PROMINENT TECH RESEARCHERS PEN OPEN LETTER TO AMAZON CITING RACIAL BIAS IN FACIAL REKOGNITION SOFTWARE

"Overall, we find [Amazon's] response to peer-reviewed research
 findings disappointing...We call on Amazon to stop selling Rekognition."

 Concerned Researchers.
Amazon Rekognition surveillance software has a low accuracy rate of 68% for women of color – relative to a 100% accuracy rate for white males

Prominent artificial intelligence researchers in tech, concerned about violations of the civil rights of American citizens and potential loss of liberties, have responded to Amazon’s defensive hostility in On Recent Research Auditing Commercial Facial Analysis Technology. Visit HERE to read the tech communities’ open letter to the tech giant.

CONCERNED RESEARCHERS

Ali Alkhatib, Stanford University

Noura Al Moubayed, Durham University

Miguel Alonso Jr, Florida International University

Anima Anandkumar, Caltech (formerly Principal Scientist at AWS)

Akilesh Badrinaaraayanan, MILA/University of Montreal

Esube Bekele, National Research Council fellow

Yoshua Bengio, MILA/University of Montreal

Alex Berg, UNC Chapel Hill

Miles Brundage, OpenAI; Oxford; Axon AI Ethics Board

Dan Calacci, Massachusetts Institute of Technology

Pablo Samuel Castro, Google

Abir Das, IIT Kharagpur

Hal Daumé III, Microsoft Research and University of Maryland

Maria De-Arteaga, Carnegie Mellon University

Mostafa Dehghani, University of Amsterdam

Emily Denton, Google

Lucio Dery, Facebook AI Research

Priya Donti, Carnegie Mellon University

Hamid Eghbal-zadeh, Johannes Kepler University Linz

Paul Feigelfeld, IFK Vienna, Strelka Institute

Jessica Finocchiaro, University of Colorado Boulder

Andrea Frome, Google

Field Garthwaite, IRIS.TV

Timnit Gebru, Google

Sebastian Gehrmann, Harvard University

Georgia Gkioxari, Facebook AI Research

Alvin Grissom II, Ursinus College

Sergio Guadarrama, Google

Alex Hanna, Google

Bernease Herman, University of Washington

William Isaac, Deep Mind

Alexia Jolicoeur-Martineau, MILA/University of Montreal

Yannis Kalantidis, Facebook AI

Khimya Khetarpal, MILA/McGill University

Michael Kim, Stanford University

Morgan Klaus Scheuerman, University of Colorado Boulder

Hugo Larochelle, Google/MILA

Hugo Larochelle, Google/MILA

Erik Learned-Miller, UMass Amherst

Xing Han Lu, McGill University

Kristian Lum, Human Rights Data Analysis Group

Michael Madaio, Carnegie Mellon University

Tegan Maharaj, Mila/École Polytechnique

João Martins, Carnegie Mellon University

El Mahdi El Mhamdi, Ecole Polytechnique Fédérale de Lausanne

Vincent Michalski, MILA/University of Montreal

Margaret Mitchell, Google

Melanie Mitchell, Portland State University and Santa Fe Institute

Ioannis Mitliagkas, MILA/University of Montreal

Bhaskar Mitra, Microsoft and University College London

Jamie Morgenstern, Georgia Institute of Technology

Bikalpa Neupane, Pennsylvania State University, UP

Ifeoma Nwogu, Rochester Institute of Technology

Vicente Ordonez-Roman, University of Virginia

Pedro O. Pinheiro

Vinodkumar Prabhakaran, Google

Parisa Rashidi, University of Florida

Anna Rohrbach, UC Berkeley

Daniel Roy, University of Toronto

Negar Rostamzadeh

Kate Saenko, Boston University

Niloufar Salehi, UC Berkeley

Anirban Santara, IIT Kharagpur (Google PhD Fellow)

Brigit Schroeder, Intel AI Lab

Laura Sevilla-Lara, University of Edinburgh

Shagun Sodhani, MILA/University of Montreal

Biplav Srivastava

Luke Stark, Microsoft Research Montreal

Rachel Thomas, fast.ai; University of San Francisco

Briana Vecchione, Cornell University

Toby Walsh, UNSW Sydney

Serena Yeung, Harvard University

Yassine Yousfi, Binghamton University

Richard Zemel, Vector & University of Toronto