The Seven Tools of Causal Inference, with Reflections on Machine Learning

被引:352
作者
Pearl, Judea [1 ,2 ]
机构
[1] Univ Calif Los Angeles, Comp Sci & Stat, Los Angeles, CA 90095 USA
[2] Univ Calif Los Angeles, Cognit Syst Lab, Los Angeles, CA 90095 USA
基金
美国国家科学基金会;
关键词
D O I
10.1145/3241036
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
THE DRAMATIC SUCCESS In machine learning has led to an explosion of artificial intelligence (AI) applications and increasing expectations for autonomous systems that exhibit human-level intelligence. These expectations have, however, met with fundamental obstacles that cut across many application areas. One such obstacle is adaptability, or robustness. Machine learning researchers have noted current systems lack the ability to recognize or react to new circumstances they have not been specifically programmed or trained for. © 2019 ACM.
引用
收藏
页码:54 / 60
页数:7
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