AI Critiques résumés Differently
This is a news story, published by Ars Technica, that relates primarily to Massive Text Embedding news.
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job descriptionsArs Technica
•AIs show distinct bias against Black and female résumés in new study
90% Informative
University of Washington researchers ran hundreds of publicly available résumés and job descriptions through three different Massive Text Embedding (MTE) models.
They used the models to generate embedded relevance scores for each résumé and job description pairing.
In all three models, white names were preferred in all three MTE models, compared to Black names being preferred in just 8.6 percent of tests.
VR Score
96
Informative language
99
Neutral language
51
Article tone
formal
Language
English
Language complexity
66
Offensive language
not offensive
Hate speech
not hateful
Attention-grabbing headline
not detected
Known propaganda techniques
not detected
Time-value
long-living
External references
4
Source diversity
3
Affiliate links
no affiliate links