Retention Limits on Later Discrimination: How What a Process Keeps Bounds What Can Later Be Told Apart

Later analysis can be careful and still be unable to make a distinction that an earlier process removed. This paper sets out Retention Limits on Later Discrimination, a structural constraint on what subsequent operations can establish from a retained record. When a retention rule maps relevant source differences to the same output, further processing of that output alone cannot recover the merged distinction. The paper distinguishes genuinely lost distinctions from differences that have merely been degraded and remain partly recoverable. It examines how independent information, including an original record, another identifier, or relevant contextual knowledge, can supply what the retained value no longer contains. A retention rule is assessed by whether it preserves the distinctions required by later uses and leaves another route available when an omitted distinction becomes important. The discussion relates this constraint to research on data provenance and examines the automatic conversion of gene symbols by spreadsheet software. The case illustrates loss within converted cell values while recognizing that other fields or context may still allow the original gene to be identified. Part of the Relational Conditions and Dynamics series within On Human Modeling, the paper identifies questions for examining what a process keeps, what later work requires, who sets the retention rule, and who bears the consequences of information loss.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-09
DOI
https://doi.org/10.5281/zenodo.24079091
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Retention Limits on Later Discrimination: How What a Process Keeps Bounds What Can Later Be Told Apart

Alexandra Cary
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

Retention Limits on Later Discrimination: How What a Process Keeps Bounds What Can Later Be Told Apart

Alexandra Cary
article en

Abstract

Later analysis can be careful and still be unable to make a distinction that an earlier process removed. This paper sets out Retention Limits on Later Discrimination, a structural constraint on what subsequent operations can establish from a retained record. When a retention rule maps relevant source differences to the same output, further processing of that output alone cannot recover the merged distinction. The paper distinguishes genuinely lost distinctions from differences that have merely been degraded and remain partly recoverable. It examines how independent information, including an original record, another identifier, or relevant contextual knowledge, can supply what the retained value no longer contains. A retention rule is assessed by whether it preserves the distinctions required by later uses and leaves another route available when an omitted distinction becomes important. The discussion relates this constraint to research on data provenance and examines the automatic conversion of gene symbols by spreadsheet software. The case illustrates loss within converted cell values while recognizing that other fields or context may still allow the original gene to be identified. Part of the Relational Conditions and Dynamics series within On Human Modeling, the paper identifies questions for examining what a process keeps, what later work requires, who sets the retention rule, and who bears the consequences of information loss.

Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
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