Viewing machine learning and data science applications as sociotechnical systems

In this episode of the Data Exchange I speak with Chris Wiggins, Associate Professor at Columbia University, Chief Data Scientist at the New York Times, and co-founder of hackNY. He began his career in theoretical physics but he always had a strong interest in applying quantitative techniques to other disciplines. Early in his career he became interested in applications of machine learning to problems in biology and the health sciences.Our conversation focused on a range of topics including:How he shifted his focus from physics to machine learning and data science.Applications of reinforcement learning.“Data scientist” as a job title, and data science training programs.Ethics in machine learning and data science, including training the next generation of data scientists.A 2015 essay written by Michael Jordan and Tom Mitchell.Detailed show notes can be found on The Data Exchange web site.Subscribe to The Gradient Flow Newsletter.