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Neural Networks Need Data to Learn. Even If It’s Fake.
Real data can be hard to get, so researchers are turning to synthetic data to train their artificial intelligence systems.
The Computer Scientist Peering Inside AI’s Black Boxes
Cynthia Rudin wants machine learning models, responsible for increasingly important decisions, to show their work.
The Researcher Who Would Teach Machines to Be Fair
Arvind Narayanan uses quantitative methods to expose and correct the misuse of quantitative methods.
How Big Data Carried Graph Theory Into New Dimensions
Researchers are turning to the mathematics of higher-order interactions to better model the complex connections within their data.
A Computer Scientist Who Tackles Inequality Through Algorithms
Rediet Abebe uses the tools of theoretical computer science to understand pressing social problems — and try to fix them.
To Build Truly Intelligent Machines, Teach Them Cause and Effect
Judea Pearl, a pioneering figure in artificial intelligence, argues that AI has been stuck in a decades-long rut. His prescription for progress? Teach machines to understand the question why.