How Product Teams Should Tackle Responsible AI

Guest host Michael Li—the founder and president of The Data Incubator—sits down with Aishwarya Srinivasan, an Artificial Intelligence and Machine Learning Innovation Leader at IBM. Aishwarya works cross-functionally with the product team, data science team and sales to research AI use cases for clients at IBM Data & AI. In her role, she conducts discovery workshops and builds assets to showcase the business value of the technology. Aishwarya holds a postgraduate degree in data science from Columbia University.The two data science experts discuss the importance of building responsible AI systems that aren't harmful to society, citing examples in the media. Aishwarya shares the responsibilities of roles like AI ethicists, UX researchers, data scientists and cybersecurity officers in upholding responsible AI standards. She also highlights the key issues organizations will have to grapple with as AI continues to evolve, and she shares key takeaways for leveraging machine learning and AI to create business value. Find links to resources shared in this episode: Trusted-AI/AIF360 via Github "Adversarial attacks in machine learning: What they are and how to stop them" via VentureBeat "What is Adversarial Machine Learning?" via Towards Data Science

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Pragmatic Institute‘s data podcast, where we cover emerging and relevant topics in data science, data analytics, data engineering and pretty much all things data.