Generative AI
Building High Quality Trustworthy Generative AI Systems: A Responsible AI Approach
About This Talk
As generative AI continues to transform industries, it is crucial to consider the ethical and social implications of this technology. Join this session to explore how responsible AI principles can be applied to generative AI, and hear from top experts about the challenges and opportunities of building ethical generative AI systems.
Speakers
Deepam Mishra is a Sr Advisor to AI/ML Startups at AWS. He is leading Strategy for Generative AI Startups and Co-Innovation. Before joining AWS, Deepam co-founded and led AI Country Plan at Microsoft Corporation and started the AI Startup Program at Wipro Technologies. Deepam has been a serial entrepreneur and investor, having founded 4 AI/ML startups in areas including computer vision, robotics and security. He was the CEO/founder of Venture Factory - a global incubator and seed fund that created multiple successful impact startups including in mobility, sustainability and healthcare. Deepam has a BSEE from Indian Institute of Technology, an MSEE from Texas A&M and an MBA from The Wharton School. He has 5 US patents and numerous publications. He is based in the Silicon Valley.
Will is CEO and Co-founder of TruEra, the leading AI Quality software company. Will became passionate about addressing the challenges of building, explaining, testing and monitoring high quality machine learning and algorithmic systems for enterprises when he experienced them firsthand while leading both product development and customer-facing teams at his prior startup, BloomReach. Prior to TruEra, Will held a variety of leadership roles at three successful startups, BloomReach, Clearwell Systems (acquired by Symantec) and Neoteris/Netscreen (acquired by Juniper Networks). Will holds an MBA from Harvard Business School and a BA from Dartmouth College.
Krishnaram Kenthapadi is the Chief AI Officer and Chief Scientist of Fiddler AI, an enterprise startup building a responsible AI and ML monitoring platform. Previously, he was a Principal Scientist at Amazon AWS AI, where he led the fairness, explainability, privacy, and model understanding initiatives in the Amazon AI platform. Prior to joining Amazon, he led similar efforts at the LinkedIn AI team, and served as LinkedIn's representative in Microsoft's AI and Ethics in Engineering and Research (AETHER) Advisory Board. Previously, he was a Researcher at Microsoft Research Silicon Valley Lab. Krishnaram received his Ph.D. in Computer Science from Stanford University in 2006. He serves regularly on the senior program committees of FAccT, KDD, WWW, and related conferences, and co-chaired the 2014 ACM Symposium on Computing for Development. His work has been recognized through awards at NAACL, WWW, SODA, CIKM, ICML AutoML workshop, and Microsoft's AI/ML conference (MLADS). He has published 50+ papers, with 4500+ citations and filed 150+ patents (70 granted). He has presented tutorials on privacy, fairness, explainable AI, responsible AI, and model monitoring at forums such as KDD ’18 ’19 '22, WSDM ’19, WWW ’19 ’20 '21, FAccT ’20 '21 ‘22, AAAI ’20 '21, and ICML '21, and instructed a course on AI at Stanford.
Robert Moseley IV is a seasoned professional in the field of Artificial Intelligence (AI) with over a decade of experience in implementing and consulting on AI solutions. He is currently the Head of Implementation and Consulting at Copy.ai, a company that leverages AI to help businesses create high-quality content.
Prior to his current role, Robert has held various leadership positions in AI-focused companies such as Moveworks and Cloudinary. He has a strong background in engineering and architecture, which has enabled him to design and implement AI solutions that are tailored to meet the specific needs of his clients.
His expertise in AI and his ability to communicate complex concepts in a simple and understandable manner make him a valuable asset to any organization looking to leverage AI to drive business growth.