监控研究和人工智能的历史:一个错失的机会?

Aaron Gluck-Thaler
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引用次数: 0

摘要

本研究报告考虑了监控学者如何处理通过人工智能(AI)进行的监控所涉及的历史遗产。《监视》杂志中相对缺乏的历史研究;该报告认为,在监控人工智能的背景下,非历史分析的风险尤其高。该报告将科学史上的学术研究与监测研究联系起来,探讨了今天的人工智能技术如何重振一段更长的历史,即关于分类的科学知识生产是如何与种族、性别和社会等级的维持和生产共同扩展的。该说明简要地考察了一个谱系——模式识别领域的历史,它与国家监视的关系,以及它对识别作为分类问题的理解——以考虑监视和人工智能是如何偶然融合的。该说明最后展示了这些历史如何帮助监控学者批判性地重新评估对当今使用的人工智能和与人工智能相关的监控实践的后果的共同理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Surveillance Studies and the History of Artificial Intelligence: A Missed Opportunity?
This research note considers how scholars of surveillance might approach the historical legacies that surveillance through artificial intelligence (AI) is implicated in. Engaging with the relative lack of historical studies within the pages of Surveillance & Society, the note argues that in the context of surveillant AI the stakes of an ahistorical analysis are especially high. Bridging scholarship within the history of science with surveillance studies, the note explores how AI techniques today reanimate a longer history of how scientific knowledge production on classification has been coextensive with the maintenance and production of racial, gender, and social hierarchies. The note briefly examines one genealogy––the history of the field of pattern recognition, its relationship to state surveillance, and its understanding of identification as a problem of classification––to consider how surveillance and AI contingently converged. The note concludes by showing how such histories can help scholars of surveillance critically reassess common understandings of the consequences of AI and AI-adjacent surveillance practices used today.
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