The DataEDGE conference at UC Berkeley brings together senior industry and academic leaders for a conversation about the challenges and opportunities created by the rise of big data.
Keynote Speaker
Rumman Chowdhury
Director of Machine Learning Ethics, Transparency, and Accountability
Twitter
Rumman is director of the META (machine learning ethics, transparency, and accountability) team at Twitter, leading a team of applied researchers and engineers to identify and mitigate algorithmic harms on the platform. She is a pioneer in the field of applied algorithmic ethics, creating cutting-edge socio-technical solutions for ethical, explainable and transparent AI. She holds degrees in quantitative social science and has been a practicing data scientist and AI developer since 2013. She is interested in how data can be used to understand bias and ways to evaluate the impact of technology on humanity. She has contributed significant work on algorithmic ethics, fairness, and justice. Her latest research is on the surveillance infrastructure of smart cities, as well as the algorithmic colonization of the global south.
A New Vision for Data Science
Are you and your organization taking advantage of the opportunities created by today’s flood of new data? Do you know about the latest tools for storing, analyzing, and visualizing data? Have you considered the privacy implications of working with data? How do leaders balance intuition and data in making important decisions?
The UC Berkeley School of Information’s DataEDGE conference will bring you up to speed quickly on the current state of the data revolution. You will hear from leading experts in the field about the way organizations are using data to address business and societal issues, about the challenges of working with data at scale, and about the most pressing questions and debates facing data scientists today.
This conference is not just for technologists and math geeks; DataEDGE brings together social scientists, computer scientists, policy-makers, designers, and artists for an intimate conference to assess the current state of data science and the data revolution.