Explainable and Non-explainable Discrimination in Classification

By Faisal Kamiran, Indrė Žliobaitė. 2013

23 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Safety Research, Safety, Robustness & Interpretability, AI Ethics, Fairness & Society

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Fred Morstatter
2. Ninareh Mehrabi
3. Aram Galstyan
4. Nripsuta Ani Saxena
5. Kristina Lerman
6. Fei Ye
7. Adrian G. Bors

In Safety Research

1. Aram Galstyan
2. Fred Morstatter
3. Ninareh Mehrabi
4. Kristina Lerman
5. Nripsuta Ani Saxena

In Safety, Robustness & Interpretability

1. Fred Morstatter
2. Ninareh Mehrabi
3. Aram Galstyan
4. Kristina Lerman
5. Nripsuta Ani Saxena

In AI Ethics, Fairness & Society

1. Aram Galstyan
2. Fred Morstatter
3. Ninareh Mehrabi
4. Kristina Lerman
5. Nripsuta Ani Saxena

Citations in the corpus

• A Survey on Bias and Fairness in Machine Learning (2019, background): “Authors in [64] also present local techniques for removing only the illegal or unexplainable discrimination, allowing only for explainable differences in decisions.”