Incident 476: YouTube Recommendations Allegedly Promoted Radicalizing Material Contributing to Terrorist Acts

Description: Family of Nohemi Gonzalez alleged YouTube recommendation systems led people to propaganda videos for the Islamic State which subsequently radicalized them to carry out the killing of 130 people in the 2015 Paris terrorist attack, including Ms. Gonzalez.

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Alleged: YouTube developed and deployed an AI system, which harmed victims in Paris attacks , Nohemi Gonzalez family and Nohemi Gonzalez.

Incident Stats

Incident ID
476
Report Count
3
Incident Date
2015-11-13
Editors
Sean McGregor
Applied Taxonomies
CSETv1, MIT

CSETv1 Taxonomy Classifications

Taxonomy Details

Incident Number

476

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

Risk Subdomain

4.1. Disinformation, surveillance, and influence at scale

Risk Domain

  1. Malicious Actors & Misuse

Entity

AI

Timing

Post-deployment

Intent

Unintentional

Supreme Court To Decide Whether YouTube Can Be Sued For Abetting Terrorism
forbes.com · 2022

It’s the first Monday in October so the Supreme Court is back in session. It issued a list of various cases that it will decide in the coming term. It was already public knowledge that the Court will be deciding a number of important and co…

Gonzalez v. Google: Implications for the Internet’s Future
bipartisanpolicy.org · 2022

On October 3, 2022, the Supreme Court announced that it would hear two cases that could fundamentally change the future of the modern internet. Gonzalez v. Google and Twitter, Inc. v. Taamneh involve both the Anti-Terrorism Act and Section …

Gonzalez v. Google LLC
scotusblog.com · 2023

Issue: Whether Section 230(c)(1) of the Communications Decency Act immunizes interactive computer services when they make targeted recommendations of information provided by another information content provider, or only limits the liability…

Variants

A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.

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