JOURNAL ARTICLE
From In(-)formation to Infrastructural Turns: The Digital Futures of Human Rights Law and Practice.
Published In: European Journal of International Law, 2024, v. 35, n. 4. P. 1013 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Fisher, Angelina 3 of 3
Abstract
This article critically examines Joshua Bowsher’s book *The Informational Logic of Human Rights: Network Imaginaries in the Cybernetic Age*, which analyzes how the human rights movement’s reliance on informational practices—shaped by cybernetic ideas and neoliberal capitalism—has depoliticized rights by privileging standardized, ostensibly objective data over situated, critical knowledge. Bowsher traces this informational logic through case studies including Amnesty International’s networked data systems, the use of social and economic rights indicators, and algorithmic methods for documenting violations, arguing that these approaches filter out structural and political dimensions of human rights issues. The article further explores calls for an infrastructural turn in human rights practice, emphasizing the need to engage with digital data infrastructures to produce relational, situated knowledge that connects systemic oppression with lived experiences. It highlights emerging efforts by activists and scholars to repurpose data and digital tools for resistance and transformative politics, while noting challenges posed by concentrated corporate control and legal limitations within the current human rights ecosystem.
Additional Information
- Source:European Journal of International Law. 2024/11, Vol. 35, Issue 4, p1013
- Document Type:Article
- Subject Area:Engineering
- Publication Date:2024
- ISSN:0938-5428
- DOI:10.1093/ejil/chae073
- Accession Number:184408274
- Copyright Statement:Copyright of European Journal of International Law is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.