Nsf 20180124 v18

Jim Spohrer (IBM)
NSF Visit – Alexandria, VA
Wednesday January 24, 2018
http://www.slideshare.net/spohrer/nsf-20180124-v18
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The Future of AI and Education:
Measuring Progress and Preparing

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Time for educators and researchers
too…
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Social Emotional Skills - Empathy
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IBM Research, Patents, Data, Cognitive
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1/24/2018 Understanding Cognitive Systems 6

TED Arai Todai Robot
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… when will
your smartphone
be smart enough to
pass a university
entrance exam?

Questions
• What is the timeline for solving AI and IA?
• Who are the leaders driving AI progress?
• What will the biggest benefits from AI be?
• What are the biggest risks associated with AI, and
are they real?
• What other technologies may have a bigger
impact than AI?
• What are the implications for stakeholders?
• How should we prepare to get the benefits and
avoid the risks?

Every 20 years, compute costs are down
by 1000x
• Cost of Digital Workers
– Moore’s Law can be thought of as
lowering costs by a factor of a…
• Thousand times lower
in 20 years
• Million times lower
in 40 years
• Billion times lower
in 60 years
• Smarter Tools (Terascale)
– Terascale (2017) = $3K
– Terascale (2020) = ~$1K
• Narrow Worker (Petascale)
– Recognition (Fast)
– Petascale (2040) = ~$1K
• Broad Worker (Exascale)
– Reasoning (Slow)
– Exascale (2060) = ~$1K
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2080204020001960
$1K
$1M
$1B
$1T
206020201980
+/- 10 years
$1
Person Average
Annual Salary
(Living Income)
Super Computer
Cost
Mainframe Cost
Smartphone Cost
T
P
E
T P E
AI Progress on Open Leaderboards
Benchmark Roadmap to solve AI/IA

GPD/Employee
(Source)
Lower compute costs translate into increasing productivity and GDP/employees for nations
Increasing productivity and GDP/employees should translate into wealthier citizens
AI Progress on Open Leaderboards
Benchmark Roadmap to solve AI/IA

Leaderboards Framework
AI Progress on Open Leaderboards - Benchmark Roadmap
Perceive World Develop Cognition Build Relationships Fill Roles
Pattern
recognition
Video
understanding
Memory Reasoning Social
interactions
Fluent
conversation
Assistant &
Collaborator
Coach &
Mediator
Speech Actions Declarative Deduction Scripts Speech Acts Tasks Institutions
Chime Thumos SQuAD SAT ROC Story ConvAI
Images Context Episodic Induction Plans Intentions Summarizatio
n
Values
ImageNet VQA DSTC RALI General-AI
Translation Narration Dynamic Abductive Goals Cultures Debate Negotiation
WMT DeepVideo Alexa Prize ICCMA AT
Learning from Labeled Training Data and Searching (Optimization)
Learning by Watching and Reading (Education)
Learning by Doing and being Responsible (Exploration)
2015 2018 2021 2024 2027 2030 2033 2036
Which experts would be really surprised if it takes less time… and which experts really surprised if it takes longer?
Approx.
Year
Human
Level ->

Icons of AI
Progress
• 1956: Dartmouth Conference
organized by:
– John McCarthy (Dartmouth, later
Stanford)
– Marvin Minsky (MIT)
– and two senior scientists:
• Claude Shannon (Bell Labs)
• Nathan Rochester (IBM)
• 1997: Deep Blue (IBM) - Chess
• 2011: Watson Jeopardy! (IBM)
• 2016: AlphaGo (Google DeepMinds)

AI Trends
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Dota 2
“Deep Learning” for
“AI Pattern Recognition”
depends on massive
amounts of “labeled data”
and computing power
available since ~2012;
Labeled data is simply
input and output pairs,
such as a sound and word,
or image and word, or
English sentence and French
sentence, or road scene
and car control settings –
labeled data means having
both input and output data
in massive quantities.
For example, 100K images
of skin, half with skin
cancer and half without to
learn to recognize presence
of skin cancer.

