High Tech, High Risk: Tech Ethics Lessons for the COVID-19 Pandemic Response

被引:16
|
作者
Moss, Emanuel [1 ,2 ]
Metcalf, Jacob [1 ]
机构
[1] Data & Soc Res Inst, New York, NY 10010 USA
[2] CUNY, Grad Ctr, New York, NY 10016 USA
来源
PATTERNS | 2020年 / 1卷 / 07期
关键词
DSML 1: Concept: Basic principles of a new data science output observed and reported;
D O I
10.1016/j.patter.2020.100102
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The COVID-19 pandemic has, in a matter of a few short months, drastically reshaped society around the world. Because of the growing perception of machine learning as a technology capable of addressing large problems at scale, machine learning applications have been seen as desirable interventions in mitigating the risks of the pandemic disease. However, machine learning, like many tools of technocratic governance, is deeply implicated in the social production and distribution of risk and the role of machine learning in the production of risk must be considered as engineers and other technologists develop tools for the current crisis. This paper describes the coupling of machine learning and the social production of risk, generally, and in pandemic responses specifically. It goes on to describe the role of risk management in the effort to institutionalize ethics in the technology industry and how such efforts can benefit from a deeper understanding of the social production of risk through machine learning.
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收藏
页数:8
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