Machine learning models are increasingly used to inform high-stakes decisions. In this session, we will explore what it means to build a trustworthy AI system covering aspects of fairness, explainability, and transparency.
We will be exploring open-source packages that can help in the aspect of fairness and explainability. Also, learn about Factsheets that can help increasing model transparency.
Join us and let us take a step towards making trustworthy AI systems.
Saishruthi (IBM AI)
Saishruthi Swaminathan is an advocate for Trustworthy AI and an Advisory Data Scientist at IBM. She has a Masters in Electrical Engineering specializing in Data Science and a Bachelor degree in Electronics and Instrumentation. Her passion is to dive deep into the ocean of data, extract insights, and use AI for social good. Previously, she worked as a Software Developer. She is on a mission to spread the knowledge and experience she acquired in her learning process. She also leads an education for rural children initiative and speaks at meetups focussing on Trustworthy AI and Women Empowerment.