The desire for automation in the Fourth Industrial Age has led to conversations around AI, ML, and NLP becoming essential components of innovation. As markets shift while these technologies become ubiquitous, the role of product managers has expanded beyond being the voice of the customer to being the voice of the society. This talk covers the skills that PMs need in order to balance innovation against other large-scale implications. It also reviews the strengths and weaknesses of incorporating AI and NLP-components, and shares tools for PMs to stay connected with market and customer needs in the automated economy.

1. Product Management for
AI in the Automated Economy
Denver Startup Week,
2018
Poornima Farrar
@poornimafarrar

2. AI
Products
AI Product
Management
Discussion Points

3. But wait...AI, ML, NLP! What’s the difference?

4. AI: Teaching Robots to be Human

5. NLP: Bringing Language Online

6. Machine Learning: Define, Learn
and Judge AI Actions

7. Evolution of AI Products

8. Automation and the Industrial Age

9. “The first company that ever had a
horse to run was Hook and Ladder No. 1.
The introduction of horse power was
owing to a squabble in the company,
which resulted in the resignation of so
many members that not enough
remained to draw the truck to a fire.”
-New York Roots

10. Between 1910 and 1950, auto industry created 7.5 million jobs
created and destroyed 623,000 jobs.
-McKinsey

14. AI: The Early Years

15. Computers as a Second Language

16. Are AI Products Displacing Jobs?

18. AI Acquisitions For An Automated
Economy

19. Corporate AI Gold Rush
By 2021, organization will spend $52.2 billion annually on A.I. related products.
+ many billions more in savings and gains from that investment.
Where will this efficiency come from?
Matching Product to Consumer

20. Is the AI Revolution Here?

21. pe n i n
em
pe n i n
no -ta g
di l g
ed i n
di l g a k
di l g
fi c
An Automated Economy running on AI
a t a n
he h e

22. pe n i n
em
pe n i n
no -ta g
di l g
ed i n
di l g a k
di l g
fi c
An Automated Economy running on AI
a t a n
he h e
A.I. could contribute up to $5.7 Trillion
to the global economy in 2030, more
than the combined output of China and
India today.

23. AI Product Management

24. Building Blocks for AI Products
Monitoring Personalization
Control
Diagnostics
Optimization
Performance
Self-service
Autonomy
Self-coordination
Self-operation

25. da al sco n a n
p i ti on
et l
de on-ma g
ac li n
de pi &
di r g
id
te r &
co b a n
re ce
ma me
re c
s t e s
Product Management Skills

26. te n y
t e d
c o s-cu r
k o l
...
et l
de on-ma g
ec ic
t e d
t a s n
& se t
p o c it a t o y
p i c &
re ti
More PM Skills

27. Delivering the Human Context

28. With Emerging Technologies,

29. UX
TechBusiness
PM
”Whe m eh o
en s eq i , t i g
go l e . Tha 's y
p si s a n ci y
is d."
-Ne l a s T n
Consider the Human
Factor

30. How does this relate to AI?

31. Understanding Humans in an
Automated Economy

32. Responding to Human Needs

33. Understanding Bias in Data

34. Understanding Bias in Users

35. Understanding Limitations of Algorithms
Low High
Precision
Recall

36. Understanding Limitations of Algorithms
Low High
Precision
Recall
Who is eligible for insurance?
Who goes to prison?
Is this email spam?
Is this translation accurate?

37. Evaluating Ethics

38. Redefining Innovation

39. PM Tools/Resources

40. Resources - Machine Learning and NLP

41. Resources - AI and Human Factor

42. Still a lot we don’t know!

43. Thanks!
@poornimafarrar