Responsible AI for Customer Product Organizations


With the accelerated use of Machine Learning and AI technologies, having a comprehensive view of the use of these technologies, the data involved, and how the technology interacts with the users have become diagnostically complicated. The talk would shed light on the pitfalls faced by industries building user-facing AI applications. We would be going over the aspects of responsible AI, how they are critical to different industries, and addressing this from data science and organizational perspective. The talk will lay out the structured pillar approach on how customer product (B2C) organizations can ensure building responsible AI solutions.


Aishwarya is working as a Data Scientist in the Google Cloud AI Services team to build machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and AI Platform. Aishwarya was working as an AI & ML Innovation Leader at IBM Data & AI, where she was working cross-functionally with the product team, data science team and sales to research AI use-cases for clients by conducting discovery workshops and building assets to showcase the business value of the technology. She is an advocate for open-source technologies; previously a developer advocate for PyTorch Lightning and a contributor to Scikit Learn. She holds a post-graduate in Data Science from Columbia University. She has worked with clients all across the globe and has traveled internationally to London, Dubai, Istanbul, and India to lead and work with them. She is very focused on expanding her horizons in the machine learning research community including her recent Patent Award won in 2018 for developing a Reinforcement Learning model for Machine Trading.

She is an ambassador for the Women in Data Science community, originating from Stanford University. She has a huge follower base on LinkedIn and actively organizes events and conferences to inspire budding data scientists. She has been spotlighted as a LinkedIn Top Voice 2020 for Data Science and AI, which features Top 10 Machine Learning influencers across the world.

She is an ardent reader and has contributed to the scholastic community. To spread her knowledge in the space of data science, and to inspire budding Data Scientists, she actively writes blogs related to machine learning on LinkedIn:

Open Data Science




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