Editor's Introduction: Humanities in the Loop

Lauren M. E. Goodlad
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Abstract

Abstract This editor's introduction welcomes readers to a new interdisciplinary undertaking. The community of practice Critical AI addresses hopes to bring critical thinking of the kind that interpretive disciplines foster into dialogue with work by technologists and others who share the understanding of interdisciplinary research as a powerful tool for building accountable technology in the public interest. Critical AI studies aims to shape and activate conversations in academia, industry, policymaking, media, and the public at large. The long and ongoing history of “AI,” including the data-driven technologies that now claim that name, remains riddled by three core dilemmas: (1) reductive and controversial meanings of “intelligence”; (2) problematic benchmarks and tests for supposedly scientific terms such as “AGI”; and (3) bias, errors, stereotypes, and concentration of power. AI hype today is steeped in blends of utopian and dystopian discourse that distract from the real-world harms of existing technologies. In reality, what is hyped and anthropomorphized as “AI” and even “AGI” is the product not only of technology companies and investors but also—and more fundamentally—of the many millions of people and communities subject to copyright infringement, nonconsensual use of data, bias, environmental harms, and the low-wage and high-stress modes of “human in the loop” through which systems for probabilistic mimicry improve their performance in an imitation game.
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编者简介:人文在循环
这篇编辑的介绍欢迎读者了解一项新的跨学科事业。实践批判性人工智能社区希望将解释性学科培养的那种批判性思维与技术专家和其他人的工作进行对话,这些技术专家和其他人将跨学科研究作为构建公共利益负责任技术的强大工具。关键的人工智能研究旨在塑造和激活学术界、工业界、政策制定、媒体和广大公众的对话。“人工智能”的漫长而持续的历史,包括现在声称这一名称的数据驱动技术,仍然受到三个核心困境的困扰:(1)“智能”的简化和有争议的含义;(2)对“AGI”等所谓的科学术语进行有问题的基准和测试;(3)偏见、错误、刻板印象和权力集中。如今的人工智能炒作充斥着乌托邦和反乌托邦的话语,分散了人们对现有技术在现实世界中的危害的关注。实际上,那些被炒作和拟人化为“人工智能”甚至“AGI”的东西,不仅是科技公司和投资者的产物,也是——更根本的是——数百万人和社区受到版权侵犯、未经同意使用数据、偏见、环境危害以及“人在循环”的低工资和高压力模式的影响,通过这种模式,概率模仿系统可以提高它们在模仿游戏中的表现。
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