OOF-AII-222064

Collection of Robotic Surgery Malfunctions

Study on database reports of robotic surgery malfunctions (8,061), including those ending in injury (1,391) and death (144), between 2000 and 2013.

Event date
2015-07-13
Country
United States of America
Severity
Critical
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

Measures source-group corroboration only; it does not establish factual truth.

Extraction completeness
High

Measures populated source fields after deterministic normalization; it does not measure correctness.

Methodological assignment confidence
Evidence Insufficient

Measures automated assignment support; substantive correctness requires authorized human review.

Known facts from the incident record

  • The incident record identifies the event date as 2015-07-13.
  • The incident record identifies the location as United States of America.

Reported claims

  • Study on database reports of robotic surgery malfunctions (8,061), including those ending in injury (1,391) and death (144), between 2000 and 2013.

Material unknowns

  • Independent corroboration is not established in the available incident record.
  • The specific AI system is not established by the available record.

Primary governance problem

Available evidence does not establish a sufficiently specific governed problem for architecture assignment.

Preliminary governance questions

  • What operational authority and controls applied to Hospitals, Doctors at the relevant time?
  • What evidence would establish how the relevant AI system 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.
  • AI technology is not specified in the source record.
  • AI system type is not specified in the source record.
  • Available evidence is insufficient for architecture relevance analysis.

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