Teaching your Models to play fair
It is very important to ensure fairness while building an AI system which can scale to a large number of users. Thus, I plan to first talk about how fairness is important while building AI apps. I would then go on to talk about how FairLearn helps us in doing so specifically with the easy to use dashboard interface. I plan to show how FairLearn could be used to assess the model fairness and how it does so. I would then talk about mitigation strategies with FairLearn so as to remove the biases with state of the art models and compare multiple models to perform this successfully. As time persists I would also show live demos about using FairLearn and Azure ML to assess and mitigate fairness in an AI system.
Other sessions from: Global AI Student Conference
Real Time Object Detection With TensorFlow
In this session, I will discuss about my project "Sign language detection...Nigama Vajjula
How to protect the oceans with AI and Open Source?
Surfrider Foundation Europe NGO has become a reference in the fight for the...Christopher Maneu
Talk and Demo on Sound Identification and Classification with Tensorflow and Librosa
I aspire to conduct an interactive and implementation based workshop on the...Raghav Rawat