---
title: Intersectionality in AI
type: concept
frequency: 3
papers_count: 3
related_concepts:
  - Algorithmic Fairness
  - Gender Bias in AI Systems
  - Responsible AI Development
  - Representation Bias
  - Algorithmic Bias
tags:
  - concept
---
# Intersectionality in AI

## Definition

Analytischer Ansatz, der untersucht, wie sich mehrere geschützte Merkmale (z.B. Geschlecht, Rasse, Klasse) wechselseitig verstärken und zu versteckten Diskriminierungsmustern führen, die Single-Attribute-Debiasing-Methoden übersehen.

## Co-occurrence

| Konzept | Gemeinsame Papers |
|---------|------------------|
| [[Algorithmic Fairness]] | 2 |
| [[Gender Bias in AI Systems]] | 2 |
| [[Responsible AI Development]] | 1 |
| [[Representation Bias]] | 1 |
| [[Algorithmic Bias]] | 1 |

## Papers

- [[Female perspectives on algorithmic bias- Implications for AI researchers and practitioners]]
- [[Policy advice and best practices on bias and fairness in AI (Kutscher_2023_Positionings,_challenges,_)]]
- [[Artificial Intelligence and Intersectionality (Ulnicane_2024_Artificial_Intelligence_an)]]

## Assessment-Divergenz

Von 1 bewerteten Papers: 1 Divergenzen (100%)

