Open AccessAnalysis of the Adaptive Representation of Artificial Intelligence Uncertainty
Author(s) -
Jinfeng Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1684/1/012003
Subject(s) - corporate governance , representation (politics) , artificial intelligence , context (archaeology) , computer science , uncertainty analysis , economics , political science , management , biology , simulation , paleontology , politics , law
This article analyzes the uncertainty of artificial intelligence. The uncertainty of artificial intelligence includes algorithm and data uncertainty, knowledge uncertainty, consequence uncertainty and context uncertainty. The author combined artificial intelligence to analyze the adaptive representation of uncertainty. This article studies how to clarify governance principles, how to do a good job in artificial intelligence assessment, how to strengthen technological governance, measures to introduce social governance and improve global governance. The author’s purpose is to reduce the uncertainty of artificial intelligence and enhance the application effect of artificial intelligence in the industry.