数据集体作为改善问责制、对抗监控和减少不平等的一种手段
Data Collectives as a means to Improve Accountability, Combat Surveillance and Reduce Inequalities
AI总结：
本文提出利用数据女性主义等框架设计可持续且具有权力意识的数据集体，以应对在线劳动平台中的算法不透明、监控和不平等问题，并通过合作设计推动问责制和政策发展。
摘要：
基于平台的劳动者面临着由算法不透明、数据透明度不足以及政策和法规不明确所导致的空前挑战和工作条件。CSCW和HCI社区越来越多地转向劳动者数据集体，以此作为推进相关政策和法规、要求平台对数据透明度和披露负责以及增强集体劳动者话语权的一种手段。然而，在设计、治理和维持此类数据基础设施方面仍存在根本性问题。在本次研讨会中，我们利用数据女性主义等框架来设计可持续且具有权力意识的数据集体，以应对各类在线劳动平台（例如网约车、自由职业、众包工作、照护工作）中存在的挑战。虽然数据集体旨在支持劳动者集体并补充相关政策倡议，但本次研讨会的目标是鼓励其设计者考虑治理、隐私、信任和透明度等主题。在这个为期一天的会议中，我们召集研究和倡导社区成员，反思关键的平台工作问题（例如劳动者监控、歧视、工资盗窃、平台问责不足），并合作设计数据集体，通过支持劳动者集体主义和为政策制定提供信息，以合乎伦理且公平的方式解决这些问题。
英文摘要：
Platform-based laborers face unprecedented challenges and working conditions that result from algorithmic opacity, insufficient data transparency, and unclear policies and regulations. The CSCW and HCI communities increasingly turn to worker data collectives as a means to advance related policy and regulation, hold platforms accountable for data transparency and disclosure, and empower the collective worker voice. However, fundamental questions remain for designing, governing and sustaining such data infrastructures. In this workshop, we leverage frameworks such as data feminism to design sustainable and power-aware data collectives that tackle challenges present in various types of online labor platforms (e.g., ridesharing, freelancing, crowdwork, carework). While data collectives aim to support worker collectives and complement relevant policy initiatives, the goal of this workshop is to encourage their designers to consider topics of governance, privacy, trust, and transparency. In this one-day session, we convene research and advocacy community members to reflect on critical platform work issues (e.g., worker surveillance, discrimination, wage theft, insufficient platform accountability) as well as to collaborate on codesigning data collectives that ethically and equitably address these concerns by supporting working collectivism and informing policy development.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
