Towards fair and pro-social employment of digital pieceworkers for sourcing machine learning training data
Towards fair and pro-social employment of digital pieceworkers for sourcing machine learning training data
复制标题
DOI：
10.1145/3491101.3516384
复制
发表时间：
2022-04
期刊：
影响因子：
--
通讯作者：
Annabel Rothschild;J. Booker;Christa Davoll;Jessica Hill;Venise Ivey;C. Disalvo;B. Shapiro;Betsy Disalvo
中科院分区：
文献类型：
--
作者：
Annabel Rothschild;J. Booker;Christa Davoll;Jessica Hill;Venise Ivey;C. Disalvo;B. Shapiro;Betsy Disalvo
虽然存在不良行为者，但平台的分布式性质可能会导致请求者的这些不当行为看起来是出于误解，而不是出于恶意。为此，我们提出了一份封面页，描述通过众包工作平台参与的学术 1 合作者（或“众包合作者”）的精确招聘和就业实践。封面页应与学术场所研究人员发表的成果一起提交。封面设计的灵感来自于数据表项目[13]的数据集，该项目是接受人群协作劳动成果（即机器学习训练数据集）的学术场所所要求的。正如 Hießl 所说，群体合作者没有可以依赖的传统雇佣合同，必须开发一种新形式的合同来解决数字计件工作的复杂性 [16]；我们将这张封面作为朝这个方向迈出的第一步。通过在机构层面上公开这些信息，我们希望 1) 在请求者不知情的情况下告知他们最佳实践，2) 证明对人群合作者的尊重，特别是考虑到用数字计件工作替代面部自动化中失去的工作的呼声 [20, 29]。我们的干预以学术请求为中心有两个原因。首先，我们选择强调这些平台中请求者的角色，因为由于供应过剩，权力平衡不可避免地从那些执行劳动的人转移到那些提供劳动的人。
, while there are bad actors, the distributed nature of the platforms may cause requesters to appear to enact these malpractices out of misunder-standing more than malintent. For this purpose, we propose a cover sheet describing precise hiring and employment practices of academic 1 collaborators (or “crowd collaborators” ) engaged through crowd-working platforms. The cover sheet is to be submitted with the publication of the resulting work by researchers in academic venues. The design of the cover sheet is inspired by the Datasets for Datasheets project [13], to be required by academic venues accepting the results of crowd collaborator labor, namely machine learning training datasets. As Hießl argues, crowd collaborators do not have traditional employment contracts to rely on and that a new form of contract must be developed to address the complexity of digital piecework [16]; we present this cover sheet as a frst step in that direction. By surfacing this information at the institutional level we hope to 1) inform requesters of the best practices if they are unaware, and 2) certify respectful treatment of crowd collaborators, especially given the calls to substitute digital piecework for jobs lost in the face automation [20, 29]. Our intervention centers academic requesters for two reasons. First, we choose to highlight the role of requesters in these platforms as the power balance is inevitably shifted away from those performing the labor to those providing it, due to the oversupply of