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Surveillance does not equal safety: Police, data and consent on dating apps

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journal contribution
posted on 2024-07-11, 15:12 authored by Zahra Stardust, Rosalie Gillett, Kath AlburyKath Albury
As dating apps continue to receive pressure from civil society, media and governments to address a range of safety concerns, technology companies have developed and deployed a spate of new safety features. Taken together, these features rely upon increased surveillance and partnerships with both technology start-up companies and law enforcement agencies proposed as responses to sexual harassment and abuse. In this article, we draw on empirical accounts of app use – and popular media reporting – to problematise commonsense assumptions about dating apps, safety, technology, policing and surveillance. Where so-called safety features involve increased surveillance and techno-carceral solutionism, there is potential to make users less safe – particularly for app users who are marginalised or stigmatised on the basis of their race, sexuality, gender, health status, employment or disability. Instead of the impetus to ‘datafy’ consent by documenting evidence of sexual transactions, or to monitor users by sharing data with police, we argue that a more effective approach to safety must extend the notion of ‘consent culture’ to encompass a consent-based approach to collecting, storing, and sharing user data – including seeking consent from users about how and whether their data is sold, monetised or shared with third parties or law enforcement.

Funding

ARC | CE200100005

ARC | LP160101687

ARC Centre of Excellence for Automated Decision-Making and Society : Australian Research Council (ARC) | CE200100005

Safety, risk and wellbeing on digital dating apps : Australian Research Council (ARC) | LP160101687

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Available versions

PDF (Accepted manuscript)

ISSN

1741-6590

Journal title

Crime, Media, Culture

Volume

19

Issue

2

Article number

174165902211118

Pagination

274-295

Publisher

SAGE Publications

Copyright statement

Copyright © 2022 the author(s). This is the final peer-reviewed accepted manuscript version, hosted under the terms and conditions of the Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.

Language

eng

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