Yann Lecun

Zhenzhong Lan

Mingda Chen

Sebastian Goodman

Bernhard E. Boser

J. Denker

Don-608 nie Henderson

Robin Howard

Wayne Hubbard

Yinhan Liu

Myle Ott

Naman Goyal

Jingfei Du

Mandar Joshi

Danqi Chen

Omer Levy

Mike Lewis

Warning : this paper contains content that may 001 be offensive or upsetting. 002 Detecting hateful, toxic, and otherwise racist 003 or sexi… (see more)st language in user-generated online con-004 tents has become an increasingly important task 005 in recent years. Indeed, the anonymity, the 006 transience, the size of messages, and the dif-007 ficulty of management, facilitate the diffusion 008 of racist or hateful messages across the Inter-009 net. The critical influence of this cyber-racism 010 is no longer limited to social media, but also 011 has a significant effect on our society : corpo-012 rate business operation, users’ health, crimes, 013 etc. Traditional racist speech reporting chan-014 nels have proven inadequate due to the enor-015 mous explosion of information, so there is an 016 urgent need for a method to automatically and 017 promptly detect texts with racial discrimination. 018 We propose in this work, a machine learning-019 based approach to enable automatic detection 020 of racist text content over the internet. State-of-021 the-art machine learning models that are able 022 to grasp language structures are adapted in this 023 study. Our main contribution include 1) a large 024 scale racial discrimination data set collected 025 from three distinct sources and annotated ac-026 cording to a guideline developed by specialists, 027 2) a set of machine learning models with vari-028 ous architectures for racial discrimination de-029 tection, and 3) a web-browser-based software 030 that assist users to debias their texts when us-031 ing the internet. All these resources are made 032 publicly available.

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

Anthony Zador

Blake Richards

Bence Ölveczky

Sean Escola

Kwabena Boahen

Matthew Botvinick

Dmitri Chklovskii

Anne Churchland

Claudia Clopath

James DiCarlo

Surya Ganguli

Jeff Hawkins

Konrad Paul Kording

Alexei Koulakov

Timothy P. Lillicrap

Adam Marblestone

Bruno Olshausen

Alexandre Pouget … (see 7 more)

Cristina Savin

Terrence Sejnowski

Eero Simoncelli

Sara Solla

David Sussillo

Andreas S. Tolias

Doris Tsao

2022-01-01

arXiv.org (preprint)

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

Anthony Zador

Blake Richards

Bence Ölveczky

Sean Escola

Kwabena Boahen

Matthew Botvinick

Dmitri Chklovskii

Anne Churchland

Claudia Clopath

James DiCarlo

Surya Ganguli

Jeff Hawkins

Konrad Paul Kording

Alexei Koulakov

Timothy P. Lillicrap

Adam Marblestone

Bruno Olshausen

Alexandre Pouget … (see 7 more)

Cristina Savin

Terrence Sejnowski

Eero Simoncelli

Sara Solla

David Sussillo

Andreas S. Tolias

Doris Tsao

2022-01-01

arXiv.org (preprint)

Deep learning for AI

Geoffrey Hinton

How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding la… (see more)nguage?

2021-06-21

Communications of the ACM (published)

Deep learning for AI

Geoffrey Hinton

2021-06-21

Communications of the ACM (published)

Deep learning for AI

Geoffrey Hinton

2021-06-21

Communications of the ACM (published)

Deep learning for AI

Geoffrey Hinton

How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding la… (see more)nguage?

2021-06-21

Communications of the ACM (published)

Deep learning for AI

Geoffrey Hinton

2021-06-21

Communications of the ACM (published)

Deep learning for AI

Geoffrey Hinton

How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding la… (see more)nguage?

2021-06-21

Communications of the ACM (published)

Deep learning for AI

Geoffrey Hinton

2021-06-21

Communications of the ACM (published)

Deep learning for AI

Geoffrey Hinton

How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding la… (see more)nguage?

2021-06-21

Communications of the ACM (published)

Deep learning for AI

Geoffrey Hinton

How can neural networks learn the rich internal representations required for difficult tasks such as recognizing objects or understanding la… (see more)nguage?

2021-06-21

Communications of the ACM (published)