生成对抗性网络的语用伦理学:耦合、机器人和机器学习

IF 0.1 4区 哲学 0 PHILOSOPHY
M. Tschaepe
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引用次数: 1

摘要

本文解决了机器学习中自适应伦理分析的需求,该分析解释了有关社会偏见和生成对抗性网络(gan)的新问题。我以约翰·杜威对心理学中反射弧概念的批评为基础来理解这些问题是如何源于人与人之间的互动的。通过将杜威的批评与Donna Haraway的半机械人思想、Luciano Floridi的分布式道德概念以及Shaowen Bardzell对人机交互女权主义方法的建议相结合,我提出了一个动态的视角,从这个视角开始分析和解决机器学习这一特定领域中明显存在的不公正问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pragmatic Ethics for Generative Adversarial Networks: Coupling, Cyborgs, and Machine Learning
This article addresses the need for adaptive ethical analysis within machine learning that accounts for emerging problems concerning social bias and generative adversarial networks (gan s). I use John Dewey’s criticisms of the reflex arc concept in psychology as a basis for understanding how these problems stem from human-gan interaction. By combining Dewey’s criticisms with Donna Haraway’s idea of cyborgs, Luciano Floridi’s concept of distributed morality, and Shaowen Bardzell’s recommendations for a feminist approach to human-computer interaction, I suggest a dynamic perspective from which to begin analyzing and solving issues of injustice evident in this particular domain of machine learning.
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来源期刊
CiteScore
0.40
自引率
0.00%
发文量
22
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