Personal virtual assistants are limited because they only have access to one side of the story and user context. True artificial intelligence requires a social approach that learns from all conversations and contexts through a feedback loop. It must have the ability to understand different perspectives and process information as a group to have the wisdom to provide meaningful experiences to users.

1. Personal Virtual Assistants
Are Not Enough?
Let’s have a conversation
Mobile Voice 2016, San Jose, CA April 12, 2016
Paul S. Heirendt, Co-Founder & CEO, TradeHarbor, inc.
pheirendt@TradeHarbor.com Twitter: @pheirendt

2. “Keiserens nye Klæder”
The Emperor's New Clothes
This talk is an effort to
Start a Dialogue
inspiration through agitation
What?

3. Only Hears One Side of the
Story
Doesn't Know the Results
Attempts to Characterize
the User’s Behavior
Without the Context or the
Results
Issues with Personal Virtual assistants
No Feedback Loop

4. Personal Virtual assistants
Conflict Will
Happen

5. “The story of technology has been a long
one of automating things that humans do;
technology tends to be about picking a
task where we understand what the
objective is because humans are already
doing it, and then we make it possible to
do that in an automatic way using
technology.”
Stephen Wolfram
CEO, Wolfram
Research
• Mathematica
• Wolfram|Alpha
• Wolfram Language

6. Machine Learning is a scientific field
addressing the question:
"How can we program systems to
automatically learn and to improve with
experience?"
Tom Mitchell the first Chair of
Department of the first Machine Learning
Department in the World, based at
Carnegie Mellon.

7. Consumer Expectation Is Very High

8. Current technology doesn't meet Expectations

9. Current technology doesn't meet Expectations

10. Is It a Smart Car if You have to
tell it everything you want
done?

11. Nobody is
asking for
more interfaces
and independent
applications

12. Current technology doesn't meet the
Expectation
User
frustration
is the result

13. though it also wants
to be expensive”
“Information
wants to be free…
Stewart Brand,
Founder of
the WELL
1984

14. IA
Content
Context
User
Rosenfield and Morville - Information Architecture for the World Wide Web 1998
IA = Information Architecture

15. AI = Artificial Intelligence
AI
User Content
Context

16. Amount of data
Performance
Large NN
Medium NN
Small NN
Traditional
learning also
Andrew Ng
Associate Professor at
Stanford
Chief Scientist of Baidu
Chairman and Co-Founder
of Coursera.
https://youtu.be/LcfLo7YP8O4
Scale Is Enabling Deep Learning

17. ?
Only Hearing One Side of the
Story
Access to All Sides of the Story is Required

18. Only Hearing One Side of the
Story
Access to All Sides of the Story

19. Old
Friends?
Business
Partners?
Cell Mates!
Sides
Of The Conversation
- Context is Key

20. Context
Data
Experience
Information Knowledge Wisdom
Understanding
Feedback
Loop

21. Intent
Content Context
Insights Purpose
+
Meaningful
Experience
Feedback
Loop

22. Knowledge is Organized information
Wisdom is the understanding and
application
Insight is the underlying truth

23. Knowledge:
a tomato is a fruit
Wisdom:
Don't put it in fruit salad.
Knowledge Alone - is Not
Enough

24. Who is Right?
No Way to Know
Without Perspective
Perspective
is also Critical

25. “Depending on their organization,
groups must have cognitive properties
that are not predictable from a
knowledge of the properties of the
individuals in the group.”
a Group Is More Than The Sum Of The Individuals
Observations of a group of Navy
navigators and how they thought and
processed as a group…
Edwin Hutchins - Dept of Cognitive Science,
UCSD

26. Distributed Cognition (DCoG)
“Thinking does not just inhabit the
mind of one person, but exists
across a group.”
Social Artificial Intelligence | Justine Cassell

27. TradeHarbor Continuous Speaker
Modeling

28. TradeHarbor
Continuous
Speaker
Modeling
ROW ModelSpeak
er
Model

29. Blind Guessing Doesn't Work

30. Do You Need A Meeting Just To Set A
Meeting

31. Bigger The Meetings - More Complex

32. The More People Involved…

33. …The More Complicated The Communication

34. Social AI - Learning From All Conversations &
Contexts

35. Social Artificial Intelligence Engine
© 2016 Skejul
Individual’s Model
People
Places
Preferences
Priorities
Potential
Ad Hoc Group Best Fit Solutions
Solution Set
Learnings From User Behavior
USPTO 14/941,142
Systems and Methods for Private
Scheduling Coordination and Event
Planning

36. SO, Personal Virtual
Assistants
Are Not Enough!
Mobile Voice 2016, San Jose, CA April 12, 2016
Paul S. Heirendt, Co-Founder & CEO, TradeHarbor, inc.
pheirendt@TradeHarbor.com Twitter: @pheirendt
Inter-Personal Virtual
Assistance
“Social AI”

37. Dig Deeper
Justine Cassell - Social Artificial Intelligence
Human-Computer Interaction Institute (HCII)
Carnegie Mellon University
https://youtu.be/WGtVR0XSzPA
Edwin Hutchins
Studying Cognition in the Wild
Professor, Department of Cognitive Science
University of California San Diego
Nils J. Nilsson
Department of Computer Science
Artificial Intelligence Laboratory
Stanford University
Stephen Wolfram
CEO, Wolfram Research
• Mathematica
• Wolfram|Alpha
• Wolfram Language
https://youtu.be/DszFKW4d2Rw
Tom Mitchell
The first Chair of Department of the first
Machine Learning Department in the
World, based at Carnegie Mellon.
Andrew Ng
Associate Professor at Stanford
Chief Scientist of Baidu
Chairman and Co-Founder of Coursera.
https://youtu.be/LcfLo7YP8O4

38. Personal Virtual Assistants
Are Not Enough?
Mobile Voice 2016, San Jose, CA April 12, 2016
Paul S. Heirendt, Co-Founder & CEO, TradeHarbor, inc.
pheirendt@TradeHarbor.com Twitter: @pheirendt