OOF-AII-816793
Personal voice assistants struggle with black voices, new study shows
A study found that voice recognition tools from Apple, Amazon, Google, IBM, and Microsoft disproportionately made errors when transcribing black speakers.
- Event date
- 2020-03-23
- 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 2020-03-23.
- The incident record identifies the location as United States of America.
Reported claims
- A study found that voice recognition tools from Apple, Amazon, Google, IBM, and Microsoft disproportionately made errors when transcribing black speakers.
Material unknowns
- Independent corroboration is not established in the available incident record.
Primary governance problem
The incident appears to expose a governance problem involving communication, information, support, when. Available reporting supports preliminary methodological interpretation, not a finding of fault or non-compliance.
Architecture intelligence
PGA™ — Prediction Governance Architecture
Primary architecture
The reported communication, information, support 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 Microsoft, Ibm, Google, Apple, Amazon at the relevant time?
- What evidence would establish how yes 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.