AI Leaders
• Who is winning?
– Regions China vs USA vs EU vs ROW
– Companies Microsoft vs Google vs IBM
• Leaderboards
– SQuAD – Question Answering
– EFF Measuring AI Progress

AI to IA Timeline: Hard unsolved AI
problems
• 2012-2017 AI Pattern Recognition and
Learning from Massive Labeled Data
– Speech, image, translation, driverless, games
– Chatbots as digital assistants
• 2018 Video Understanding
• 2021 Episodic Memory
• 2022 Learning from Watching
• 2024 Commonsense Reasoning
• 2026 Learning from Reading
• 2028 Learning from Doing
• 2030 Fluent Conversation
• 2031-2039 Cognitive Collaborator and
Mediator; Intelligence Augmentation (IA)

AI Benefits
• Access to expertise
– “Insanely great” labor productivity for trusted
service providers
– Digital workers for healthcare, education, finance,
etc.
• Better choices
– ”Insanely great” collaborations with others on
what matters most
– AI for IA = Augmented Intelligence and higher
value co-creation interactions

AI Risks
• Job Loss
– Shorter term
bigger risk
= de-skilling
• Super-intelligence
– Shorter term
bigger risk
= bad actors

Other Technologies: Bigger impact?
Yes.
• Augmented Reality (AR)/
Virtual Reality (VR)
– Game worlds
grow-up
• Blockchain/
Security Systems
– Trust and security
immutable
• Advanced Materials/
Energy Systems
– Manufacturing as cheap,
local recycling service
(utility fog, artificial leaf, etc.)

Stakeholders
• Individuals
• Families
• Businesses and
other Organizations
• Industry Groups
• Regional
Governments:
– Cities
– States
– Nations

Be Prepared
• Understand open AI code + data +
models + stacks + communities
– Leaderboards
– Ethical conduct
• Learn 3 R’s of IBM’s Cognitive
Opentech Group (COG)
– Read arXiv
– Redo with Github
– Report with Jupyter notebooks on
DSX and/or leaderboards
• Improve your team’s skills of rapidly
rebuilding from scratch
– Build your open code eminence
– Understand open innovation
– Communities + Leaderboards
1972 used
Punch cards
2016 used
IBM Watson
Open APIs to win…

Cupertino Teens
• IBM Watson on Bluemix
AI for NLP
entity identification

Courses
• 2015
– “How to build a cognitive system for Q&A task.”
– 9 months to 40% question answering accuracy
– 1-2 years for 90% accuracy, which questions to reject
• 2025
– “How to use a cognitive system to be a better professional X.”
– Tools to build a student level Q&A from textbook in 1 week
• 2035
– “How to use your cognitive mediator to build a startup.”
– Tools to build faculty level Q&A for textbook in one day
– Cognitive mediator knows a person better than they know themselves
• 2055
– “How to manage your workforce of digital workers.”
– Most people have 100 digital workers.
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Take free online cognitive classes today at cognitiveclass.ai

Headlines
• 2017 Popular
– “AI vs People”
– “X-Y team up to invest big in AI”
• 2025 Commonplace
– “People using AI to become better at their
professions, serving others.”
– “Teenagers using AI to solve challenges,
and improve their communities.”
• 2085 Resilience
– “Teams competing to rapidly rebuild
socio-economic-technical systems (wise
service systems) from scratch”
– “U.N. Pluto-base makes major discovery
about nature of universe. U.F.P.
established.”
IEEE 2017

IBM-MIT $240M over 10 year AI
mission

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Programs Worldwide accelerating regional
development
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I have…
Have you noticed how the building
blocks just keep getting better?

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

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Fast Forward 2016:
Consider this…

Microsoft CaptionBot June 19, 2016
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Microsoft CaptionBot June 20, 2016
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IBM Image Tagging
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Today: November 10, 2017
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IBM

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Cognitive Mediators
for all people in all roles

Occupations = Many Tasks
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Watson Discovery Advisor
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34
Simonite, T. 2014. Software Mines Science Papers to Make New Discoveries. MIT. November 25, 2014.
URL: http://m.technologyreview.com/news/520461/software-mines-science-papers-to-make-new-discoveries/

Measuring AI Progress
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AI Trends
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1955 1975 1995 2015 2035 2055
Can better service help us be wiser?
Cognitive Mediator (2035): Tool, Assistant, Collaborator, Coach

Courses
2015
– “How to build a cognitive system for Q&A task.”
– 9 months to 40% question answering accuracy
– 1-2 years for 90% accuracy, which questions to reject
2025
– “How to use a cognitive system to be a better professional X.”
– Tools to build a student level Q&A from textbook in 1 week
2035
– “How to use your cognitive mediator to build a startup.”
– Tools to build faculty level Q&A for textbook in one day
– Cognitive mediator knows a person better than they know themselves
2055
– “How to manage your workforce of digital workers.”
– Most people have 100 digital workers.
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Computing: Then, Now, Projected
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2035
2055

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Build: 10 million minutes of experience

Build:
Hardware < Software < Data < Experience < Transformation

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

“The best way to predict the future is to inspire the
next generation of students to build it better”
Digital Natives Transportation Water Manufacturing
Energy Construction ICT Retail
Finance Healthcare Education Government

User Models
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$5M Prize
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“AI will change the world?
Who will change AI?”

