AI 中文总结
本研究以准确性为案例，探讨机器学习界与法律界对其的不同预期，指出二者在准确性理解上的五大张力，建议标准化中的基线与干预性研究，以及扩展准确性测量有效性的工具需求。
AI 中文摘要
机器学习领域的发展部分依赖于提升系统的“准确性”。欧盟AI法案明确将“准确性”作为高风险AI系统合规措施的一部分。我们讨论的是同一个“准确性”概念吗？本研究以“准确性”为案例，探讨社会界、技术机器学习界与法律界的不同要求。虽然围绕准确性的竞争有助于技术发展，但机器学习学者同时认识到准确性在系统实用性和有效性方面的缺陷。法律界则接受“准确性”的模糊性，为技术和社会变革留下解释空间，同时准确性是欧盟AI法案合规的核心要素。我们阐述了五大主要张力：(a)准确性的本质、(b)性能的概念、(c)有效性的范围、(d)目的、(e)统计性，以展示两个群体对准确性的预期存在差异甚至矛盾。法律和技术群体在各自领域边界之外都缺乏对“准确性”的精确理解，由此产生的摩擦（例如基于对准确性的经验或规范理解）是关于准确性本质的未解决且无法解决的争论的表现。我们建设性地利用这些摩擦，建议在标准化中设立基线和干预性研究，并要求开发工具以扩展准确性测量的有效性。
英文摘要
The machine learning community progresses (in part) by improving the "accuracy" of its systems. The EU AI Act explicitly refers to "accuracy" as part of its compliance measures for high-risk AI systems. Are we talking about the same thing? This work presents "accuracy" as a case-study for differing requirements of social worlds, the technological machine learning community and the legal community. While competition on accuracy contributes to technological development, machine learning scholars simultaneously recognize accuracy's shortcomings regarding the usefulness and effectiveness of machine learning systems. The legal counterpart embraces the vagueness of "accuracy," leaving interpretative flexibility for technological and societal changes. At the same time, accuracy is a core element of compliance within the EU AI Act. We elaborate on five main tensions, (a) nature of accuracy, (b) notion of performance, (c) scope of validity, (d) ends, and (e) statisticalness, to show that the two communities project disparate, and sometimes contradictory, expectations on accuracy. Both legal and technical communities lack precise understanding of "accuracy" beyond the contextual boundaries of their community. The resulting frictions, \eg, based on the empirical or normative understanding of accuracy, are symptoms of an unresolved (and unresolvable) debate on what accuracy is. We constructively use the frictions to recommend baselines and interventional studies in standardization, and demand for tools to extend the validity of accuracy measurements.
