Breaking black-box AI

Accompanying demos at https://github.com/evelinag/breaking-black-box-ai

Transcript

1. BREAKING BLACK BOX AI Evelina Gabašová @evelgab evelinag.com
2. Dr Evelina Gabašová Principal Research Data Scientist Research Engineering group
3. STAR WARS SOCIAL NETWORK
4. AIR TRAFFIC CONTROL
5. STATE OF MACHINE LEARNING IN 2019
7. MACHINE LEARNING APIS
8. NO MATHEMATICS NEEDED
9. COMPILER Lexer Tokenizer Parser ASTs ... You don't need to know this to use a compiler
10. SOFTWARE DEVELOPMENT MACHINE LEARNING Algorithms Implementation bugs Fails silently
11. BLACK BOX MACHINE LEARNING
12. RULES •Use algorithms out of the box with minimal setup •Keep mathematics at minimum •Observe where things go wrong
13. LINEAR REGRESSION
14. DEMO LINEAR REGRESSION
15. Weak exogeneity Homoscedasticity Lack of perfect multicollinearity
16. HUMAN COMPUTER INTERACTION
17. DEMO DECISION TREE
18. Wikipedia: decision trees
19. AAARGH
20. DEMO DEEP LEARNING
22. reddit u/MalletsDarker
25. MACHINE VISION IN MEDICINE
28. DATA
32. SALARY DISTRIBUTION
39. MACHINE LEARNING MAGIC
42. DATA
43. ASK QUESTIONS Where do the training data come from? How did you preprocess the data? Are there outliers in the data? What are the biases in the data? Are real-world data different from training data? Is the model the right one for the data? Is your model doing what you think it's doing?
44. THE DATA SCIENCE ICEBERG
46. BREAKING BLACK BOX AI Evelina Gabašová @evelgab evelinag.com