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C S E 4 2 2 - C O M P U T E R G R A P H I C S
MD.ANISUR RAHMAN
192-15-2825
E X P L A I N A B L E
C S E 4 2 2 - C O M P U T E R G R A P H I C S
CONTENTS
1)EXPLAINALBLE AI
2)PROVIDNG ANSWERS
3)CONSTITUENTS
4)METHODS
5)PROCESS
6)EXAMPLE
7)USE CASES
WHAT IS EXPLAINABLE AI!!??
Explainable AI (Artificial Intelligence) is a set
of tools and frameworks to help you
understand and interpret predictions
made by your machine learning models.
With it, you can debug and improve
model performance, and help others
understand your models' behavior. It is
also known as XAI. It basically helps
the human world by explaining the
factors, results and reasons for trust.
PROVIDING ANSWERS…
✓Describes the challenge of understanding why an
artificial intelligence algorithm makes a decision.
✓The question of “why” should be answered in an
understandable and interpretable way.
✓ The question of whether artificial intelligence can
be explained.
✓“How does AI work?” or “how does the AI arrive
at this result”
WHY THE EXPLANATION
Questions around AI explainability help us understand
how data, predictions and algorithms influence decisions.
EXPLAINABLE AI CONSTITUENTS
LIME -
Local
Interpretable
Model-agnostic
Explanations
SHAP -
SHapley Additive
exPlanations
ELI5 -
Explain Like I'm
Five
Skater -
Skater is a
unified
framework
What – If -
easy-to-use
interface for
expanding
understanding of
a black-box
Explainable AI Methods
EXAMPLE
EXAMPLE
USE CASES
THANK YOU
“ O U R I N T E L L I G E N C E I S W H AT M A K E S U S H U M A N ,
A N D A I I S A N E X T E N S I O N O F T H AT Q U A L I T Y ”
– YA N N L E C U N

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