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Incident 132: TikTok’s Content Moderation Allegedly Failed to Adequately Take down Videos Promoting Eating Disorders

Description: Videos promoting eating disorders evaded TikTok's automated violation detection system without difficulty via common misspellings of search terms, bypassing its ban of violating hashtags such as "proana" and "anorexia".

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Alleged: TikTok developed and deployed an AI system, which harmed TikTok users and TikTok users under 18 years old.

Incident Stats

Incident ID
132
Report Count
1
Incident Date
2020-12-27
Editors
Sean McGregor, Khoa Lam
Applied Taxonomies
CSETv1, GMF, MIT

CSETv1 Taxonomy Classifications

Taxonomy Details

Incident Number

The number of the incident in the AI Incident Database.
 

132

Special Interest Intangible Harm

An assessment of whether a special interest intangible harm occurred. This assessment does not consider the context of the intangible harm, if an AI was involved, or if there is characterizable class or subgroup of harmed entities. It is also not assessing if an intangible harm occurred. It is only asking if a special interest intangible harm occurred.
 

yes

Date of Incident Year

The year in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the year, estimate. Otherwise, leave blank. Enter in the format of YYYY
 

2020

Date of Incident Month

The month in which the incident occurred. If there are multiple harms or occurrences of the incident, list the earliest. If a precise date is unavailable, but the available sources provide a basis for estimating the month, estimate. Otherwise, leave blank. Enter in the format of MM
 

12

Estimated Date

“Yes” if the data was estimated. “No” otherwise.
 

No

Multiple AI Interaction

“Yes” if two or more independently operating AI systems were involved. “No” otherwise.
 

no

MIT Taxonomy Classifications

Machine-Classified
Taxonomy Details

Risk Subdomain

A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
 

1.2. Exposure to toxic content

Risk Domain

The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
 
  1. Discrimination and Toxicity

Entity

Which, if any, entity is presented as the main cause of the risk
 

AI

Timing

The stage in the AI lifecycle at which the risk is presented as occurring
 

Post-deployment

Intent

Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
 

Unintentional

Incident Reports

Reports Timeline

+1
TikTok Anorexia Videos Misspell Hashtags to Beat the 'Pro-Ana' Ban
TikTok Anorexia Videos Misspell Hashtags to Beat the 'Pro-Ana' Ban

TikTok Anorexia Videos Misspell Hashtags to Beat the 'Pro-Ana' Ban

insider.com

TikTok Anorexia Videos Misspell Hashtags to Beat the 'Pro-Ana' Ban
insider.com · 2020

TikTok said it banned six accounts reported to it for posting content promoting eating habits that are likely to lead to health problems in its latest effort to crackdown on harmful content.

The app is rife with dangerous material including…

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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