Open AccessPatterns and Antipatterns, Principles, and Pitfalls: Accountability and Transparency in Artificial Intelligence
Author(s) -
Matthews Jeanna
Publication year - 2020
Publication title -
ai magazine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.597
H-Index - 79
eISSN - 2371-9621
pISSN - 0738-4602
DOI - 10.1609/aimag.v41i1.5204
Subject(s) - transparency (behavior) , accountability , set (abstract data type) , computer science , management science , engineering management , data science , process management , knowledge management , artificial intelligence , engineering , political science , computer security , law , programming language
This article discusses a set of principles for accountability and transparency in AI as well as a set of antipatterns or harmful trends too often seen in deployed systems. It provides concrete suggestions for what can be done to shift the balance away from these antipatterns and toward more positive ones.