From Statecraft to Codebreaking: The Big Data Origin Story with Chris Wiggins, Chief Data Scientist at The New York Times

If you’re a history buff in the data world, you know that there’s a complex interplay between data, statecraft, and machine learning. The history of data visualization is entwined with societal governance and technological advancements, starting from the usage of statistics for statecraft in the 18th century to the transformative innovations during World War II that birthed computation and data science as we know it. And because of the subjective design choices that underpin data gathering and analysis, there’s an inherently political nature of deciding what data to collect and how to utilize it, which is critical in understanding both historical and contemporary data practices. As we move into the modern applications of data science and the advent of AI technologies, deep reinforcement learning and the integration with generative AI models, these technologies are reshaping the field by enabling computers to process and interact with unstructured data in unprecedented ways. Satyen and Chris discuss his book How Data Happened, the origins of data science and the role of Alan Turing in the creation of digital computing, and the challenges generative AI brings around model interoperability. *Satyen’s narration was created using AI

Om Podcasten

Some people can see things that nobody else can. They seem to be able to peer around corners and into the future. These seemingly super powers come from being able to synthesize the data all around us. They approach problems with a curious and rational mind. They think differently and encourage others to embrace data culture. We call them “data radicals” because they transform themselves and the world around them In this podcast, we talk to these Data Radicals to understand what makes their approach so unique and how it can be replicated.