Jacobs / CIFAR Workshop

Machine Learning &

Theory Development

July 10th  ·  July 11th  ·  July 12th 

(Three 3h-Sessions, Online) 

Experts in machine learning with theoretical backgrounds from various fields present cutting edge methodologies and discuss how machine learning methods can be applied to further theory development.

Cognitive Neuroscience  ·  Cognitive Psychology  ·  Language ·  Sociology  ·  Computational Modelling ·  Developmental Science ·  AI

Machine learning has attracted huge attention in social sciences and neuroscience, delivering predictions that exceed any insight that a human researcher would be able to obtain with common theory-driven approaches. However, applications are often criticized as being mainly exploratory and inductive, and their utility for theory development is not yet clear. In this online workshop, we will discuss how we can leverage machine learning methods and AI to further theories. By hearing from speakers with diverse perspectives (cognitive neuroscience, cognitive psychology, language, sociology, computational modelling, developmental science, AI), and through panel discussions, the workshop aims to interactively highlight the strengths and limitations of machine learning methods in theory development and refinement. The workshop is targeted for applied researchers in any discipline interested in using machine learning methods to advance their field.