【环球网科技综合报道】"跑了那么多年车，之前都没真正清晰地了解过平台的算法和规则。"一位跑了 7年城配的货车司机，这样形容过去的感受。话虽朴素，却道出了平台经济长期存在的"关系困境"：劳 动者与算法之间缺乏对话界面，部分规则不透明、不可议、不可改，于是"误解"被沉淀为"成见"。当新 就业形态劳动者突破8000万人、数字经济规模占GDP比重超40%的今天，如果继续把劳动者排除在算法 之外，不仅伤害个体尊严，也将抬高整个社会的制度性交易成本。破解之道，首在"把墙变成窗"——让 规则可见，让协商可及，让治理可感。 开放倾听与规则可视化只是第一步，关键在于将协商成果转化为实际举措。平台还需在算法优化、权益 保障、常态化协商这三个层面持续发力。 破局的关键在于打破"企业单方面决策"的闭环，构建开放对话机制。 以货拉拉为例，其已于公司官网增设"算法公开"入口，将适时对平台算法和规则等进行公开，内容以图 文可视化的形式呈现，确保算法和规则通俗易懂，并多次调整分播单算法，将"就近优先"订单占比从 90%提升至93%。这种调整不仅提升了司机收入效率，也增强了其对平台的认同感。而针对运费拖欠、 职业伤害等痛点，货拉拉推出"预付+ ...

Core Insights - The "Court Informationization Blue Book" released by the Chinese Academy of Social Sciences highlights significant advancements in online litigation processes, particularly in civil and administrative second-instance cases, with over 370,000 online filings by the end of 2024, reducing the average filing time by over 70% compared to pre-trial periods [1][2] Group 1: Online Litigation Developments - The pilot program for online second-instance filings has been implemented in 16 regions, allowing for same-day applications and filings [1] - Shandong High Court has processed 99,000 online second-instance applications, with an average filing time reduction of over two-thirds [2] Group 2: Cross-Domain Litigation Services - The Supreme People's Court has guided 13 pilot regions to provide cross-domain services, significantly lowering litigation costs and enabling local processing of legal matters [2] Group 3: Dispute Resolution Innovations - The court's informationization efforts have led to the establishment of a mediation platform that has resolved over 2.5 million disputes through local governance units [3] Group 4: Technological Integration and Recommendations - The blue book emphasizes the need for developing specialized models for court litigation to reduce reliance on external technologies and suggests regular assessments of algorithm fairness and reliability [4]

Core Viewpoint - The digital freight platform Huolala has announced its second batch of algorithm disclosure measures, aimed at enhancing fairness and reducing costs for drivers [1] Group 1: Algorithm Disclosure - The disclosed content includes dynamic evaluation algorithms and rules to improve the fairness of order distribution [1] - The optimization of the automatic commission reduction algorithm is part of ongoing efforts to alleviate financial burdens on drivers [1] Group 2: Driver Support Initiatives - Huolala has improved its "driver autonomy, proximity priority" order distribution model, increasing the proportion of orders prioritized by distance from 90% to 93% [1] - The platform plans to launch additional driver commission reduction products, expecting to lower commissions by a total of 230 million yuan by 2025 [1] - The company will increase order subsidies, with an anticipated annual investment of nearly 70 million yuan to enhance driver income [1]

Group 1 - The core issue of "big data killing familiarity" involves platforms using personal data to implement differential pricing, leading to consumer dissatisfaction [1] - Consumers report being charged more for the same products in live-streaming sessions, highlighting a lack of transparency in pricing [1] - The collection of personal information and the subsequent analysis of consumer habits are the preliminary steps that enable differential pricing strategies [1] Group 2 - Algorithms should not operate outside of governance; their design and application must align with human-centered principles to protect consumer rights [2] - There is a call for platforms to adopt an open approach, enhancing algorithm transparency to combat "big data killing familiarity" [2] - Recommendations include returning control of information recommendations to users and establishing industry standards to improve algorithm transparency [2]