.jpg)
Causal Bandits Podcast
Causal Bandits Podcast with Alex Molak is here to help you learn about causality, causal AI and causal machine learning through the genius of others.
The podcast focuses on causality from a number of different perspectives, finding common grounds between academia and industry, philosophy, theory and practice, and between different schools of thought, and traditions.
Your host, Alex Molak is an a machine learning engineer, best-selling author, and an educator who decided to travel the world to record conversations with the most interesting minds in causality to share them with you.
Enjoy and stay causal!
Keywords: Causal AI, Causal Machine Learning, Causality, Causal Inference, Causal Discovery, Machine Learning, AI, Artificial Intelligence
Causal Bandits Podcast
Do Heterogeneous Treatment Effects Exist? | Stephen Senn X Richard Hahn S2E9 | CausalBanditsPodcast
Do Heterogeneous Treatment Effects Exist?
For the last 50 years, we've designed cars to be safe...
For the 50th-percentile male.
Well, that's actually not 100% correct.
According to Stanford's report, we introduced "female" crash test dummies in the 1960s, but...
They were just scaled-down versions of male dummies and...
Represented the 5th percentile of females in terms of body size and mass (aka the smallest 5% of women in the general population).
These dummies also did not take into account female-typical injury tolerance, biomechanics, spinal alignment, and more.
But...
Does it matter for actual safety?
In the episode, we cover:
- Do heterogeneous treatment effects (different effects in different contexts) exist?
- If so, can we actually detect them?
- Is it more ethical to look for heterogeneous treatment effects or rather look at global averages?
Video version available on the Youtube:
https://youtu.be/V801RQTBpp4
Recorded on Nov 12, 2025 in Malaga, Spain.
------------------------------------------------------------------------------------------------------
About Richard
Professor Richard Hahn, PhD, is a professor of statistics at Arizona State University (ASU). He develops novel statistical methods for analyzing data arising from the social sciences, including psychology, economics, education, and business. His current focus revolves around causal inference using regression tree models, as well as foundational issues in Bayesian statistics.
Connect with Richard:
- Richard on LinkedIn: https://www.linkedin.com/in/richard-hahn-a1096050/
About Stephen
Stephen Senn, PhD, is a statistician and consultant who specializes in drug development clinical trials. He is a former Group Head at Ciba-Geigy and has taught at the University of Glasgow and University College London (UCL). He is the author of "Statistical Issues in Drug Development," "Crossover Trials in Clinical Research," and "Dicing with Death."
Connect with Stephen:
- Stephen on LinkedIn:
Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4