Statements (29)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:concept
|
| gptkbp:addressedTo |
gptkb:legislation
debiasing techniques fairness metrics |
| gptkbp:aimsTo |
ensure equitable outcomes
|
| gptkbp:challenge |
societal impact
defining fairness measuring fairness trade-offs with accuracy |
| gptkbp:concerns |
gptkb:racism
algorithmic fairness bias |
| gptkbp:debatedBy |
gptkb:industry
gptkb:researchers policy makers |
| gptkbp:example |
AI ethics issue
|
| gptkbp:importantFor |
AI governance
trustworthy AI ethical AI |
| gptkbp:relatedTo |
gptkb:artificial_intelligence
gptkb:machine_learning |
| gptkbp:studiedIn |
gptkb:law
gptkb:philosophy computer science social sciences |
| gptkbp:bfsParent |
gptkb:Berkeley_Artificial_Intelligence_Research_(BAIR)
gptkb:Olga_Russakovsky |
| gptkbp:bfsLayer |
7
|
| https://www.w3.org/2000/01/rdf-schema#label |
Fairness in AI
|