The Sociotechnical Stack: Opportunities for Social Computing Research in Non-consensual Intimate Media

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Authors: Li Qiwei, Allison McDonald, Oliver L. Haimson, Sarita Schoenebeck, Eric Gilbert

Published: 2024-05-06 15:58:03+00:00

AI Summary

This paper introduces the sociotechnical stack, a framework to analyze how technology facilitates non-consensual intimate media (NCIM) harms. It maps social impacts of NCIM to layers of the technical stack, revealing opportunities for computing research to deter NCIM and support victims.

Abstract

Non-consensual intimate media (NCIM) involves sharing intimate content without the depicted person's consent, including revenge porn and sexually explicit deepfakes. While NCIM has received attention in legal, psychological, and communication fields over the past decade, it is not sufficiently addressed in computing scholarship. This paper addresses this gap by linking NCIM harms to the specific technological components that facilitate them. We introduce the sociotechnical stack, a conceptual framework designed to map the technical stack to its corresponding social impacts. The sociotechnical stack allows us to analyze sociotechnical problems like NCIM, and points toward opportunities for computing research. We propose a research roadmap for computing and social computing communities to deter NCIM perpetration and support victim-survivors through building and rebuilding technologies.

Key findings

The sociotechnical stack reveals how various technological layers contribute to NCIM harms, from default public settings on social media to algorithms inadvertently promoting abusive content. The research highlights the need for interventions at multiple levels of the technical stack to mitigate NCIM's impact.

Approach

The paper proposes a sociotechnical stack framework to analyze non-consensual intimate media (NCIM). This framework maps the social impacts of NCIM to different layers of the technical stack (hardware, OS, storage, network, algorithms, applications, and user interface), enabling a systematic analysis of how technology facilitates NCIM.

Datasets

The research uses qualitative data from previous studies, including surveys and interviews with over 400 victim-survivors of NCIM.

Model(s)

UNKNOWN

Author countries

USA

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