70% of customers expect organizations to provide AI interactions and products that are transparent and fair (Capgemini). Now more than ever, organizations need to govern deployed AI systems to minimize harm for end-users and organizational risk. In this webinar, the VP of Trusted AI at DataRobot Ted Kwartler, DataRobot’s Global AI Ethicist Haniyeh Mahmoudian, and DataCamp’s Adel Nehme will outline:
- The importance of developing responsible AI and what it means for organizations today
- Practical solutions data teams and organizations can adopt to mitigate risk in AI systems
- The crucial role data literacy plays when scaling responsible AI and aligning stakeholders on AI Governance frameworks
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Adel is a Data Science educator, speaker, and Evangelist at DataCamp, where he has released various courses and live training on data analysis, machine learning, and data engineering. Adel is passionate about spreading data skills and data literacy throughout organizations and the intersection of technology and society. He has an MSc in Data Science and Business Analytics. In his free time, you can find him hanging out with his cat Louis.
Haniyeh is a Global AI Ethicist at DataRobot's Trusted AI team. Her research focuses on bias, privacy, robustness and stability, and ethics in AI and Machine Learning. She has a demonstrated history of implementing ML and AI in a variety of industries and initiated the incorporation of bias and fairness feature into DataRobot product. She is a thought leader in the area of AI bias and ethical AI. Haniyeh holds a PhD in Astronomy and Astrophysics from the Rheinische Friedrich-Wilhelms-Universität Bonn.
Ted Kwartler is Vice President, Trusted AI at DataRobot. In that role, he sets product strategy for explainable and ethical uses of data technology. Through his current position and his previous employment in a major insurance company and the IT industry, he brings unique insights and experience with data ethics and transparency. Ted also teaches at the Harvard University Extension School and serves as an advisor to the Bureau of Economic Affairs' Advisory Committee on Data for Evidence Building.