Thou Shall Judge But With Fairness: Methods to Ensure an Unbiased Model
Nandana Sreeraj

Biased models can impact each of us. While it may feel abstract, AI fairness can be achieved through many methods and metrics. More so, mitigation reports can initiate you to responsible AI. Check out my talk & demo at PyData Berlin.

What could possibly go wrong? - An incomplete guide on how to prevent, detect & mitigate biases in data products
Lea Petters

Data Ethics: What could possibly go wrong? - An incomplete guide on how to prevent, detect & mitigate biases in data products

Workshop on Privilege and Ethics in Data
Tereza Iofciu, Paula Gonzalez Avalos

Data-driven Products are built by humans. Humans are intrinsically biased. This bias goes into the products, which amplifies the original bias. In this tutorial, you will learn how to identify your biases and reflect on the consequences of unchecked biases in Data Products.

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