Modeling needs user modeling - Çelikok, Mustafa Mert; Murena, Pierre-Alexandre; Kaski, Samuel (Frontiers in Artificial Intelligence, 2023)
Modelling has actively tried to take the human out of the loop, originally for objectivity and recently also for automation. We argue that an unnecessary side effect has been that modelling workflows and machine learning pipelines have become restricted to only well-specified problems. Putting the humans back into the models would enable modelling a broader set of problems, through iterative modelling processes in which AI can offer collaborative assistance. However, this requires advances in how we scope our modelling problems, and in the user models. In this perspective article, we characterize the required user models and the challenges ahead for realizing this vision, which would enable new interactive modelling workflows, and human-centric or human-compatible machine learning pipelines.