AAAI

@RealAAAI

Founded in 1979, AAAI is an international, nonprofit, scientific society devoted to promote research in, and responsible use of Artificial Intelligence.

Washington, DC

aaai.org

Joined February 2017

AAAI
@RealAAAI
Aug 10
Metadata is the foundation of trustworthy, reproducible AI. In the article "The Metadata Ecosystem and AI: Enabling FAIR and AI-Ready Data" by Jane Greenberg, Joel Pepper, Xintong Zhao, Richard Marciano, David Breen, and Yuan An, the authors explore how well-structured metadata
AAAI
@RealAAAI
Aug 7
Metadata is the foundation of trustworthy, reproducible AI. In the article "The Metadata Ecosystem and AI: Enabling FAIR and AI-Ready Data" by Jane Greenberg, Joel Pepper, Xintong Zhao, Richard Marciano, David Breen, and Yuan An, the authors explore how well-structured metadata
AAAI
@RealAAAI
Aug 6
"Knowledge Engineering for Open Science: Building and Deploying Knowledge Bases for Metadata Standards" by Mark A. Musen, Martin J. O'Connor, Josef Hardi, and Marcos Martínez-Romero explores how knowledge engineering and the CEDAR Workbench help scientific communities create and
onlinelibrary.wiley.com
Knowledge Engineering for Open Science: Building and Deploying Knowledge Bases for Metadata...
For more than a decade, scientists have been striving to make their datasets available in open repositories, with the goal that they be findable, accessible, interoperable, and reusable (FAIR)....
AAAI
@RealAAAI
Aug 5
Datasheets for Machine Learning Sensors" by Matthew Stewart, Yuke Zhang, Pete Warden, Yasmine Omri, Shvetank Prakash, Jacob Huckelberry, João H. Santos, Scott Hymel, Brian Y. Brown, Jim MacArthur, Nathan Jeffries, Emanuel Moss, Michael Sloane, Brian Plancher, and Vijay Janapa
AAAI
@RealAAAI
Aug 4
"An Actionable Framework for AI-Ready Data"" by Nikita Majithia, Tom Carey-Wilson, Elena Simperl, and Nigel Shadbolt is available in the Special Issue of AI Magazine. In this article, the authors introduce a practical framework for evaluating whether datasets are prepared for AI
onlinelibrary.wiley.com
An actionable framework for AI‐ready data
Data is the foundation of AI. Poor-quality data drive up costs and can lead to hidden problems for AI models, especially in complex fields such as healthcare and manufacturing. Meanwhile, biased...