Statistical Modeling, Causal Inference, and Social Science

By Bob Carpenter

The European Commission just released their Proposal for a Regulation on a European approach for Artificial Intelligence. They finally get around to a definition of “AI” on page 60 of the report (link above):

‘artificial intelligence system’ (AI system) means software that is developed with one or more of the techniques and approaches listed in Annex I and can, for a given set of human-defined objectives, generate outputs such as content, predictions, recommendations, or decisions influencing the environments they interact with

We don’t even have to wonder if they mean us. They do. Here’s the full text of Annex 1 from page 1 of “Laying down harmonized rules on artificial intelligence (Artificial Intelligence Act) and amending certain Union legislative acts” (same link, different doc).


referred to in Article 3, point 1

(a) Machine learning approaches, including supervised, unsupervised and reinforcement learning, using a wide variety of methods including deep learning;

(b) Logic- and knowledge-based approaches, including knowledge representation, inductive (logic) programming, knowledge bases, inference and deductive engines, (symbolic) reasoning and expert systems;

(c) Statistical approaches, Bayesian estimation, search and optimization methods.

This feels hopelessly vague with phrasing like “wide variety of methods” and the inclusion of “statistical approaches”. Also, I don’t see what’s added by “Bayesian estimation” given that it’s an instance of a statistical approach. At least it’s nice to be noticed.

Annex I looks like my CV rearranged. In the ’80s and ’90s, I worked on logic programming, linguistics, and knowledge representation (b). I’m surprised that’s still a going concern. I spent the ’00s working on ML-based natural language processing, speech recognition, and search (a). And ever since the ’10s, I’ve been working on Bayesian stats (c).