Bye-bye, Miss AI

The presentation describes a need to implement explainable AI.

Transcript

1. Kacper Łukawski, Data Science Lead at Codete
   

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2. Agenda:
   AI hype
   ML project lifetime
   Real-life story
   XAI
   

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3. Forty percent of “AI startups” in Europe don’t actually
   use AI
   The State of AI 2019: Divergence
   AI hype
   

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4. Startups labelled as being in AI attract 15% to 50% more
   funding than other technology firms.
   The State of AI 2019: Divergence
   AI hype
   

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5. 1. Data wrangling
   2. Model training
   3. Validation
   4. Inference
   ML project lifetime
   

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6. ML project lifetime
   1. Data wrangling
   2. Model training
   3. Validation
   4. Inference
   

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7. Real-life story
   

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8. 1. Sweet little girl
   2. Her grandmother
   3. Little red cap
   4. A piece of cake and a bottle of wine to be
   delivered
   5. Big bad wolf
   Real-life story
   

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9. The question is:
   How to distinguish grandma from a wolf?
   Real-life story
   

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10. It doesn’t matter what is the issue. Our Little Red Riding
    Hood needs some support so badly. The original story
    comes from the 17th century and at this time there was
    no rescue, but now we have AI!
    Real-life story
    

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11. There is a well-known example of a Machine Learning
    system designed for classifying the images of wolves
    and huskies.
    Classification: wolf or a husky?
    

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12. Even though, just by looking at the numbers, everything
    may seem to work perfectly, we need to understand how
    it works behind the scene.
    Classification: wolf or a husky?
    

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13. We are in a point, when we desperately need AI that can
    be explained. In other words, our models cannot just
    make the decisions - they need to clarify them as well or
    at least allow to be clarified.
    XAI
    

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14. Thank you!
    Kacper Łukawski
    kacper.lukawski@codete.com
    

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