Chris Wiggins on how Data and Algorithms have shaped society and what we can do about it.
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Chris Wiggins is a Professor at Columbia University and the Chief Data Scientist at the NYTimes. He is also co-author of a fascinating new historical exploration of how data has been used as a tool in shaping society, from the census to eugenics to Google search. How Data Happened traces the trajectory of data and explores new mathematical and computational techniques that serve to shape people, ideas, society, and economies. They offer practical insights into how we can better understand and control data to promote privacy, democracy, and individual rights. I have perused numerous historical books and biographies pertaining to the subject matter, however, this book stands out for its distinctive approach in utilizing history to explain the present landscape of Data, Machine Learning, and AI for readers.
Interview highlights – key sections from the video version:
- Comparing the book “How Data Happened” to the course they teach at Columbia
- Combining quantitative (Chris) and historical (Matt) perspectives
- Statistical topics and pioneering statisticians
- Data mining, and Leo Breiman
- Data science and early data scientists
- Big data
- Machine learning and AI (and pattern recognition)
- Dominance of neural networks and deep learning
- Ethics and privacy
- A video version of this conversation is available on our YouTube channel.
- Chris Wiggins: Viewing machine learning and data science applications as sociotechnical systems
- Peter Norvig and Alfred Spector: Data Science and AI in Context
- Percy Liang: Evaluating Language Models
- Vector Database Primer
- FREE Report: 2023 Trends in Data, Machine Learning, and AI
- Specialized Hardware for AI: Rethinking Assumptions and Implications for the Future
- Mark Chen of OpenAI: How DALL·E works
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[Image: Book cover and Image from Kathleen Smith (Privacy Journal, 1984)]