“These amazing technologies must be
able to help people like myself…”

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Future of Skills

Future-Ready T-Shapes
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In Summary
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“A service science
perspective considers
the evolving ecology of
service system entities,
their value co-creation and
capability co-elevation
interactions, and their
capabilities, constraints,
rights, and responsibilities.”
Cognitive Systems
Entities
Service
Systems
Entities With
Cognitive
Mediators
Add Rights &
Responsibilities

Good science = Reproducibility

In Conclusion
• Hundreds of AI Challenge Leaderboards
exist and the number is growing
• Can one system be built to do them all?
See: https://www.youtube.com/watch?v=8FpdEmySsuc

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accelerating regional development
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accelerating regional development
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You say you want a
revolution?
October 8, 2017
https://www.slideshare.net/spohrer/revolution-20171008-v23
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By 2035, T-Shaped Makers with great
Building Blocks and Cognitive Mediators
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Empathy & Teamwork
sector
region/culture
discipline
Depth
Breadth
STEM
Liberal Arts

In Summary
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Cognitive Systems
Entities
Service
Systems
Entities With
Cognitive
Mediators
Add Rights &
Responsibilities

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Machine
Learning
Natural
Language
Processing
High
Performance
Computing
Knowledge
Representation
and Reasoning
Question
Answering
Unstructured
Information

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
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Definitions: AI vs IA
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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)”
Cognition as a Service (CaaS):
AI building blocks for IA solutions

Augmenting Workers

Startup
Companies

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I have…
Have you noticed how the building
blocks just keep getting better?

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

Societal Grand Challenges
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Solving these would mean we are smarter,
but would they mean we are wiser?

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High School Senior: Anish Krishnan
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IBM in Silicon Valley:
From Punch Cards….
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On August 22, 1943, 105 men, women and children,
among them 43 IBM employees, alighted from a special
train that carried them across the continent to establish
new homes and the new IBM Card Manufacturing Plant
Number 5 at 16th and St. John Streets, San Jose, CA.

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IBM in Silicon Valley:
To Brain Chips….
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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/
Self Capacity & Limits
User Model/
User’s Episodic Memory and Identity
Institutions Model/
Trust & Social Acts
Tool + - - -
Assistant ++ + - -
Collaborator +++ ++ + -
Coach ++++ +++ ++ +
Mediator +++++ ++++ +++ ++
tool assistant collaborator coach mediator

Partnership for AI formed

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What might Reality 2.0 look like?

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How fast is Reality 2.0 approaching?
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What might it look like?

Reality 2.0 Service Platform:
polite cognitive mediators (CM1,CM2)
do not interrupt people (P1,P2)
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Service Platform
CM2
P2
CM1
P1
100x
100x 100x

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Wise Service System:
All entities’ in network
use cognitive mediators
to enhance
value co-creation interactions
Cognitive Mediators:
Cognitive systems
with deep knowledge of both
customer (user) and provider (expert)
as co-creators of win-win value
Entity augmentation boosts both creativity and productivity of interactions

Two assertions
• Machines seem to be getting smarter fast.
– Agree/disagree?
• People do not seem to be getting wiser fast.
– Agree/disagree?
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Homo Sapiens means Wise Man: True/False?

IBM Cloud Bluemix:
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What is Industry 4.0?
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History of the idea: Mirror Worlds
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Why is this relevant?

