Data Collectives as a means to Improve Accountability, Combat Surveillance and Reduce Inequalities
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866914932088373248 |
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| author | Hsieh, Jane Zhang, Angie Kim, Seyun Rao, Varun Nagaraj Dalal, Samantha Mateescu, Alexandra Grohmann, Rafael Do Nascimento Eslami, Motahhare Lee, Min Kyung Zhu, Haiyi |
| author_facet | Hsieh, Jane Zhang, Angie Kim, Seyun Rao, Varun Nagaraj Dalal, Samantha Mateescu, Alexandra Grohmann, Rafael Do Nascimento Eslami, Motahhare Lee, Min Kyung Zhu, Haiyi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_00737 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Data Collectives as a means to Improve Accountability, Combat Surveillance and Reduce Inequalities Hsieh, Jane Zhang, Angie Kim, Seyun Rao, Varun Nagaraj Dalal, Samantha Mateescu, Alexandra Grohmann, Rafael Do Nascimento Eslami, Motahhare Lee, Min Kyung Zhu, Haiyi Human-Computer Interaction 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. |
| title | Data Collectives as a means to Improve Accountability, Combat Surveillance and Reduce Inequalities |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2409.00737 |