Concept#Artificial Intelligence#Data
Bias in AI Systems
Bias in AI systems are systematic distortions in data, models, or decision processes that can produce unfair or discriminatory outcomes. This concept explains root causes, common types (e.g. data, sampling, measurement bias) and practical approaches to detect and mitigate bias across data collection, model training and deployment.
This block bundles baseline information, context, and relations as a neutral reference in the model.
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What is this view?
This page provides a neutral starting point with core facts, structure context, and immediate relations—independent of learning or decision paths.
Baseline data
Context
Organizational leveli
Enterprise
Organizational maturityi
Intermediate
Impact areai
Organizational
Decision
Decision typei
Design
Value stream stagei
Build
Assessment
Complexityi
High
Maturityi
Emerging
Cognitive loadi
High
Context in the model
Structural placement
Where this block lives in the structure.
Relations
Connected blocks
Directly linked content elements.
No relations available.