Ethical Implications Of Bias In Machine Learning

被引：0
|
作者：
Yapo, Adrienne [1 ]
Weiss, Joseph [1 ]
机构：
[1] Bentley Univ, 175 Forest St, Waltham, MA 02452 USA
来源：
PROCEEDINGS OF THE 51ST ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS) | 2018年
关键词：
ARTIFICIAL-INTELLIGENCE;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Biases in AI and machine learning algorithms are presented and analyzed through two issues management frameworks with the aim of showing how ethical problems and dilemmas can evolve. While "the singularity" concept in AI is presently more predictive than actual, both benefits and damage that can result by failure to consider biases in the design and development of AI. Inclusivity and stakeholder awareness regarding potential ethical risks and issues need to be identified during the design of AI algorithms to ensure that the most vulnerable in societies are protected from harm.
引用
收藏
页码：5365 / 5372
页数：8
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