OOF-AII-786732
A Collection of Tesla Autopilot-Involved Crashes
Multiple unrelated car accidents result in varying levels of harm have been occurred while a Tesla's autopilot was in use.
- Event date
- 2016-06-30
- Country
- United States of America
- Severity
- Low
- 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
- High
- 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 2016-06-30.
- The incident record identifies the location as United States of America.
Reported claims
- Multiple unrelated car accidents result in varying levels of harm have been occurred while a Tesla's autopilot was in use.
Material unknowns
- Independent corroboration is not established in the available incident record.
Primary governance problem
The incident appears to expose a governance problem involving object, been, harm, multiple. Available reporting supports preliminary methodological interpretation, not a finding of fault or non-compliance.
Architecture intelligence
LIGA™ — Liability Governance Architecture
Primary architecture
The reported object, been, harm concern falls within the governed questions represented by LIGA™ — Liability Governance Architecture.
Governance focus: On what governed basis can Liability potentially exist?
Canonical methodology (ParentStandard):
PGA™ — Prediction Governance Architecture
Contributing architecture
The reported object, multiple concern falls within the governed questions represented by PGA™ — Prediction Governance Architecture.
Governance focus: How should object, multiple 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.
VFM® — Value Flow Mechanisms Architecture
Contributing architecture
The reported recognition, object, occurred concern falls within the governed questions represented by VFM® — Value Flow Mechanisms Architecture.
Governance focus: How should recognition, object, occurred 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
- On what governed basis can Liability potentially exist?
- How should object, multiple be governed in the conditions described by the available incident evidence?
- How should recognition, object, occurred be governed in the conditions described by the available incident evidence?
- What operational authority and controls applied to Tesla at the relevant time?
- What evidence would establish how yes produced or enabled the reported outcome?
Evidence gaps and limitations
- Only one independent source group is represented; corroboration is not established.
- AI technology is not specified in the source record.