In her 2021 IC2S2 keynote talk, “Critical Data Theory,” Margaret Hu builds off Critical Race Theory, privacy law, and big data surveillance to grapple with questions at the intersection of big data and legal jurisprudence. As a legal scholar, Hu’s work focuses primarily on issues of governance and regulation—examining the legal and constitutional impact of modern data collection and analysis. Yet, her call for Critical Data Theory has important implications for the field of Computational Social Science (CSS) as a whole. In this article, I therefore reflect on Hu’s conception of Critical Data Theory and its broader implications for CSS research. Specifically, I’ll consider the ramifications of her work for the scientific community—exploring how we as researchers should think about the ethics and realities of the data which forms the foundations of our work.

在 2021 年 IC2S2 主题演讲“关键数据理论”中，Margaret Hu 以批判种族理论、隐私法和大数据监控为基础，以解决大数据和法律法理学交叉点的问题。作为一名法律学者，胡的工作主要关注治理和监管问题——审视现代数据收集和分析的法律和宪法影响。然而，她对批判数据理论的呼吁对整个计算社会科学（CSS）领域具有重要意义。因此，在本文中，我反思了 Hu 的关键数据理论概念及其对 CSS 研究的更广泛影响。具体来说，我将考虑她的工作对科学界的影响——探索我们作为研究人员应该如何思考构成我们工作基础的数据的道德和现实。