AI Failure Index
AI Recommender failures
Ranking and recommendation engines that steer what people see, buy, or watch. Failures amplify at feed scale.
- Incidents
- 12
- Highest severity
- High
- Sources cited
- 30
- Newest indexed
- Jun 10, 2026
School districts sue Meta, Snap, TikTok, and Google over engagement algorithms
Meta, Snap, TikTok, and Google allegedly used AI recommendation and notification systems to maximize student engagement during school hours. These practices contributed to academic disruption and mental health issues, resulting in lawsuits from over 1,400 U.S. school districts.
- Confidence
- High (multi-source, primary)
X algorithm amplified right-wing and extreme content in the UK
Investigations and academic research documented that X’s recommendation/feed algorithm systematically promoted right‑wing and, in many cases, extreme content to UK users. Sky News’ controlled experiment (reported via AIAAIC and GIJN) found a majority share of political posts shown to test accounts came from right‑wing or extreme accounts, and a 2026 peer‑reviewed Nature study found X’s algorithm promotes conservative content relative to a chronological feed. Multiple independent sources report these findings publicly.
- Confidence
- High (multi-source, primary)
Meta job ad algorithm allegedly biased against women and older workers
In December 2022, the organization Real Women in Trucking filed an EEOC complaint against Meta. The complaint alleged that Facebook's ad delivery algorithm discriminatorily steered higher-paying job advertisements away from women and older workers.
- Confidence
- Medium (multi-source)
KFC Germany apologises after app alert linked to Kristallnacht promotion
In November 2022 KFC Germany sent an automated app push notification that referenced Kristallnacht while promoting a cheese chicken offer. The company apologised and said the message resulted from an automated push-notification system linked to calendars of national observances and that app communications were suspended while it reviewed internal processes.
- Confidence
- Medium (multi-source)
TikTok algorithm exposed young users to pro-eating disorder content
TikTok's algorithmic recommendation system allegedly promoted pro-eating disorder content to minors. This occurred despite official policies banning such material, highlighting a failure in content filtering and safety guardrails.
- Confidence
- High (multi-source, primary)
Instagram AI moderation fails to block global paedophile network
Instagram's automated moderation and recommendation systems failed to identify and block the growth of a global network of child predators. The AI-driven systems allegedly promoted accounts sharing child sexual abuse material and failed to remove them despite user reports.
- Confidence
- Medium (multi-source)
TikTok 'Suggested Accounts' experiment alleged to amplify or suppress certain creators
In February 2020 an AI researcher reported that TikTok’s "Suggested Accounts" feature recommended other creators who looked similar to the account a user had just followed, raising concerns about feedback loops and visibility bias for creators. TikTok disputed the claim and said recommendations are based on collaborative filtering. Independent news outlets reported the researcher’s experiment and the platform response.
- Confidence
- High (multi-source, primary)
Facebook job ad delivery biased toward male users
Facebook's ad delivery system disproportionately showed certain job advertisements to men over women, even when advertisers did not target by gender. Research indicated that the algorithm skewed delivery based on stereotypes, potentially violating anti-discrimination laws.
- Confidence
- High (multi-source, primary)
Meta settles lawsuit over discriminatory housing and credit ad targeting algorithms
Meta settled a US Department of Justice lawsuit regarding ad-delivery algorithms that discriminated against users in housing and credit ads. The company agreed to cease using the Special Ad Audience tool and paid a civil penalty.
- Confidence
- High (multi-source, primary)
Facebook ad delivery system produces discriminatory outcomes for housing and job ads
Research revealed that Facebook's ad delivery optimization system produced discriminatory outcomes for housing and job ads. The system's internal relevance and financial optimizations skewed ad delivery based on demographic traits despite neutral targeting.
- Confidence
- High (multi-source, primary)
Booking.com fined for algorithmic demotion of hotels over price parity
The Spanish competition authority fined Booking.com for using its ranking algorithm to penalize hotels that offered lower prices on other platforms. This practice was found to be an abuse of its dominant market position.
- Confidence
- High (multi-source, primary)
Google ad delivery algorithm showed gender bias in high paying job advertisements
A 2015 study by Carnegie Mellon University found that Google's ad delivery system showed significantly fewer high-paying job advertisements to women than to men. Researchers used simulated profiles to demonstrate that gender was the primary factor in this disparity.
- Confidence
- High (multi-source, primary)