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Interpretability Of AI
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Summary
Interpretability Of AI
is essential for ensuring that
Artificial Intelligence Systems
are
Transparent and understandable
to humans, which helps build trust and facilitates
Verification and debugging
. The challenge lies in balancing the
Complexity of high-performance models
with the necessity for them to explain their
Decision-making Processes
in a meaningful way.
Concepts
Explainable Artificial Intelligence
Model Transparency
Black Box Models
Feature Importance
Causality In AI
Trustworthy AI
Human-AI Interaction
Disentangled Representations
Post-hoc Interpretability
Alignment Problem
Relevant Degrees
Computer Hardware 44%
Data Management and Processing 33%
Science Methodologies 22%
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