OOF-AII-800840
Major Universities Are Reportedly Using Race as a 'High Impact Predictor' of Student Success
Several major universities are reportedly using a tool that uses race as one factor to predict student success.
- Event date
- 2012-01-01
- Country
- United States of America
- Severity
- Moderate
- 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 2012-01-01.
- The incident record identifies the location as United States of America.
Reported claims
- Several major universities are reportedly using a tool that uses race as one factor to predict student success.
Material unknowns
- Independent corroboration is not established in the available incident record.
Primary governance problem
The incident appears to expose a governance problem involving prediction, support, performance, probability, uncertainty. Available reporting supports preliminary methodological interpretation, not a finding of fault or non-compliance.
Architecture intelligence
PGA™ — Prediction Governance Architecture
Primary architecture
The reported prediction, support, performance concern falls within the governed questions represented by PGA™ — Prediction Governance Architecture.
Governance focus: How may a prediction be communicated, interpreted, and relied upon without exceeding what its methodology, uncertainty, feasibility, intended purpose, and governed conditions legitimately support?
Canonical methodology (ParentStandard):
Preliminary governance questions
- How may a prediction be communicated, interpreted, and relied upon without exceeding what its methodology, uncertainty, feasibility, intended purpose, and governed conditions legitimately support?
- What operational authority and controls applied to University Of Wisconsin Milwaukee, University Of Massachusetts Amherst, University Of Houston, Texas Aandm University, More Than 500 Colleges, Georgia State University at the relevant time?
- What evidence would establish how Eab Navigate, Ai Enabled Decision Support Systems 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.