I am still very skeptical…
but tell me more….
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Managers: Courage Required….
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Talent required, but…
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Industry 4.0
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CyberPhysical Systems?
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Industry 4.0
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Yesterday: Servitization
• Rolls Royce: “Power By The Hour”

Tomorrow: Servitization
• Start with any traditional product that is sold to customers
• Make the product part of a smart/wise service system
– Instrument it (sensors) – Internet of Things/Everything
– Set-up an intelligent operation center to monitor all products’
performance across their life-cycles
– Use big data analytics to determine how to improve product
performance, efficiency, maintenance, etc.
– Offer customer the “product-performance-as-a-service” with
financing/Internet of Service
– Customer benefits from cost-savings, predictability
– Provider benefits margin-improvements, predictability
• Every product becomes a platform technology (a vehicle for
service innovation) for innovative university startups

Vision: MMaaRRSS
• Modular Manufacturing as a Regional
Recirculation Service System
– “I am the stuff that will be made into product X for
customer Y.”
– Stuff = Material, Energy, and Information Flows
– Minimize transport costs (for products and waste)
• The Vision: Circular Economy (~4 minutes)

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Explain external
phenomena

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Explain internal
phenomena

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Explain
value co-creation
phenomena

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Physics Chemistry Biology
Neuroscience Psychology Artificial
Intelligence
Engineering Management Public
Policy
Education Design Humanities
Natural Systems
Cognitive Systems
Service Systems

Sciences provide…
• Frameworks for people to ask and answer
questions systematically
• Explanations with instructions on “how to re-do”
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Kline: Conceptual Foundation of Multidisciplinary Thinking -
“To our children and children’s children,
to whom we elders owe an explanation of the world
that is understandable, realistic, forward-looking, and whole.”
Proenneke:
Alone in the Wilderness -
To do a thorough testing,
should each generation
be required to rapidly rebuild
from scratch?
A re-makers movement?

Some paths to becoming 64x smarter:
Improving learning and performance
• 2x from Learning sciences (methods)
– Better models of concepts
– Better models of learners
• 2x from Learning technology (tools)
– Guided learning paths
– Elimination of “thrashing”
• 2x from Quantity effect (overlaps)
– More you know, faster you go
– Advanced organizers
• 2x from Lifelong learning (time)
– Longer lives and longer careers
– Keeps “learning-mode” activated
• 2x from Early learning (time)
– Start earlier: Challenged-based approach
– STEM-2D in K-12 (SSME+DAPP Design of Smart Service Systems)
• 2x from Cognitive systems (performance support)
– Technology & Infrastructure Interactions
– Organizations & Others Interactions

Next Generation:
Future-Ready T-Shaped Adaptive Innovators
Many disciplines
Many sectors
Many regions/cultures
(understanding & communications)
Deepinonesector
Deepinoneregion/culture
Deepinonediscipline

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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
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Cognitive Assistants for all occupations
are beginning to appear
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The Maker Movement &
Open Source Ecology
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Future of Skills

Assisting individuals and organizations
to close their service innovation skills gap
and co-create wiser service systems
empowering employees, customers, citizens
with cognitive mediators
in the collaborative service economy

Dedication: Doug Engelbart
Father of the mouse and
augmentation theory
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1955 1975 1995 2015 2035 2055
Can better service help us be wiser?
Cognitive Mediator (2035): Tool, Assistant, Collaborator, Coach

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Cyber-Social-Learning-Systems
Jim Spohrer (IBM)
August 29, 2016
http://www.slideshare.net/spohrer/csls-20160821-v1
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126

Today’s Talk: Cyber-Social-Learning-
Systems• What is the impact of Artificial Intelligence (AI) on CSLS?
– Augmented Intelligence (IA) via digital cognitive systems
– White House OSTP Response(s)
• Other topics to think about:
– What are more of the implications of digital cognitive systems?
• Tool > Assistant > Collaborator > Coach > Mediator
• Transformation > Experience > Data > Software > Hardware
– What does social intelligence require? Episodic Memory?
– What is the impact of augmented reality on CSLS?
– What are possible connections to service systems science
(SSME+DAPP)?
– What type of adaptive innovator with growth mindset needed
(T-shapes)?

Augmented Intelligence
• Tool
• Assistant
•
Collaborat
or
• Coach
• Mediator

White House OSTP Response(s)
• AI for public good
• Social & economic implications
• Education to harness AI
• Research questions and gaps
• Data sets and model sets
• Multidisciplinary research
• Role of incentives and prizes
• Safety and control protocols
• Legal and governance issues

In Summary
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Cognitive Systems
Entities
Service
Systems
Entities With
Cognitive
Mediators
Add Rights &
Responsibilities

Backup Slides
• Understanding Cognitive Systems

Understanding
Cognitive Systems
Jim Spohrer (IBM), August 25, 2016
CSIG (Cognitive Systems Institute Group) Speaker
Series
http://www.slideshare.net/spohrer/understanding_20
160825_v3
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132

