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From Meaning to Metrics: How Algorithmic Morality Reorders Educational Values in Humanitarian Education Governance.

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Title: From Meaning to Metrics: How Algorithmic Morality Reorders Educational Values in Humanitarian Education Governance.
Authors: Ahn, Youngbeen1
Source: Current Issues in Comparative Education. 2026 Special Issue, Vol. 28, p43-67. 25p.
Subject Terms: *Values education, *Artificial intelligence, *Moral education, *Decision making, Humanitarianism, Ethics, Moral reasoning
Geographic Terms: Jordan
Abstract: As humanitarian education becomes increasingly reliant on digital infrastructures, moral values governing access, protection, and recognition are now mediated through data and algorithmic decision-making. This paper develops the concept of algorithmic morality to analyze how digital governance systems reorder educational values in humanitarian settings. Employing critical document analysis of policy texts, technical specifications, and documented cases, the paper maps how humanitarian ideals move across the three analytical sites of articulation, encoding, and encounter. Three patterns emerge: relational dimensions of educational value compress into individual metrics, procedural flexibility hardens into algorithmic thresholds, and ethical imperatives transform into severity rankings. Cases from Jordan and Kenya illustrate the functioning and the limits of this logic. The paper makes two contributions. First, it conceptualizes algorithmic morality as a field-level logic that actively constitutes moral worth rather than operationalizing pre-existing values. Second, it introduces a moral-technical analytic for examining digital systems as moral infrastructures. As global disorder intensifies and digital humanitarianism expands, the central challenge is not a shortage of data but a crisis of meaning: the marginalization of relational and contextual dimensions of humanitarian education that resist computational reduction. [ABSTRACT FROM AUTHOR]
Copyright of Current Issues in Comparative Education is the property of Current Issues in Comparative Education 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.)
Database: Education Research Complete
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  Data: As humanitarian education becomes increasingly reliant on digital infrastructures, moral values governing access, protection, and recognition are now mediated through data and algorithmic decision-making. This paper develops the concept of algorithmic morality to analyze how digital governance systems reorder educational values in humanitarian settings. Employing critical document analysis of policy texts, technical specifications, and documented cases, the paper maps how humanitarian ideals move across the three analytical sites of articulation, encoding, and encounter. Three patterns emerge: relational dimensions of educational value compress into individual metrics, procedural flexibility hardens into algorithmic thresholds, and ethical imperatives transform into severity rankings. Cases from Jordan and Kenya illustrate the functioning and the limits of this logic. The paper makes two contributions. First, it conceptualizes algorithmic morality as a field-level logic that actively constitutes moral worth rather than operationalizing pre-existing values. Second, it introduces a moral-technical analytic for examining digital systems as moral infrastructures. As global disorder intensifies and digital humanitarianism expands, the central challenge is not a shortage of data but a crisis of meaning: the marginalization of relational and contextual dimensions of humanitarian education that resist computational reduction. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Current Issues in Comparative Education is the property of Current Issues in Comparative Education 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.</i> (Copyright applies to all Abstracts.)
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              Text: 2026 Special Issue
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