2020 WiDS was held Friday, March 27, from 9:45 a.m. to 5:00 p.m. Eastern. You can view the event in the videos below.
WiDS Charlottesville is an independent event organized by the UVA School of Data Science to coincide with the annual Global Women in Data Science (WiDS) Conference held at Stanford University and an estimated 150+ locations worldwide. All genders are invited to attend WiDS regional events, which feature outstanding women doing outstanding work. Read more about the event at the button below.
Overview of conference and introductory remarks by Arlyn Burgess, Associate Director for Operations and Strategic Initiatives- UVA School of Data Science.
"Scaling Innovation via Human-AI Collaboration" with Franziska Bell, Senior Director of Accelerated Materials Design and Discover and Machine Assisted Cognition at Toyota Research Institute
Listen to research highlights from three women working in data science at University of Virginia.
Businesses today are increasingly certain that AI will be a driving force in the evolution of their industries over the next few years. Yet for every successful AI project, there are many that fail to reach widespread adoption in the business and achieve their expected outcomes. Even the most expert data science teams will typically only deploy a handful of models into production every year. This is partly because the mechanics of AI deployment can be complex, and there are still gaps in skills and tooling that can make it difficult for data science, IT operations, and business teams to work in lockstep. But beyond the operational challenges, there are also much more profound issues of trust and transparency that businesses need to address before they can truly turn AI into a business advantage.
IBM approaches data science with these issues in mind, creating tooling to make AI and analytics transparent, fair, and accessible to users of all backgrounds. In this session, we will discuss IBM’s approach to data science and AI ethics and the ways we enable our customers to build powerful machine learning and deep learning models. We will complete an interactive and hands-on lab to explore bias in data science and ways to mitigate it, and then wrap up by discussing exciting emerging technologies. We look forward to exploring together the ways in which ethical data science practices help businesses ensure fair outcomes, remain compliant with regulations, and increase confidence in the value of AI.
Women leaders discuss opportunities and challenges in the field of data science. At this year's conference featured a conversation with women leaders on the opportunities and challenges they face in the field of data science.
"The Corona Response: The Need for Intersectional Technical Leadership" with Mutale Nkonde, Founding Executive Director, AI for the People