---
title: Gender Bias in NLP
type: concept
frequency: 3
papers_count: 3
related_concepts:
  - Algorithmic Bias in Language Models
  - Algorithmic Fairness
  - Data Feminism
  - Intersectional Feminism
  - Intersectional Fairness
tags:
  - concept
---
# Gender Bias in NLP

## Definition

Phänomen, bei dem Natural Language Processing-Modelle sexistische Stereotypen in Trainigsdaten reproduzieren und verstärken, z.B. durch problematische Word Embeddings oder Autocomplete-Systeme.

## Co-occurrence

| Konzept | Gemeinsame Papers |
|---------|------------------|
| [[Algorithmic Bias in Language Models]] | 2 |
| [[Algorithmic Fairness]] | 1 |
| [[Data Feminism]] | 1 |
| [[Intersectional Feminism]] | 1 |
| [[Intersectional Fairness]] | 1 |

## Papers

- [[Prompting fairness- Learning prompts for debiasing large language models]]
- [[Data feminism for AI]]
- [[Bias and fairness in large language models- A survey]]

## Assessment-Divergenz

Von 1 bewerteten Papers: 1 Divergenzen (100%)

