3 papers
cs.LG2024
The Costs of Pretending That There Are Data-Generating Probability Distributions in the Social World
Benedikt Höltgen, Robert C. Williamson
Machine Learning research, including work promoting fair or equitable algorithms, often relies on the concept of a data-generating probability distribution. The standard presumptio…
stat.ME2024
Formalising causal inference as prediction on a target population
Benedikt Höltgen, Robert C. Williamson
The standard approach to causal modelling especially in social and health sciences is the potential outcomes framework due to Neyman and Rubin. In this framework, observations are…
cs.CL2024
Limits to Predicting Online Speech Using Large Language Models
Mina Remeli, Moritz Hardt, Robert C. Williamson
Our paper studies the predictability of online speech -- that is, how well language models learn to model the distribution of user generated content on X (previously Twitter). We d…