Excavating "Excavating AI": The Elephant in the Gallery

TL;DR

This paper critically examines art exhibitions and essays on AI, highlighting contradictions in their stance on consent and clarifying issues about machine learning training sets and data use.

Contribution

It provides a critical analysis of recent AI art discourse, emphasizing the importance of informed consent and clarifying misconceptions about training set descriptions.

Findings

Reveals contradictions in consent policies in AI art exhibitions

Highlights flaws in critique of machine learning training sets

Underscores the importance of informed consent in AI data use

Abstract

Two art exhibitions, "Training Humans" and "Making Faces," and the accompanying essay "Excavating AI: The politics of images in machine learning training sets" by Kate Crawford and Trevor Paglen, are making substantial impact on discourse taking place in the social and mass media networks, and some scholarly circles. Critical scrutiny reveals, however, a self-contradictory stance regarding informed consent for the use of facial images, as well as serious flaws in their critique of ML training sets. Our analysis underlines the non-negotiability of informed consent when using human data in artistic and other contexts, and clarifies issues relating to the description of ML training sets.