A frequent point of criticism against Directed Acyclic Graphs is that writing them down for a real-world problem can be a difficult task. There are numerous possible variables to consider and it’s not clear how we can determine all the causal relationships between them. We recently had a Twitter discussion where exactly this argument popped up again.
Beyond Curve Fitting
Last week I attended the AAAI spring symposium on “Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-based AI”, held at Stanford University. Since Judea Pearl and Dana Mackenzie published “The Book of Why”, the topic of causal inference gains increasing momentum in the machine learning and artificial intelligence community. If we want to build truly intelligent machines, which are able to interact with us in a meaningful way, we have to teach them the concept of causality. Otherwise, our future robots will never be able to understand that forcing the rooster to crow at 3am in the morning won’t make the sun appear. Continue reading Beyond Curve Fitting
Causal Inference for Policymaking
I just submitted an extended abstract of an upcoming paper to a conference that will discuss new analytical tools and techniques for policymaking. The abstract contains a brief discussion about the importance of causal inference for taking informed policy decisions. And I would like to share these thoughts here. Continue reading Causal Inference for Policymaking
The Origins of Graphical Causal Models
Here is an interesting bit of intellectual history. In his 2000 book “Causality”, Judea Pearl describes how he got to the initial idea that sparked the development of causal inference based on directed acyclic graphs. Continue reading The Origins of Graphical Causal Models
How We Started to Study Technological Change
In 1957, Zvi Griliches published a seminal article in innovation economics (“Hybrid Corn: An Exploration in the Economics of Technological Change“), which is based on his PhD thesis. It is safe to say that this piece stands at the beginning of innovation developing into an independent subfield of economics. Besides that, Griliches was also a pioneer in modern style econometric work. In this paper you can clearly see why. It’s a marvellous combination of policy relevant work–he collected a novel data set on US corn production of the time–and advancement in economic theory. Continue reading How We Started to Study Technological Change
How to get knowledge out of the ivory tower?
Technology transfer is a big topic for scholars and policy makers.We would like to know how we can harvest the knowledge and ideas that are produced at universities and research institutes and to make them available to society. The invention of new technologies is only a first step. They need to be commercialized as innovative products and services to further foster a society’s wealth. Especially Europe could do better here. Continue reading How to get knowledge out of the ivory tower?
Exodus in German science
Fabian Waldinger pursued an interesting research agenda so far. Let me explain what’s so fascinating about his work. But in order to do so, I first need to describe why (good) empirical research is actually such a hard task. Continue reading Exodus in German science