乔伊·博拉维尼: 我如何与算法偏见对抗

我如何与算法偏见对抗

MIT的硕士生Joy Buolamwini在研发人脸识别软件的时候注意到一个问题：这个软件没能识别她的脸－因为程序员没有使软件去在一个很广的肤色和面部结构中识别人脸。现在，她在为机器学习的偏见作战，她把这个现象称作为“代码的凝视 “。算法正在控制我们生活越来越多的方面，这是一个开阔眼界的关于编程责任的演讲。

Algorithmic bias can exclude and discriminate at lightning speed, affecting millions without warning. When facial recognition software failed to detect a face unless a white mask was worn, the flaw exposed a deeper issue: undiverse training data shapes who technology serves. With police departments accessing facial recognition networks containing over 117 million Americans, unchecked algorithms risk reinforcing unfair practices. Addressing who codes, how they code, and why they code is essential to building technology that works for everyone.

Algorithmic Bias Spreads Faster Than Human Prejudice

*Unmasking AI: My Mission to Protect What Is Human in a World of Machines*

"Meet the computer scientist and activist who got Big Tech to stand down"

activism

algorithm

code

data

identity

product design

innovation

software

TEDx

technology

race

equality

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