DeepAI AI Chat
Log In Sign Up

Levels of Analysis for Machine Learning

by   Jessica Hamrick, et al.

Machine learning is currently involved in some of the most vigorous debates it has ever seen. Such debates often seem to go around in circles, reaching no conclusion or resolution. This is perhaps unsurprising given that researchers in machine learning come to these discussions with very different frames of reference, making it challenging for them to align perspectives and find common ground. As a remedy for this dilemma, we advocate for the adoption of a common conceptual framework which can be used to understand, analyze, and discuss research. We present one such framework which is popular in cognitive science and neuroscience and which we believe has great utility in machine learning as well: Marr's levels of analysis. Through a series of case studies, we demonstrate how the levels facilitate an understanding and dissection of several methods from machine learning. By adopting the levels of analysis in one's own work, we argue that researchers can be better equipped to engage in the debates necessary to drive forward progress in our field.


page 1

page 2

page 3

page 4


Insiders and Outsiders in Research on Machine Learning and Society

A subset of machine learning research intersects with societal issues, i...

Sex Trouble: Common pitfalls in incorporating sex/gender in medical machine learning and how to avoid them

False assumptions about sex and gender are deeply embedded in the medica...

A Causal Framework to Unify Common Domain Generalization Approaches

Domain generalization (DG) is about learning models that generalize well...

Pairing Conceptual Modeling with Machine Learning

Both conceptual modeling and machine learning have long been recognized ...

The Scientific Method in the Science of Machine Learning

In the quest to align deep learning with the sciences to address calls f...

Concordance as evidence in the Watson for Oncology decision‑support system

Machine learning platforms have emerged as a new promissory technology t...