Forecasting Impact
Forecasting Impact is a monthly podcast that aims to disseminate the science and practice of forecasting alongside prominent academics and practitioners in the field. Our vision is to grow the forecasting community, foster collaboration between academia and industry, and promote scientific forecasting and good practice. We’ll discuss a variety of topics in economics, supply chain, energy, AI, data analytics, healthcare, and more.
Podcast Team: Dr. Mahdi Abolghasemi, Dr. Sevvandi Kandanaarachchi, Michał Chojnowski, Dr Laila Akhlaghi, George Boretos, Mariana Menchero, Dr. Faranak Golestaneh, Arian Sultan Khan.
Future guests: if you have something interesting on forecasting to share with our audiences, please send an email to forecastingimpact@gmail.com
Forecasting Impact
Galit Shmueli, on causal inference, behavioural modifications, and role of ethics.
In this episode, we spoke to Prof Galit Shmueli, Tsing Hua Distinguished Professor at the Institute of Service Science, and Institute Director at the College of Technology Management, National Tsing Hua University.
Galit talked with us about the multi-disciplinary work she has done over the years, as well as the differences between statistical models that are purposed for predicting as opposed to explaining. We also discussed causal inference and how it can be used to estimate behaviour modification by the tech giants. We continued and talked about the ethics and the complexity of that landscape.
Galit's recommended books:
1. The age of surveillance capitalism, Shoshana Zuboff
2. Books on causality:
• The book of Why, Dana Mackenzie and Judea Pearl
• Causal Inference in Statistics: A Primer, Judea Pearl, Madelyn Glymour, and Nicholas P. Jewell
• Causality, Judea Pearl
3. Mostly Harmless Econometrics: An Empiricist's Companion, Joshua D. Angrist, Jörn-Steffen Pischke