Korea day1 keynote 20161013 v6

Artificial Intelligence (AI)
Jim Spohrer (IBM)
Seoul, South Korea; October 13, 2016
Consulting Conference
http://www.slideshare.net/spohrer/korea-day1-keynote-20161013-v6
10/4/2016 Understanding Cognitive Systems 1

Today’s Talk
• Abstract: Artificial Intelligence (AI)
• IBM is transforming into a cognitive solutions and cloud platform
company. What opportunities and challenges? What was IBM’s
response to a recent White House RFI about Preparing for the
Future of Artificial Intelligence?
• Bio:
• Jim Spohrer, IBM, Director Understanding Cognitive Systems
• Former Director, University; Service Research; CTO IBM VC Group
• Jim is developing a next generation curriculum to help learners
build, understand, and work with cognitive systems. Education:
Yale Computer Science (AI&CogSci) PhD, MIT Physics BS.
Jim Spohrer
IBM

Today’s Talk
• Four Cool Tech Topics
• Today: AI
• If time others
• Definitions
• Perspectives
• Industry
• IBM
• Relationships
• Industry 4.0/IoT
• Challenge & Opportunity
• Too hard to build, understand,
and work with AI systems
10/4/2016
© IBM UPWard 2016
5

Definition: Intelligence
• Intelligence has been defined in many
different ways including as one's capacity
for logic, understanding, self-awareness,
learning, emotional knowledge, planning,
creativity and problem solving. It can be
more generally described as the ability to
perceive information, and retain it as
knowledge to be applied towards adaptive
behaviors within an environment or
context.
10/4/2016
© IBM UPWard 2016
6

Definitions: AI vs IA
10/4/2016
© IBM UPWard 2016
7
AI is Artificial Intelligence, or
intelligence in machines (smart machines)
IA is Intelligence Augmentation, or
people thinking and working together with smart machines.
IA is what IBM calls “Cognitive Computing” and
the smart machines are called “Watson Solutions” or
more generally “Digital Cognitive Systems (Cogs)”

Definitions: Types of Cognitive System Entities
(symbol and pattern processing systems)
• Socio-Technical (Organization-based)
• Businesses
• Cities
• Nations
• Biological (Brain-based)
• People
• Animals
• Technological (Computation-based)
• Embodied (Robot, Car, Device)
• Virtual (Local, Cloud)

Industry Perspective

IBM Perspective
10/4/2016 Future of AI 15

Request:
White House OSTP
• The White House Office of Science and Technology Policy is particularly
interested in responses related to the following topics:
• (1) the legal and governance implications of AI;
• (2) the use of AI for public good;
• (3) the safety and control issues for AI;
• (4) the social and economic implications of AI;
• (5) the most pressing, fundamental questions in AI research, common to
most or all scientific fields;
• (6) the most important research gaps in AI that must be addressed to
advance this field and benefit the public;
• (7) the scientific and technical training that will be needed to take advantage
of harnessing the potential of AI technology;
• (8) the specific steps that could be taken by the federal government,
research institutes, universities, and philanthropies to encourage multi-
disciplinary AI research; and
• (9) the use of open data sets to close fundamental research gaps;
• (10) the role of incentives and prizes to accelerate public benefits;
• (11) any additional information related to AI research or policymaking, not
requested above, that you believe OSTP should consider.

A. The Use of AI for the Public Good
• Healthcare
• Social Services
• Education
• Financial Services
• Transportation
• Public Safety
• The Environment
• Infrastructure

B. Social and economic
implications of AI
• History: Technologies with broad
potential across industries like AI
increase:
• Productivity
• Earnings
• Job growth
• Adjustment: Social, learning, and
decision making capabilities are
key to acceptance of AI in society
• Underserved: Potential to help
underserved populations and
improve their quality of life

C. Education for
harnessing AI technologies
• Demand: High demand for AI,
machine learning, data science and
related courses; many MOOCs
• Industry Platforms: Growing set of
companies provide learners access to
cognitive service capabilities in their
clouds
• Gap: Need curriculum for learners
with no programming or advanced
mathematics background

D. Fundamental questions
in AI research, and
the most important
research gaps
• Machine learning and reasoning
• Decision techniques
• Domain-specific AI systems
• Data assurance and trust
• Radically efficient computing
infrastructure

E. Data sets that can
accelerate AI research
• Bottleneck: Develop and validate
data sets that are:
• Large and unbiased
• Openly curated
• Publically accessible
• Domains: Novice to expert task
performance is hard to get for all
occupations and industries
• Models: Incentives to share trained
models that require lots of data and
compute time to create

F. Multi-disciplinary
research
• Disciplines: Breadth of disciplines
to tackle issues:
• Psychology and cognitive science,
philosophy, design and art, public
policy and management, law and
regulations
• Systems: Professional associations
to tackle industry and system
issues, including novice to expert
progression on tasks
• Socio-technical system design
loop and smart service systems

