Research

How Meta is working to assess fairness in relation to race in the U.S. across its products and systems

November 16, 2021

Abstract

At Meta, we’re taking action to advance racial justice in our company and on our platform.

The purpose of this paper is to describe in detail privacy-preserving approaches that Meta is currently scoping and piloting in the U.S. to advance our ability to assess whether product and system differences exist across race and ethnicity.

Download the Technical Paper

AUTHORS

Written by

Rachad Alao

Miranda Bogen

Jingang Miao

Ilya Mironov

Jonathan Tannen

Related Publications

June 14, 2020

Iterative Answer Prediction with Pointer-Augmented Multimodal Transformers for TextVQA | Facebook AI Research

Ronghang Hu, Amanpreet Singh, Trevor Darrell, Marcus Rohrbach

June 14, 2020

April 25, 2020

Permutation Equivariant Models for Compositional Generalization in Language | Facebook AI Research

Jonathan Gordon, David Lopez-Paz, Marco Baroni, Diane Bouchacourt

April 25, 2020

September 15, 2019

Speech & Audio

Who Needs Words? Lexicon-Free Speech Recognition | Facebook AI Research

Tatiana Likhomanenko, Gabriel Synnaeve, Ronan Collobert

September 15, 2019

September 10, 2019

NLP

Bridging the Gap Between Relevance Matching and Semantic Matching for Short Text Similarity Modeling | Facebook AI Research

Jinfeng Rao, Linqing Liu, Yi Tay, Wei Yang, Peng Shi, Jimmy Lin

September 10, 2019

Help Us Pioneer The Future of AI

We share our open source frameworks, tools, libraries, and models for everything from research exploration to large-scale production deployment.