Ghosts in the machine

Toft Djanegara, Nina

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https://hdl.handle.net/2142/117913 Copy

Description

Title

Ghosts in the machine

Author(s)

Toft Djanegara, Nina

Issue Date

2023-02

Keyword(s)

• Facial Recognition
• Artificial Intelligence
• Machine Learning
• Training Datasets
• Computer Vision
• Immigration
• Borders

Abstract

The National Institute of Standards and Technology's (NIST’s) Facial Recognition Vendor Test is considered the gold standard for assessing the performance of facial recognition models. Since the test series began in 1994, it has been regarded as an objective benchmark for corporations and academic research groups to compare their models against one another. To evaluate the accuracy of facial recognition models, NIST draws upon a database of millions of photos of US visa applicants and border crossers. Without their knowledge or consent, immigrants’ photos have become raw material for the refinement of facial recognition software. This essay discusses the afterlife of these images, photos of immigrants and non-citizens that have been repurposed for a function that goes far beyond their original intent.

Series/Report Name or Number

Media-N, vol. 19, issue 1

Type of Resource

text

Language

en

DOI

https://doi.org/10.21900/j.median.v19i1.953

Copyright and License Information

• Copyright 2023 Nina Toft Djanegara
• This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-sa/4.0/).

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