的算法推荐加热低俗信 息、加剧"信息茧房"、加重观点极化等问题风险，中央网信办督促指导重点平台针对性优化信息推 荐算法功能、调整信息推荐算法规则。重点平台积极响应，签署"算法向善"南宁宣言，完善算法推 荐内容审核，开设专门网站、频道或账号集中公开算法规则原理，开发上线"茧房评估""一键破 茧"等创新功能，完善用户兴趣偏好管理服务，提升算法推荐内容多样性。 近日，抖音、小红书、微博、快手、微信视频号、哔哩哔哩等平台围绕正能量内容加权推荐、用户 自主选择权保障、推荐内容多样性优化、提升算法透明度等核心环节，系统性优化完善多项功能。 在提升算法透明度方面。 公开算法运行规则，推进透明展示工作，保障用户知情权。抖音通过开 设"安全与信任中心"网站、举办开放日活动等方式，向公众阐释推荐逻辑、干预机制及 ...

中央网信办持续加强信息推荐算法治理。 "清朗·网络平台算法典型问题治理"专项行动开展以来，针对网民反映强烈的算法推荐加热低俗信息、加剧"信 息茧房"、加重观点极化等问题风险，中央网信办督促指导重点平台针对性优化信息推荐算法功能、调整信息 推荐算法规则。重点平台积极响应，签署"算法向善"南宁宣言，完善算法推荐内容审核，开设专门网站、频道 或账号集中公开算法规则原理，开发上线"茧房评估""一键破茧"等创新功能，完善用户兴趣偏好管理服务，提 升算法推荐内容多样性。 近日，抖音、小红书、微博、快手、微信视频号、哔哩哔哩等平台围绕正能量内容加权推荐、用户自主选择权 保障、推荐内容多样性优化、提升算法透明度等核心环节，系统性优化完善多项功能。 在提升算法透明度方面。公开算法运行规则，推进透明展示工作，保障用户知情权。抖音通过开设"安全与信 任中心"网站、举办开放日活动等方式，向公众阐释推荐逻辑、干预机制及治理成效。微博提升热搜算法透明 度，公示上榜规则、数据规则，上线热搜热度标签，标示热度背后的推动因素。微信视频号通过通俗易懂的图 文、视频方式向用户公示，发布《一图读懂微信视频号算法推荐》《算法破茧系列》。 在破除"信息 ...

今天（5月2 2日）1 0点，微信公众号"网信中国"发文称，中央网信办持续加强信息推荐算法治 理。 全文如下 ↓ ↓ "清朗·网络平台算法典型问题治理"专项行动开展以来，针对网民反映强烈的算法推荐加热低 俗信息、加剧"信息茧房"、加重观点极化等问题风险，中央网信办督促指导重点平台针对性 优化信息推荐算法功能、调整信息推荐算法规则。 重点平台积极响应，签署"算法向善"南宁宣言，完善算法推荐内容审核，开设专门网站、频 道或账号集中公开算法规则原理，开发上线"茧房评估" "一键破茧"等创新功能，完善用户兴 趣偏好管理服务，提升算法推荐内容多样性。 近 日 ， 抖 音 、 小 红 书 、 微 博 、 快 手 、 微 信 视 频 号 、 哔 哩 哔 哩 等 平 台 围 绕 正 能 量 内 容 加 权 推 荐、用户自主选择权保障、推荐内容多样性优化、提升算法透明度等核心环节，系统性优化 完善多项功能。 来 源 | 微信公众号"网信中国" 在完善推荐内容审核方面。不断健全推荐内容审核机制，加强正能量内容推送，防范算法推 荐低俗不良信息。微信视频号完善"好友推荐"和"算法推荐"双重机制，不断迭代升级识别打 击模型，严禁低俗恶 ...