Visualizations are both a tool for exploration and a mechanism of communication about complex information. The power and potential of visualization work stems from the ability to help people see in new ways. But what people see - and how it helps them make sense of the world - is shaped by more than the tool itself. In this talk, danah will grapple with how contestations over information and communication affect the practice of visualization. Just as data can never be neutral, neither can visualization. This talk will reflect on how visualization experts can navigate biases in data, the politicization of information, and the challenges in communicating uncertainty.
Dr. boyd is an internationally recognized authority on the ways people use networked social media as a context for social interaction. She has been called the “high priestess” of online social network sites by the Financial Times. Dr. boyd’s research focuses on the intersection of technology, society, and policy. Currently, she is Founder & President of Data & Society, a research institute focused on examining the social and cultural issues that emerge around data-driven technologies. She is author of _It’s Complicated and co-author of, Participatory Culture in a Networked Era, and Hanging Out, Messing Around and Geeking Out_. danah is a Partner Researcher at Microsoft Research, and a Visiting Professor at New York University. She is on the board of the Crisis Text Line, a Trustee of Smithsonian’s National Museum of the American Indian, a member of the U.S. Department of Commerce Data Advisory Council and is on the advisory boards of the Electronic Privacy Information Center and both University of California at Berkeley and University of Michigan’s School of Information. Previously, danah was Fellow at Harvard University’s Berkman Center for Internet and Society.
Part science, part art, data visualization relies on rules and heuristics developed over hundreds of years. A shared vocabulary of effective visual encodings has put the field on solid ground, and prevents us from reinventing the wheel every time we visualize a new data set. Yet sometimes this wisdom fails. This talk focuses on what we can learn from visualizations that defy our own expectations in a positive way, working better than we’d imagine. As we encounter new kinds of data and sensemaking challenges, even the most finely-honed intuition and scientific theories can limit us. To move the field forward, we need to keep our eyes open for surprising observations and happy accidents.
Fernanda Viégas and Martin Wattenberg are Principal Scientists at Google, where they co-lead the PAIR (People+AI Research) initiative. Viégas and Wattenberg are also Gordon McKay Professors of Computer Science at Harvard, where Fernanda is an incoming Sally Starling Seaver Professor at the Radcliffe Institute for Advanced Study. Their work in machine learning focuses on transparency and interpretability, as part of a broad agenda to improve human/AI interaction. They are well known for their contributions to social and collaborative visualization, and the systems they’ve created are used daily by millions of people. Viégas and Wattenberg are also known for visualization-based artwork, which has been exhibited in venues such as the Museum of Modern Art in New York, London Institute of Contemporary Arts and the Whitney Museum of American Art. Their artwork has influenced contemporary design practice: for instance, the techniques in their wind map are now used by major media companies around the world to display the weather.