“Data Strikes”: Evaluating the Effectiveness of a New Form of Collective Action Against Technology Companies
“Data Strikes”: Evaluating the Effectiveness of a New Form of Collective Action Against Technology Companies
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DOI：
10.1145/3308558.3313742
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发表时间：
2019-05
期刊：
影响因子：
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通讯作者：
Nicholas Vincent;Brent J. Hecht;Shilad Sen
中科院分区：
文献类型：
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作者：
Nicholas Vincent;Brent J. Hecht;Shilad Sen
公众越来越关注大型科技公司在隐私和许多其他问题上的做法。为了迫使这些做法发生变化，越来越多的人呼吁“数据罢工”。这些新类型的集体行动将寻求通过缺乏急需的培训数据的业务关键模型(例如推荐系统、排名算法)来为公众创造杠杆作用。然而，人们对数据罢工将如何运作知之甚少，更不用说它们的效果了。聚焦于推荐系统这一重要的商业领域，我们模拟了各种条件下的数据攻击，并探索了它们如何增强传统的抵制。我们的结果表明，数据罢工可能是有效的，而且用户在与科技公司的关系中比与其他公司的关系拥有更大的权力。然而，我们的结果也突出了潜在组织者必须考虑的重要权衡和挑战。
The public is increasingly concerned about the practices of large technology companies with regards to privacy and many other issues. To force changes in these practices, there have been growing calls for “data strikes.” These new types of collective action would seek to create leverage for the public by starving business-critical models (e.g. recommender systems, ranking algorithms) of much-needed training data. However, little is known about how data strikes would work, let alone how effective they would be. Focusing on the important commercial domain of recommender systems, we simulate data strikes under a wide variety of conditions and explore how they can augment traditional boycotts. Our results suggest that data strikes can be effective and that users have more power in their relationship with technology companies than they do with other companies. However, our results also highlight important trade-offs and challenges that must be considered by potential organizers.