[The full content of this talk can be found in this article: https://medium.com/@clarecorthell/hybrid-artificial-intelligence-how-artificial-assistants-work-eefbafbd5334] When we think about automated, learning systems, we often think of a world without humans - but there are many signs and limitations that show we’re not moving toward a human-free world. We’ll explore the strengths and weaknesses of humans and computers, and explore the new design paradigm that’s making artificial intelligence more powerful than it’s ever been before. Thinking Machines Conference, February 2016, Manila http://thinkingmachin.es/events/

1. Hybrid Intelligence
The New Paradigm
in Artificial Intelligence
@clarecorthell
Clare Corthell
thinkingmachin.es/events

2. Luminant Data
is a Machine Intelligence Consultancy
building more intelligent businesses
with data science strategy and
artificial intelligence technology
clare@luminantdata.com
based in San Francisco
Clare Corthell, Founder

3. datasciencemasters.org
The Open Source Data Science Masters
The most popular curriculum for
learning data science

4. Artificial Intelligence, “AI”
has massive potential to change
how we live and work
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6. Two visions of the future
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7. The Vision of the Internet
a huge catalog
highly structured
standardized
firstly,
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8. the data format
the dream
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9. The Vision of the Internet
The Web was designed as an information space, with the
goal that it should be useful not only for human-human
communication, but also that machines would be able
to participate and help. One of the major obstacles to
this has been the fact that most information on the
Web is designed for human consumption, and even if
it was derived from a database with well defined meanings
(in at least some terms) for its columns, that the structure
of the data is not evident to a robot browsing the Web.
Tim Berners-Lee, 2001
On the “Semantic Web”
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10. The Vision of the Internet
a huge catalog
highly structured
standardized
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11. The Vision of the Internet
a huge catalog
highly structured
standardized
Reality
a mess
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12. The Vision of a world with Machines
secondly,
1.Machines take over all tasks
2.Humans no longer required
3.Humans Prosper.
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13. 1.Machines take over all tasks
2.Humans no longer required
3.Humans Prosper
some
stuff
The Vision of a world with Machines
Reality
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14. So in a world
where the internet is a mess
and machines can’t do everything for us
What do we do?
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15. Artificial Intelligence is a collection of
technologies that emulate intelligence
two specific technologies
Machine Learning uses statistics to
make educated guesses
Natural Language Processing helps
computers understand human language
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16. Broadly stated, Machine Learning lets us
take patterns from the past and project
them going forward, sometimes allowing
us to infer what might happen, including
guess what a human might think or do
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17. The Computer’s Limits of Understanding
those r cats! where is the cat plz
computercomputer
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18. Machine Learning is about 75% accurate,
or maybe 90% in certain circumstances.
That’s not good enough for most products.
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19. Computers and Humans
have very different talents
Humans
Creativity
Intuition
Choosing arbitrarily
Learning new things
Being empathic
Computers
Math
Paring down options
Repeating forever
Being fast
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20. Neither the Computer nor the Human
is objectively better —
they just have different strengths
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21. Given this truth
about humans and computers,
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22. In building businesses and technologies,
we must anticipate a different future.
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23. A New Paradigm
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24. The Hybrid Intelligence Paradigm
(not neural nets or the superintelligence)
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25. Leverages what humans do best
and what computers do best.
Asks humans to make judgments when the
computer is less confident —
resulting in the most accurate, trustworthy system.
The Hybrid Intelligence Paradigm
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26. Development:Training&Test
machinelearningalgorithm
new
input prediction
Active Learning Pattern Credit:
Lukas Biewald, Crowdflower
Hybrid Intelligence Design Pattern:
Active Learning
human prediction
confident
not confident
output
human labelled “feedback” data added back into training data
Production: Prediction Production: Active Learning
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27. Where are we seeing Hybrid AI
in applications?
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28. Consumer Applications ArtificialAssistant
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29. It’s simple, right?
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30. Development:Training&Test
decisiontree
algorithm
new
request
suggested response
Hybrid Intelligence Design Pattern:
Hybrid Interaction
human validation
send
response
human labelled “feedback” data added back into training data
send
response
don’t send
response
extractentities&captureintent
structured
data
compose
new response
“I want to take the
next flight to Cebu
this afternoon.”
“I have booked you
for the 5pm flight.
Have a nice trip!”
execute task
book flight
existing
context
current time
current location
credit card
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31. wired.com

32. Hybrid Intelligent Agent Systems
Hybrid Distributed
Humans
Automated
urgencyofresponse
slowfrom fully automated to fully humanfast
“Hybrid Interaction”
“Active Learning”
Siri
Duer
Cortana
Customer
Service Centers
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33. 25%75%
Human AI
The Reality for Artificial Assistants
humans deal with
everything that isn’t
an easy, known case
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34. 90%10%
Human AI
The Dream for Artificial Assistants
humans deal with
contextually tough
or new cases
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35. Artificial Assistants don’t work very well yet.
But there’s one important thing to pay
attention to —
and it has to do with design.
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36. Hi ,
How are you?
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37. Anthropomorph Design
chat interaction establishes an interaction paradigm
human language establishes empathy and trust
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38. The Hybrid AI Paradigm will change everything —
it’s already happening.
In the next customer service revolution that
leverages Hybrid Interaction,
BPOs must be ready for the boom.
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Business
Process
Outsourcing

39. Humans will never be irrelevant.
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The Most Important Point Here:

40. Humans are the only part of the equation
endowed with empathy
and the creativity to imagine the future.
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41. Clare Corthell
clare@luminantdata.com
twitter @clarecorthell
Thank You!