Concept#Artificial Intelligence#Analytics
Explainable AI
Explainable AI (XAI) comprises techniques for representing and assessing the decision basis of machine learning models. It enables stakeholders to understand model behavior, detect bias and meet regulatory requirements. XAI is particularly relevant in high-stakes domains such as healthcare, finance and public administration.
This block bundles baseline information, context, and relations as a neutral reference in the model.
Open 360° detail view
Definition · Framing · Trade-offs · Examples
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
Domain
Organizational maturityi
Intermediate
Impact areai
Business
Decision
Decision typei
Architectural
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.
Content · Related to
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