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Stewardship in the 'Age of Algorithms'

机译：“算法时代”的管理

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This paper explores pragmatic approaches that might be employed to document the behavior of large, complex socio-technical systems (often today shorthanded as “algorithms”) that centrally involve some mixture of personalization, opaque rules, and machine learning components. Thinking rooted in traditional archival methodology — focusing on the preservation of physical and digital objects, and perhaps the accompanying preservation of their environments to permit subsequent interpretation or performance of the objects — has been a total failure for many reasons, and we must address this problem. The approaches presented here are clearly imperfect, unproven, labor-intensive, and sensitive to the often hidden factors that the target systems use for decision-making (including personalization of results, where relevant); but they are a place to begin, and their limitations are at least outlined. Numerous research questions must be explored before we can fully understand the strengths and limitations of what is proposed here. But it represents a way forward. This is essentially the first paper I am aware of which tries to effectively make progress on the stewardship challenges facing our society in the so-called “Age of Algorithms;” the paper concludes with some discussion of the failure to address these challenges to date, and the implications for the roles of archivists as opposed to other players in the broader enterprise of stewardship — that is, the capture of a record of the present and the transmission of this record, and the records bequeathed by the past, into the future. It may well be that we see the emergence of a new group of creators of documentation, perhaps predominantly social scientists and humanists, taking the front lines in dealing with the “Age of Algorithms,” with their materials then destined for our memory organizations to be cared for into the future.
机译：本文探讨了可用于记录大型复杂的社会技术系统（今天通常简称为“算法”）行为的务实方法，这些系统主要涉及个性化，不透明规则和机器学习组件的混合。植根于传统档案学方法的思想-着重于对物理和数字对象的保存，以及可能随之而来的对环境的保存，以允许对这些对象的后续解释或性能进行处理-由于许多原因，这已经完全失败了，我们必须解决这个问题。这里介绍的方法显然是不完善的，未经证实的，劳动密集型的，并且对目标系统用于决策（包括相关结果的个性化）的通常隐藏的因素敏感;但它们是一个起点，并且至少概述了它们的局限性。在我们完全了解这里提出的优点和局限之前，必须探索许多研究问题。但这代表了前进的道路。这实质上是我所知道的第一篇论文，该论文试图在所谓的“算法时代”中有效应对社会所面临的管理挑战。本文最后讨论了迄今未能解决这些挑战的情况，以及档案工作者在更广泛的管理工作中相对于其他参与者的作用的含义，即记录了当下的情况并传递了这些信息。记录，以及记录由过去传给未来。很有可能，我们看到了一个新的文档创建者团队的出现，也许主要是社会科学家和人文主义者，在处理“算法时代”方面走在前线，其材料随后将运用于我们的存储组织。关心未来。

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