Saved in:
Bibliographic Details
Main Author: Marshalkin, Nikita
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2605.17347
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866917505460600832
author Marshalkin, Nikita
author_facet Marshalkin, Nikita
contents When a neural network estimates someone's age from a photograph, does it process biometric data? The answer depends on whether identity-discriminative representations arise within the network during inference, a question that may seem trivial to ML researchers but triggers consent requirements under GDPR, statutory damages under BIPA, or high-risk AI classification under the EU AI Act. Yet no regulatory guidance addresses it. This position paper provides empirical evidence: 14 models evaluated across 3 face verification benchmarks show age estimators fall orders of magnitude short of identification thresholds. Age estimation models cannot identify individuals. We call on researchers to provide transparency about what systems store and can do, and on regulators to distinguish transient processing from template storage.
format Preprint
id arxiv_https___arxiv_org_abs_2605_17347
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Position: Age Estimation Models Do Not Process Biometric Data
Marshalkin, Nikita
Computers and Society
Computer Vision and Pattern Recognition
Machine Learning
68T07, 68T10, 68T45
I.5.4; I.2.10; K.4.1; K.5.2
When a neural network estimates someone's age from a photograph, does it process biometric data? The answer depends on whether identity-discriminative representations arise within the network during inference, a question that may seem trivial to ML researchers but triggers consent requirements under GDPR, statutory damages under BIPA, or high-risk AI classification under the EU AI Act. Yet no regulatory guidance addresses it. This position paper provides empirical evidence: 14 models evaluated across 3 face verification benchmarks show age estimators fall orders of magnitude short of identification thresholds. Age estimation models cannot identify individuals. We call on researchers to provide transparency about what systems store and can do, and on regulators to distinguish transient processing from template storage.
title Position: Age Estimation Models Do Not Process Biometric Data
topic Computers and Society
Computer Vision and Pattern Recognition
Machine Learning
68T07, 68T10, 68T45
I.5.4; I.2.10; K.4.1; K.5.2
url https://arxiv.org/abs/2605.17347