# The Method of Critical AI Studies, A Propaedeutic

arXiv: https://arxiv.org/abs/2411.18833 · HTML: https://mlsanity.com/paper/2411.18833/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Nov 2024.

## Built on by (most cited first, 2 of 2)

- [The Evolving Nature of Latent Spaces: From GANs to Diffusion](https://mlsanity.com/paper/2510.17383/) (2025)
- [Surface Reading LLMs: Synthetic Text and its Styles](https://mlsanity.com/paper/2510.22162/) (2025)

## Abstract (arXiv)

We outline some common methodological issues in the field of critical AI studies, including a tendency to overestimate the explanatory power of individual samples (the benchmark casuistry), a dependency on theoretical frameworks derived from earlier conceptualizations of computation (the black box casuistry), and a preoccupation with a cause-and-effect model of algorithmic harm (the stack casuistry). In the face of these issues, we call for, and point towards, a future set of methodologies that might take into account existing strengths in the humanistic close analysis of cultural objects.