Search Results for author: Nicholas Schmidt

Found 2 papers, 1 papers with code

An Introduction to Artificial Intelligence and Solutions to the Problems of Algorithmic Discrimination

no code implementations8 Nov 2019 Nicholas Schmidt, Bryce Stephens

In this article, we provide an overview of the potential benefits and risks associated with the use of algorithms and data, and focus specifically on fairness.

Fairness

Proposed Guidelines for the Responsible Use of Explainable Machine Learning

5 code implementations8 Jun 2019 Patrick Hall, Navdeep Gill, Nicholas Schmidt

Explainable machine learning (ML) enables human learning from ML, human appeal of automated model decisions, regulatory compliance, and security audits of ML models.

BIG-bench Machine Learning Explainable artificial intelligence +1

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