Yevgeniy Vahlis, Head of Applied Machine Learning, Borealis AI

2. our
mandate:

3. who we are

4. Privacy
Preserving
AI

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why privacy?

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problem statement

7. But I’m removing PII??!
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● 天涯人肉搜索引擎
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Most organizations have processes for anonymizing and
sanitizing data to protect privacy, however...

8. Toward real privacy & data aggregation
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You can create lasting differentiation by mathematically
proving that your customers’ data is protected

9. Who is doing it?
The 1st rule of DP club is that you don’t talk about DP club…
unless you’re Apple

10. General property of security psychology

11. What is
differential
privacy?

12. Differential privacy
ML
Model
ML
Model
ML
Model
Aggregate
Model
Data
Data
Data
Add Noise
“Differential privacy lets you gain insights from large datasets, but
with a mathematical proof that no one can learn about a single
individual.”

13. Differential privacy (non) guarantees
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14. Differential privacy guarantees
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15. Differential privacy misconceptions
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16. Technical
crash course

17. Definition
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18. Randomized response

19. Laplacian mechanism [Dwork06]

20. Teacher student model [PAEGT2017]

21. Examples of Use Cases
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