Princeton University

CITP Lecture: Amanda Coston - Responsible Machine Learning through the Lens of Causal Inference

Machine learning algorithms are widely used for decision making in societally high-stakes settings from child welfare and criminal justice to healthcare and consumer lending. Recent history has ...
Diginomica

How causal analysis and AI intersect - methods of causal inference

Our foray into causal analysis is not yet complete. Until we define the methods of causal inference, we can't get to the deeper insights that causal analysis can provide. This article details many of ...
Times Higher Education

Research Engineer (Federated Causal Inference in Heterogeneous Data Environments) - UP

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are ...
mccormick.northwestern.edu

COMP_SCI 374: Causal Graphical Models

We know that correlation does not imply causation, but careful analyses of correlations are often our only way to quantify cause and effect in domains ranging from healthcare to education. This ...
EDN

Intel to release first ‘causal’ learning algorithms

PORTLAND, Ore. — Intel Corp. is unveiling a do-everything machine learning package capable of fusing separate streams from real-time sensors as easily as spotting and identifying objects and ...
Science Daily

Revealing causal links in complex systems

SURD, an algorithm, reveals causal links in complex systems. Applications may include forecasting climate to projecting population growth to designing efficient aircraft. Getting to the heart of ...