TECHNOLOGY
Bias
A concise overview of Bias, how it relates to Trustworthy AI, key considerations, and conditions to confirm.
Item 1 of 1: Bias
Trustworthy AI
Bias
A concise overview of Bias, how it relates to Trustworthy AI, key considerations, and conditions to confirm.
Scope
For Bias, we define applicability from the purpose and constraints, including conditions where it should not be used. The relationship to Trustworthy AI remains visible so the reasons behind each decision can be reviewed.
Design decisions
For Bias, we avoid locking the design to one model or platform, separate data, integration, and monitoring, and record the reasons for each choice. The relationship to Trustworthy AI remains visible so the reasons behind each decision can be reviewed.
Validation
For Bias, we use repeatable inputs and criteria and inspect failure cases as well as expected behavior. The relationship to Trustworthy AI remains visible so the reasons behind each decision can be reviewed.
Operational review
For Bias, we track changes, quality shifts, and use patterns while keeping a path for rollback. The relationship to Trustworthy AI remains visible so the reasons behind each decision can be reviewed.
Human governance
For Bias, we do not leave consequential decisions to automation alone and define accountable review points. The relationship to Trustworthy AI remains visible so the reasons behind each decision can be reviewed.