Authors

* External authors

Venue

Date

Share

A View From Somewhere: Human-Centric Face Representations

Jerone T. A. Andrews

Przemyslaw Joniak*

Alice Xiang

* External authors

NeurIPS 2022

2022

Abstract

We propose to implicitly learn a set of continuous face-varying dimensions, without ever asking an annotator to explicitly categorize a person. We uncover the dimensions by learning on a novel dataset of 638,180 human judgments of face similarity (FAX). We demonstrate the utility of our learned embedding space for predicting face similarity judgments, collecting continuous face attribute values, and attribute classification. Moreover, using a novel conditional framework, we show that an annotator's demographics influences the importance they place on different attributes when judging similarity, underscoring the need for diverse annotator groups to avoid biases.

Related Publications

Measure dataset diversity, don’t just claim it

ICML, 2024
Dora Zhao*, Jerone T. A. Andrews, Orestis Papakyriakopoulos*, Alice Xiang

Machine learning (ML) datasets, often perceived as neutral, inherently encapsulate abstract and disputed social constructs. Dataset curators frequently employ value-laden terms such as diversity, bias, and quality to characterize datasets. Despite their prevalence, these ter…

Not My Voice! A Taxonomy of Ethical and Safety Harms of Speech Generators

FaccT, 2024
Wiebke Hutiri*, Orestis Papakyriakopoulos*, Alice Xiang

The rapid and wide-scale adoption of AI to generate human speech poses a range of significant ethical and safety risks to society that need to be addressed. For example, a growing number of speech generation incidents are associated with swatting attacks in the United States…

Ethical Considerations for Responsible Data Curation

NeurIPS, 2023
Jerone Andrews, Dora Zhao*, William Thong, Apostolos Modas, Orestis Papakyriakopoulos*, Alice Xiang

Human-centric computer vision (HCCV) data curation practices often neglect privacy and bias concerns, leading to dataset retractions and unfair models. HCCV datasets constructed through nonconsensual web scraping lack crucial metadata for comprehensive fairness and robustnes…

JOIN US

Shape the Future of AI with Sony AI

We want to hear from those of you who have a strong desire
to shape the future of AI.