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Fairness and bias mitigation

A new age in AI — MOSTLY AI's response to MIT Technology Review's recent article on fair synthetic data

Cathy O'Neil says, 'Synthetic data is likely to get better over time, but not by accident.' We couldn't agree more, and our world-class team of scientists and engineers is constantly working on just that.
by 
Ágnes Fekete
June 29, 2021
Fairness and bias mitigation

The State of Fair Synthetic Data in 2021

Any machine learning model that is trained on fair synthetic data will be representative of the real world but fair by design.
by 
Michael Platzer
May 28, 2021
Fairness and bias mitigation

Diving Deep Into Fair Synthetic Data Generation (Fairness Series Part 5)

In the previous part of this series, we have discussed two risks entailed in the rise of digitalization and artificial intelligence: the violation of the privacy and fairness of individuals.
by 
Paul Tiwald
May 8, 2020
Fairness and bias mitigation

Tackling AI Bias At Its Source – With Fair Synthetic Data (Fairness Series Part 4)

In the age of digitalization and the rise of artificial intelligence, more and more tasks in public and private organizations are managed or supported by computers and machine-learning algorithms.
by 
Paul Tiwald
May 7, 2020
Fairness and bias mitigation

We Want Fair AI Algorithms – But How To Define Fairness? (Fairness Series Part 3)

Fairness is a vastly complex concept and as people tend to have different values their interpretations of fairness differ as well.
by 
Alexandra Ebert
May 6, 2020
Fairness and bias mitigation

10 Reasons For Bias In AI And What To Do About It (Fairness Series Part 2)

You may remember that back in 2015 Google was called out for its photo app that mistakenly labeled pictures of people with darker skin color as “gorillas”. As you can imagine, it was a PR disaster back then.
by 
Alexandra Ebert
May 5, 2020
Fairness and bias mitigation

Why Bias in AI is a Problem & Why Business Leaders Should Care (Fairness Series Part 1)

While AI has remarkable potential to analyze and identify patterns even in very large datasets and to help humans to make more informed decisions, the examples mentioned above were by far not the only...
by 
Alexandra Ebert
May 4, 2020
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