Key Takeaways: -Why is this hard? *A quick overview on Integrity (or Trust & Safety) related risks in products with some examples -How can technology help? *Role of AI/ML in mitigating those risks -As a product leader how can you be prepared? *Being proactive *Partnering with cross functional teams efficiently *Measuring progress & success

1. Building Products with Integrity Mindset
by Facebook Tech PM
www.productschool.com

2. CERTIFICATES
Your Product Management Certificate Path
Product Leadership
Certificate™
Full Stack Product
Management Certificate™
Product Management
Certificate™

3. Corporate
Training
Level up your team’s Product
Management skills

4. Free Product Management Resources
BOOKS
EVENTS
JOB PORTAL
COMMUNITIES
bit.ly/product_resources
COURSES

5. Building Products with Integrity Mindset

6. Vasanth Arunachalam
Head of Technical Program Management
Business Integrity at Facebook

7. Agenda
01 Why is this hard?
02 As a product leader how can you be prepared?

8. 01 Why is this hard?
Definition
Evolution
Examples

9. Definition
Reducing the risk exposure on your products and platform

10. Evolution
300 BC 193 AD 1920
Hegestratos - Greek
merchant sinking ship
to claim insurance
The Praetorian Guard
tried to sell the Roman
empire
Ponzi
1980
Money
transfer
1990
Phishing
2000 2010-2020
Malware;
Credit card
Ad fraud, Scams,
Impersonation,
Misinformation

11. Marijuana or Broccoli?
Examples

12. Strand of hair - Click fraud
Examples
80% off
BLACK FRIDAY SALE

13. Examples
Bicycle on a truck - Problem for self-driving cars

14. 02 As a product leader how can
you be prepared?

15. Stakeholders
Data
Standards
Technology
Problem

16. Stakeholders
● Understand who you are serving - People, Businesses
● Understand how your customers will use your product/platform
○ Perform a comprehensive risk assessment
○ Being proactive is key
App Store ECommerce Dating Services Autonomous vehicles Social media

17. Standards
● What is permissible when someone engages with your product or platform?
● Codify your standards into policies that are explainable and defensible
● Partner with internal subject matter experts here

18. Data
● Size and Scope
● Mitigate
● Measure success (or lack thereof)
Precision
(minimizing false positives)
Things we DID consider a
problem that WERE NOT a
problem
Recall
(minimizing false
negatives)
Things we DID NOT consider to
be a problem that WERE a
problem
True Negative
Things we DID NOT consider
to be a problem that WERE
NOT a problem
True Positives
Things we DID consider to be a
problem that WERE a problem

19. Example use case: Ad Review at Facebook

20. Technology: Role of AI/ML
Manual Automated
● Works at smaller scale
● Works for nuanced cases
● Expensive
● Can still be a fallback mechanism
● Scalable
● Reasonably predictable
● Cost effective
● Proactive

21. Computer Vision
Understanding the visual world around
us. Making sense of digital images and
videos.
Natural Language
Processing
Text understanding and generation.
Ability to work across multiple
languages and interpret context.
Speech & Audio
Spoken language technology including
speech recognition and synthesis.
Technology: Role of AI/ML

22. At Facebook, we invest in cutting-edge machine learning technology to protect people from harmful content such as hate speech, misinformation
Technology: Role of AI/ML
The challenge of multimodal AI

23. Thank you

24. www.productschool.com
Part-time Product Management Training Courses
and
Corporate Training