OOF-AII-446066
Social Media Recommendation Algorithms Allegedly Repeatedly Exposed 13-Year-Old Blake Gallier to Suicide-Related Videos Before Her Death
Before her death on October 30, 2025, 13-year-old Blake Gallier reportedly viewed and reposted social-media videos normalizing suicide. After examining her phone, her family alleged that recommendation algorithms had repeatedly surfaced similar material. The platform or platforms involved have not been publicly identified, and an inquest into her death remains pending.
- Event date
- 2025-10-30
- Country
- Location not specified
- Severity
- High
- Evidence state
- Single-source
Assessment status
Generated from available public incident evidence using OOF® governance methodology. It is not an official investigation, legal determination, regulatory finding, certification, or OOF® Approved Assessment.
View source record from AI Incident Database (Responsible AI Collaborative)
Assessment confidence dimensions
- Source corroboration
- Single-source
- Extraction completeness
- Moderate
- Methodological assignment confidence
- Moderate
Measures source-group corroboration only; it does not establish factual truth.
Measures populated source fields after deterministic normalization; it does not measure correctness.
Measures automated assignment support; substantive correctness requires authorized human review.
Known facts from the incident record
- The incident record identifies the event date as 2025-10-30.
Reported claims
- Before her death on October 30, 2025, 13-year-old Blake Gallier reportedly viewed and reposted social-media videos normalizing suicide. After examining her phone, her family alleged that recommendation algorithms had repeatedly surfaced similar material. The platform or platforms involved have not been publicly identified, and an inquest into her death remains pending.
Material unknowns
- Independent corroboration is not established in the available incident record.
Primary governance problem
The incident appears to expose a governance problem involving related, identified, been, into. Available reporting supports preliminary methodological interpretation, not a finding of fault or non-compliance.
Architecture intelligence
LIGA™ — Liability Governance Architecture
Primary architecture
The reported related, identified, been concern falls within the governed questions represented by LIGA™ — Liability Governance Architecture.
Governance focus: How should related, identified, been be governed in the conditions described by the available incident evidence?
Deeper methodology is withheld because the available evidence does not justify a Parent Standard or Core Module.
PGA™ — Prediction Governance Architecture
Contributing architecture
The reported related, into, identified concern falls within the governed questions represented by PGA™ — Prediction Governance Architecture.
Governance focus: How should related, into, identified be governed in the conditions described by the available incident evidence?
Deeper methodology is withheld because the available evidence does not justify a Parent Standard or Core Module.
Preliminary governance questions
- How should related, identified, been be governed in the conditions described by the available incident evidence?
- How should related, into, identified be governed in the conditions described by the available incident evidence?
- What operational authority and controls applied to Social Media Platforms at the relevant time?
- What evidence would establish how Social Media Recommendation Algorithms, Social Media Platforms produced or enabled the reported outcome?
- What additional independent evidence is required to resolve the material evidence gaps?
Evidence gaps and limitations
- Only one independent source group is represented; corroboration is not established.
- Country could not be resolved from the available evidence.
- AI technology is not specified in the source record.
- industry is not specified in the source record.
- AI system type is not specified in the source record.