G. Role of incentives
and prizes
• Example:
• IBM Watson AI XPrize ($5M)
• Best AI system to empower teams
of people to tackle the world’s
grand challenges
• TED 2020, finalists present
• I-athlon
• More objective scoring
• Rational processes
• Multiple dimensions of intelligence

H. Safety and
control issues for AI
• Trust & Trustworthiness
• Ethical & Social Norms
• Algorithmic Transparency
• Unexpected Interactions
• Safeguards

Partnership for AI formed

I. Legal and governance
implications of AI
• Responsible & inclusive dialogue
• Elevate the dialogue
• Algorithmic responsibility
• Individual privacy
• Jobs and workforce transformation
• Safety
• Learn beyond the headlines
• Key: Focus on skills

J. Other issues:
Business models
• Trusted platform
• Training – Unbiased data
• Algorithms - Transparency
• Services - Open API Economy
• Transactions – Blockchain
• Applications – Ethically boosting
creativity and productivity
• Governance – Laws and regulations
• Trust takes time
• Steam engines – boiler explosions
• Cognitive engines – headline hype

Some reactions…
• aitrends
• Artificial Brilliance
• Futurism
• InformationWeek
• Calburn: “IBM: AI Should Stand For
‘Augmented Intelligence’
• PYMNTS
• TechCrunch
• Coldewey: “The White House
requested input on artificial
intelligence, and IBM’s response is a
great AI 101”

White House OSTP
Follow Up
• The White House OSTP received
161 responses and created a 349
downloadable PDF with URL links
• The White House Frontiers
Conference is being planned as a
follow up meeting
• Date: October 13, 2016
• Place: Pittsburgh, PA USA

What types of digital cognitive systems?
• Cognitive Build: Outthink Challenge (250K people)
• Imagine a digital cognitive system to help you do
something important in your personal or professional
lives
• Team to design it and advocate for it, and then everyone
votes
• Winners: reduce waste and human suffering, screen for
health issues and safety threats, learn life skills and make
better choices, find what you are looking for, move
around more effectively, provide emotional support,
provide IT support, learn about important public policy
goals and make better choices
• Types: Tool, Assistant, Collaborator, Coach, Mediator

Types
• Tool
• Assistant
• Collaborator
• Coach
• Mediator

Types: Progression of models and capabilities
Task & World Model/
Planning & Decisions
Self Model/
Capacity & Limits
User Model/
Episodic Memory
Institutions Model/
Trust & Social Acts
Tool + - - -
Assistant ++ + - -
Collaborator +++ ++ + -
Coach ++++ +++ ++ +
Mediator +++++ ++++ +++ ++
tool assistant collaborator coach mediator

Build: 10 million minutes of experience

Build: 2 million minutes of experience

Build:
Hardware < Software < Data < Experience < Transformation

Understand them…

Work with…

Next generation cognitive curriculum

IBM Cloud Bluemix: Watson APIs are growing…
10/4/2016
© IBM UPWard 2016
40
So far (June 2016), 100,000 faculty and students globally given access

IBM Cloud Bluemix: Watson APIs are growing…
10/4/2016
© IBM UPWard 2016
44
So far (June 2016), 100,000 faculty and students globally given access

10/4/2016
© IBM 2015, IBM Upward University Programs Worldwide
accelerating regional development
45
I have…
Have you noticed how the building blocks just
keep getting better?

Learning to program:
My first program
10/4/2016
46
Early Computer Science Class:
Watson Center at Columbia 1945
Jim Spohrer’s
First Program 1972

Brief History
of AI
• 1956 – Dartmouth Conference
• 1956 – 1981 Micro-Worlds
• 1981 – Japanese 5th Generation
• 1988 – Expert Systems Peak
• 1990 – AI Winter
• 1997 – Deep Blue
• 1997 – 2011 Real-World
• 2011 – Jeopardy! & SIRI
• 2013 – Cognitive Systems Institute
• 2014 – Watson Business Unit &
• True North Brain Chip
• 2015 – “Cognition as a Service”
on IBM Bluemix
10/4/2016
47

10/4/2016 48
1955 1975 1995 2015 2035 2055
Can better service help us be wiser?
Cognitive Mediator (2035): Tool, Assistant, Collaborator, Coach

Computing: Then, Now, Projected
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2035
2055

10/4/2016
50

10/4/2016
51

What exists in 2016?
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54
360,000 100,000 120,000 60,000 150,000

How fast is Artificial Intelligence approaching?
10/4/2016 55
What might it look like?

Jim Spohrer (IBM)
Seoul, South Korea; October 13, 2016
Consulting Conference
http://www.slideshare.net/spohrer/korea-day1-keynote-20161013-v6
10/4/2016 56
Come visit IBM Research – Almaden
in San Jose, CA USA – monthly university day!

10/4/2016
57

Dedication: Douglas C. Engelbart
Father of the mouse and augmentation theory
10/4/2016
58

Korea day1 keynote 20161013 v6

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Korea day1 keynote 20161013 v6