This document discusses explainable artificial intelligence and the importance of interpretability for building trust in AI systems. It describes Bleckwen's approach to combining complex machine learning models with local surrogate models and technologies like LIME to extract explanations for decisions in a way that is understandable to humans. The goal is to enable effective collaboration between human and artificial intelligence, with applications in industries like banking to fight financial fraud using interpretable machine learning and behavioral profiling.

1. Explainable AI:
Machine Learning for Humans
Yannick Martel
Bleckwen Director
12 June, 2018 @bleckwen_ai
Leonardo Noleto
Bleckwen Senior Data Scientist
www.linkedin.com/company/bleckwen

2. Artificial Intelligence is Everywhere

3. Booking an appointment
for you

4. Beating the Go Master

5. Carrying goods

6. Defeating Breast Cancer

7. Speaking Chinese

8. And even painting

9. When a task can be
automated at a low cost, the
task will be automated.
Image from Kurzweil’s The Singularity Is Near, published in 2005.

10. Autonomous
AI
Augmented
Human
Human-in-the-loop Human-out-of-the-loop

11. We believe in a collaboration between
Human and Artificial Intelligence.
Interpretability is the key enabler.

12. Why you should care about
Interpretability?
Image from Drive.ai, a self-driving car service for public use in Frisco, Texas

13. “Interpretability is the degree to which a human can
understand the cause of a decision.”
Miller, Tim. 2017. “Explanation in Artificial Intelligence: Insights from the Social Sciences.”

14. Why do we need interpretability?
STRENGTHEN TRUST AND
TRANSPARENCY
SATISFY REGULATORY
REQUIREMENTS
EXPLAIN DECISIONS
IMPROVE MODELS
Get more information in our blog post

15. But what about the trade-off Accuracy vs. Interpretability?
Image source: https://blog.bigml.com/2018/05/01/prediction-explanation-adding-transparency-to-machine-learning/amp/

16. Explaining the taxonomy of Interpretability
globallocal

17. Explaining the taxonomy of Interpretability
Model-
agnostic
Model-specific

18. Explaining the taxonomy of Interpretability
globallocal
Model-
agnostic
Model-specific

19. Explaining the taxonomy of Interpretability
globallocal
Model-
agnostic
Model-specific
Added value for
industries

20. How we are helping the banking industry accelerate
the adoption of AI?

21. Our clients are fighting against financial
fraud with the power of Machine
Learning and the Behavioral Profiling
while keeping decisions
interpretable.

22. How is that possible?

23. Complex Model
Local surrogate model
Introducing LIME
Local Interpretable Model-Agnostic Explanations

24. Introducing LIME
Local Interpretable Model-Agnostic Explanations
Extracting explanations from a linear model

25. We combine best-in-class Machine Learning models with
interpretation technologies to get the best from
a collective artificial and human intelligence
Get more information in our blog post

26. Collaboration between
Human Being and Artificial Intelligence will
secure the world.

27. DEEP TRUTH REVEALED
Anti-fraud solution for banks
Thank you for your attention.
www.bleckwen.ai
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