Today’s Talk: Understanding Cognitive
Systems• What is a cognitive system (entity)?
– biological
– technological
– types of digital cognitive systems
• How to…
– build them?
– understand them?
– work with them?
• Steps toward a next generation cognitive
curriculum…

But first…. Cognitive Science, a young
field
• Society
– cognitivesciencesociety.org
• People
– Founders: Roger Schank, Donald Norman,
Allan Collins
– Others: David Rumelhart, Herbert Simon,
Allen Newell
– Today: Patrick Langley, Wayne Gray,
Kenneth Forbus, Ashok Goel, Paul Maglio,
etc.
• Systems Conference
– cogsys.org
– (JCS wishes this was part of HICSS)

Advances in Cognitive Systems -
cogsys.org

Google Search: August 26, 2016

Today’s Talk: Understanding Cognitive
Systems• What is a cognitive system (entity)?
– biological
– technological
– types of digital cognitive systems
• How to…
– build them?
– understand them?
– work with them?
• Steps toward a next generation cognitive
curriculum…

What is a cognitive system (entity)?

What is a digital cognitive system
(entity)?

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
•
Collaborat
or
• 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 +++++ ++++ +++ ++
Cognitive
Tool
Cognitive
Assistant
Cognitive
Collaborator
Cognitive
Coach
Cognitive
Mediator

Build: Hardware < Software < Data <
Experience

Understand them…

Work with…

Next generation cognitive curriculum

Backup slides
• Service systems - http://service-
science.info/archives/3368

What is service science?
• IBM initiated effort to establish a
multidisciplinary field to study
service systems … with a focus on
people-centered, IT-enabled service
innovations for business and society
– based on service-dominant logic
– service = value co-creation
– IT-enabled service architectures
– service systems (socio-technical
systems for win-win value co-creation)
• IBM helped establish
– computer science (1945-present)
– service science (2005-present)
Service systems are dynamic configurations of
resources (people, technology, organizations,
and information) interconnected by
value propositions, internally and externally.
Examples:
- macro: cities, states, nations
- meso: hospitals, universities, businesses
- micro: households, families, individuals
Reference:
Spohrer J, Maglio P, Bailey J, Gruhl D (2007)
Steps toward a science of service systems.
IEEE Computer Society. 40(3):71-77(January).

What is service science?
• Now over 500 universities globally teach a more
multidisciplinary approach to service innovation,
including:
– Service management and marketing
– Service engineering and operations
– Service design and arts
– Service public policy and economics
– Service computing and informatics
• SSME + DAPP =
Service Science Management Engineering +
Design Arts Public Policy
– People, technology, organizations, information
interconnected by value propositions.
Reference:
IfM & IBM (2008). Succeeding through service
innovation: A service perspective for education,
research, business and government.
University of Cambridge Institute for Manufacturing,
Cambridge, UK. 2008.

How to get involved?
• Weekly speaker series
– Service innovation
– Service education & research
– Smart service/cognitive systems
• Discovery summits & book series
• Opportunities
– Institutional memberships
– Leadership & ambassadors
– Volunteer opportunities
– Awards & sponsored
conferences
ISSIP.org is a non-profit society
International Society of Service Innovation Professionals
Membership:
Over 1000 professionals and students from 40+ countries,
50+ companies and 50+ universities.

How to get involved?
• Journals (INFORMS,
etc.)
• Conferences (HICSS,
etc.)
• Courses (MIT, etc.)
• Funding (NSF, etc.)
• Society (ISSIP, etc.)

What are the hot topics?
• Smart Service Systems: Intelligence Augmentation
– AI + AR UX (Artificial Intelligence + Augmented Reality User
Experience)
– Smartphones (mobile, social, secure, etc.)
• Collaborative Economy: Servitization
– From assets to co-creation (e.g., Uber, AirBnB, etc.)
– From product to capability/outcome-as-a-service
– Manufacturing as a local recycling service
• Digital Transformation: Trust and Identity
– Blockchain: Don Tapscott’s TED Talk & book
– Big Data: Service Analytics & HAT (Hub of All Things)

Backups
• T-shaped people

Cognitive Assistants for all occupations
are beginning to appear
1/24/2018
development
159

My Quest
• What is the best bot that anyone can easily
install on their smartphone and laptop today?
1/24/2018
© IBM UPWard 2016
165

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