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Fairness

A collection of 5 posts

The Man, The Machine, And The Black Box: ML Observability
Bias

The Man, The Machine, And The Black Box: ML Observability

Aparna Dhinakaran, Co-Founder & CPO of Arize AI, explores the challenges organizations face in checking for model fairness, such as the lack of access to protected class information to check for bias and diffuse organizational responsibility of ensuring model fairness....

  • Nikita Johnson
    Nikita Johnson
14 September 2021
Can We Trust AI?
Trusted AI

Can We Trust AI?

This article explores building trust in AI, the risks in AI, and how to best build trust in AI through frameworks and guidelines....

  • Mia Clarke
    Mia Clarke
4 March 2021
Why AI Ethics Matter by Kay Firth-Butterfield, Head of AI and ML at WEF
Ethics

Why AI Ethics Matter by Kay Firth-Butterfield, Head of AI and ML at WEF

Kay Firth-Butterfield, Head of AI & Machine Learning at WEF talks about Why AI Ethics Matter. Watch the video presentation with accompanying transcript....

  • Mia Clarke
    Mia Clarke
19 October 2020
Fairness in Machine Learning - The Case of Juvenile Criminal Justice in Catalonia
Machine Learning for Criminal Justice

Fairness in Machine Learning - The Case of Juvenile Criminal Justice in Catalonia

Is it possible to use Machine Learning to predict recidivism in young offenders? We asked HUMAINT to share their research on this incredible study....

  • Pip Curtis
    Pip Curtis
2 July 2020
Fairness in Machine Learning: Recommender Diversity
Recommendation Systems

Fairness in Machine Learning: Recommender Diversity

You’ve doubtless come across recommenders before. You’ll certainly have been on the receiving end of a few. The question is, what do they look like on the inside?...

  • Guest Blog
    Guest Blog
27 September 2019
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