OOF-AII-773520
Deepfake Obama Introduction of Deepfakes
University of Washington researchers made a deepfake of Obama, followed by Jordan Peele
- Event date
- 2017-07-01
- 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
- High
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 2017-07-01.
- The incident record identifies the location as United States of America.
Reported claims
- University of Washington researchers made a deepfake of Obama, followed by Jordan Peele
Material unknowns
- Independent corroboration is not established in the available incident record.
Primary governance problem
The incident appears to expose a governance problem involving evidence, identity, origin. Available reporting supports preliminary methodological interpretation, not a finding of fault or non-compliance.
Architecture intelligence
OBIDENITY® — Origin-Bound Identity Governance Architecture
Primary architecture
The reported evidence, identity, origin concern falls within the governed questions represented by OBIDENITY® — Origin-Bound Identity Governance Architecture.
Governance focus: How should evidence, identity, origin be governed in the conditions described by the available incident evidence?
Canonical methodology (ParentStandard):
ASGA™ — Autonomous Systems Governance Architecture
Contributing architecture
The reported identity, arts, evidence concern falls within the governed questions represented by ASGA™ — Autonomous Systems Governance Architecture.
Governance focus: How should identity, arts, evidence 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.
LIGA™ — Liability Governance Architecture
Contributing architecture
The reported network, evidence concern falls within the governed questions represented by LIGA™ — Liability Governance Architecture.
Governance focus: How should network, evidence 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 evidence, identity, origin be governed in the conditions described by the available incident evidence?
- How should identity, arts, evidence be governed in the conditions described by the available incident evidence?
- How should network, evidence be governed in the conditions described by the available incident evidence?
- What operational authority and controls applied to University Of Washington, Fakeapp 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.