---
title: Algorithmic Transparency and Explainability
type: concept
frequency: 4
papers_count: 4
related_concepts:
  - Algorithmic Fairness
  - Algorithmic Fairness in Child Welfare
  - Human-AI Collaboration
  - Algorithmic Discrimination
  - Intersectional Discrimination
tags:
  - concept
---
# Algorithmic Transparency and Explainability

## Definition

The degree to which users understand how an algorithmic system operates, which features influence its outputs, and how different inputs affect predictions. Workers demand explicit explanations rather than opaque 'black-box' decision-making.

## Co-occurrence

| Konzept | Gemeinsame Papers |
|---------|------------------|
| [[Algorithmic Fairness]] | 3 |
| [[Algorithmic Fairness in Child Welfare]] | 1 |
| [[Human-AI Collaboration]] | 1 |
| [[Algorithmic Discrimination]] | 1 |
| [[Intersectional Discrimination]] | 1 |
| [[Proxy Discrimination]] | 1 |
| [[Algorithmic Accountability]] | 1 |
| [[Trustworthy AI]] | 1 |

## Papers

- [[Improving human-AI partnerships in child welfare- Understanding worker practices, challenges, and desires for algorithmic decision support]]
- [[Algorithms, artificial intelligence and discrimination]]
- [[Advancing Accountability in AI]]
- [[AI for impact- The PRISM framework for responsible AI in social innovation]]

## Assessment-Divergenz

Von 4 bewerteten Papers: 3 Divergenzen (75%)

