Human Bias in Visual Data Analysis A Synthesis of Research to Empower Decision Makers | 16.07 MB
Title: Human Bias in Visual Data Analysis
Author: Emily Wall
Category: Nonfiction, Computers, Advanced Computing, Management Information Systems, Business & Finance, Industries & Professions, Information Management, Health & Well Being, Psychology, Developmental Psychology
Language: English | 232 Pages | ISBN: 9789819526130
Description:
This brief discusses how to deal with data visualization and prediction in human society, a context in which big data analysis and artificial intelligence have the potential to transform the world.
The debates presented in this brief combine different disciplines such as data-science, economics, political science, social informatics, informatics, philosophy of recognition and human actions, and artificial intelligence for human society.
Written by leading researchers from various disciplines, the brief provides fresh perspectives on the social impact of AI and evolution of human beings. As such, it offers a unique resource for all scholars and policymakers interested in the most exciting and fuzzy connections between disciplines, where knowledge in one field helps to answer questions in another.
This brief discusses how to deal with data visualization and prediction in human society, a context in which big data analysis and artificial intelligence have the potential to transform the world.
The debates presented in this brief combine different disciplines such as data-science, economics, political science, social informatics, informatics, philosophy of recognition and human actions, and artificial intelligence for human society.
Written by leading researchers from various disciplines, the brief provides fresh perspectives on the social impact of AI and evolution of human beings. As such, it offers a unique resource for all scholars and policymakers interested in the most exciting and fuzzy connections between disciplines, where knowledge in one field helps to answer questions in another.
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