Stop the Nonconsensual Use of Nude Images in Research

TL;DR

This paper highlights the ethical issues and potential harms caused by the nonconsensual collection and distribution of nude images in machine learning research, urging the community to cease such practices.

Contribution

It provides a systematic review of current practices in nudity detection research and advocates for ethical standards to prevent misuse of nude images.

Findings

Widespread nonconsensual use of nude images in research

Distribution of uncensored nude images with faces

Problematic practices like sharing abusive content

Abstract

In order to train, test, and evaluate nudity detection models, machine learning researchers typically rely on nude images scraped from the Internet. Our research finds that this content is collected and, in some cases, subsequently distributed by researchers without consent, leading to potential misuse and exacerbating harm against the subjects depicted. This position paper argues that the distribution of nonconsensually collected nude images by researchers perpetuates image-based sexual abuse and that the machine learning community should stop the nonconsensual use of nude images in research. To characterize the scope and nature of this problem, we conducted a systematic review of papers published in computing venues that collect and use nude images. Our results paint a grim reality: norms around the usage of nude images are sparse, leading to a litany of problematic practices like distributing and publishing nude images with uncensored faces, and intentionally collecting and sharing abusive content. We conclude with a call-to-action for publishing venues and a vision for research in nudity detection that balances user agency with concrete research objectives.