Data Analysis and Data Literacy for a Better World in the Age of Big Data and Artificial Intelligence
Recent technology including social media and artificial intelligence have fundamentally changed data analysis and data literacy. As one example, the distinction between categorical and qualitative data on one hand and quantitative data on the other hand is now completely outdated. Artificial Intelligence is now, for example, being used to translate formerly qualitative data like audio and video recordings of traffic, classrooms or focus groups into a form that can be processed quantitatively by computers. More importantly, quantitative data is no longer being represented by low-dimensional vectors but rather by very high-dimensional vectors that capture more complexity and nuance. (ChatGPT represents words by 12,288 dimensional vectors.) We are also learning more about how we build understanding, how we use data and how we make decisions from our experience with large language models and generative artificial intelligence coupled with earlier work by people like Daniel Kahneman and Dan Kahan.
Data analysis can be used to increase our understanding or it can be misused, often deliberately misused, to cloud our understanding. This workshop is a call to action to develop our students so they can use data well as data analysts and so that they can be critical consumers of data. It is also a call to action to work with staff, students and faculty throughout our institutions to understand the humanity behind our data and to develop students who are able to make decisions that will better our lives and our world. This workshop looks at both modern methods of data analysis and at specific actions we can take now.
Workshop Facilitator: Frank Wattenberg
Frank Wattenberg is known to many in the SENCER community as a longtime participant and Co-PI of the NSF funded "Engaging Mathematics" initiative. Frank retired at the end of June 2020 after 19 years in the Department of Mathematical Sciences at the United States Military Academy and over 50 years as a mathematician and mathematics educator primarily interested in mathematical modeling of and for high stakes and often controversial personal and public policy decision-making. Like many of us, he has been forced by recent events to question the assumption that good science and good science education by themselves empower us to improve our world. Since retiring his focus has been on understanding the popular distrust of scientists that is part of a broader distrust of experts under the guise of anti-elitism. He has come to believe that we, along with experts in other fields, have contributed to this distrust and must act to regain trust. This is not just a matter of failures of communication and failures of education. He also has come to believe that the current breakdown of our cultural norms is part of long trends accelerated by modern technology including social media and now generative artificial intelligence.