To Live in Their Utopia: Why Algorithmic Systems Create Absurd Outcomes

A. Alkhatib
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引用次数: 39

Abstract

The promise AI’s proponents have made for decades is one in which our needs are predicted, anticipated, and met - often before we even realize it. Instead, algorithmic systems, particularly AIs trained on large datasets and deployed to massive scales, seem to keep making the wrong decisions, causing harm and rewarding absurd outcomes. Attempts to make sense of why AIs make wrong calls in the moment explain the instances of errors, but how the environment surrounding these systems precipitate those instances remains murky. This paper draws from anthropological work on bureaucracies, states, and power, translating these ideas into a theory describing the structural tendency for powerful algorithmic systems to cause tremendous harm. I show how administrative models and projections of the world create marginalization, just as algorithmic models cause representational and allocative harm. This paper concludes with a recommendation to avoid the absurdity algorithmic systems produce by denying them power.
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生活在他们的乌托邦:为什么算法系统创造荒谬的结果
人工智能的支持者几十年来做出的承诺是,我们的需求经常在我们意识到之前就被预测、预测和满足。相反,算法系统,特别是在大数据集上训练并大规模部署的人工智能,似乎一直在做出错误的决定,造成伤害并奖励荒谬的结果。试图弄清楚为什么人工智能会在当下做出错误的调用,解释了错误的实例,但围绕这些系统的环境是如何促成这些实例的,仍然很模糊。本文借鉴了关于官僚机构、国家和权力的人类学研究成果,将这些观点转化为一种理论,描述了强大的算法系统造成巨大伤害的结构性趋势。我展示了管理模式和对世界的预测是如何造成边缘化的,就像算法模型会造成代表性和分配性的损害一样。本文最后提出了通过拒绝算法系统的权力来避免算法系统产生的荒谬性的建议。
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