ahfe hsse 20140722 v3

Educating Service InnovatorsJim Spohrer, IBM

AHFE Human Side of Service EngineeringKrakow, PolandJuly 22, 2014

This presentation with speaker notes is available for download at: http://www.slideshare.net/spohrer/ahfe-hsse-20140722-v3

Waldemar KarwowskiUCFlorida, USA

Gavriel SalvendyPurdue, USA

Tsinghua, China

Lou FreundSJSU, USA

Wojciech CellaryUEPozanan, Poland

Yuriko SawataniWasedaU, Japan

Phil GardnerMSU, USA

Paolo PiciocchiUSolerno, Italy

Clara BassanoUNaples Parthenope, Italy

ISSIP.orgProfessional Development for Service Innovators

• 2015 Conferences– HICSS, Honolulu, HI, Jan 5-8– T Summit, E Lansing, MI, Mar 16-17– ICSERV,San Jose, CA July 6-8– Frontiers, San Jose, CA July 9-12– AHFE HSSE,Las Vegas, NV July 23-27

What is more important than this?

• “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.”– Stephen Jay Kline (1922-1997)– From the dedication of “The Conceptual

Foundations of Multidisciplinary Thinking,” Stanford University Press, 1995.

Kidzania – Systems & Roles

From Prof. Bo Edvardsson HSSE 2014 Plenary Speech

Help transform K-12 STEM Education

“Imagine a better service system, and use STEM language to explain why it is better”STEM = Science, Technology, Engineering, and Mathematics

See Challenge-Based Learning: http://www.nmc.org/news/nmc/nmc-study-confirms-effectiveness-challenge-based-learning

• Challenge-based SSME+DAPP Design of Smart Service Systems– K - Transportation– 1 - Water & Waste Management– 2 - Food & Global Supply Chain– 3 - Energy & Electric Grid– 4 - Info & Comm Tech (ICT) Infrastructure– 5 - Buildings & Construction– 6 - Banking & Finance– 7 - Retail & Hospitality– 8 - Healthcare– 9 - Education (including Universities)– 10 - Government (Cities)– 11 - Government (Regions/States)– 12 - Government (Nations)– Higher Ed – Specific Service Systems– Professional Life – Specific Service Systems

Smarter Planet (SP)Service Systems:

Quality of Life (QoL)depends directly on

Quality of Service (QoS)

Systemsthat govern

Systemsthat enable

healthy, wealthy,and wise people

Systemsthat move, store,harvest, process

Scope – 169 Experts

Scale: Nested, Networked Structure

Types of Service System Entities

04/07/2023© IBM 2013 IBM University Programs

worldwide accelerating regional development (IBM UPward)

http://www.service-science.info/archives/1056

Nation

State/ProvinceCity/Region

UniversityCollege

Cultural &ConferenceHotels

HospitalMedical

Research

Worker(professional)

Family(household)

For-profits:Business Entrepreneurship

Non-profitsSocial Entrepreneurship

U-BEEJob Creator/Sustainer

U-BEEs = University-Based Entrepreneurial Ecosystems

“The future is already here (at universities),it is just not evenlydistributed.”

“The best way topredict the futureis to (inspire the nextgeneration of studentsto) build it better.”

“Multilevel nested, networked holistic service systems (HSS) that provision whole service (WS) tothe people inside them. WS includes flows (transportation, water, food, energy, communications), development (buildings, retail ,finance, health, education), and governance (city, state, nation). ”

University Four Missions1. Learning2. Discovery3. Engagement4. Convergence

Entities (Actors) as Service Systems

Economics

Marketing

Computer Science

Operations

Supply Chain Management

Management Science

Design

“service science isthe transdisciplinary study of

service systems &value co-creation”

“a service system isa human-made system to improve

provider-customer interactionsand value co-creation outcomes,

studied by many disciplines,one piece at a time.”

Systems Engineering

Systems Sciences

Psychology

Political Sciences

Management

FinanceLawInformation

Systems

Information Systems

Cognitive Scienceand many others…

Maglio, P. P., Vargo, S. L., Caswell, N., & Spohrer, J. (2009). The service system is the basic abstraction of service science. Information Systems and e-business Management, 7(4), 395-406.

Next Generation:T-Shaped Adaptive Innovators

Many disciplinesMany sectors

Many regions/cultures(understanding & communications)

Deep in one sector

Deep in one region/culture

Deep in one discipline

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

What are the (system) trends?

Digital ImmigrantBorn: 1988

Graduated College with PhD: 2014

Digital NativeBorn: 2014

Enters College: 2032

Transportation: Self-driving cars

Water: Circular Economy

Manufacturing: Circular EconomyBaxter: Building the Future

Maker-Bot: Replicator 2

Energy: Artificial Leaf

Technology: Cognitive Computing

Example: Leading Through Connections with…Universities Collaborate with IBM Research to Design Watson for the Grand Challenge of Jeopardy !

Assisted in the development of the Open Advancement of Question-Answering Initiative (OAQA) architecture and methodology

Pioneered an online natural language question answering system called START, which provided the ability to answer questions with high precision using information from semi-structured and structured information repositories

Worked to extend the capabilities of Watson, with a focus on extensive common sense knowledge

Focused on large-scale information extraction, parsing, and knowledge inference technologies

Worked on a visualization component to visually explain to external audiences the massively parallel analytics skills it takes for the Watson computing system to break down a question and formulate a rapid and accurate response to rival a human brain

Provided technological advancement enabling a computing system to remember the full interaction, rather than treating every question like the first one - simulating a real dialogue

Explored advanced machine learning techniques along with rich text representations based on syntactic and semantic structures for the Watson’s optimization

Worked on information retrieval and text search technologies

http://w3.ibm.com/news/w3news/top_stories/2011/02/chq_watson_wrapup.html

New Era of Computing:Cognitive Technologies & Componentry

Natural Language– Reasoning, Logic & Planning– Symbolic Processing– Natural Language Processing– Ranking of Hypotheses– Knowledge Representations– Domain-Specific Ontologies– Information Storage/Retrieval– Machine Learning, Reasoning– Von Neumann Componentry– OpenPOWER Systems

Pattern Recognition– Recognition, Sensing & Acting– Pattern Processing– Image & Speech Processing– Ranking of Hypotheses– Pattern Representations– Domain-Specific Neural Nets– Information Storage/Retrieval– Machine Learning, Perception– Neuromorphic Componentry– SyNAPSE Systems

AI for IA: Intelligence Augmentation

Cognitive Systemsthat boost learning,discovery, engagement, transformation, and long-range planning.

Cognition as a Service

Buildings: Circular EconomyChina Broad Group:30 Stories in 15 Days

Retail & Hospitality: Social Media

Finance: Crowd Funding

Health: Robotics & 3D Printing

Education: Challenge-Based Sport

Government: Parameterized Meta-Rules

• Innovativeness

• Equity– Improve

weakestlink

• Sustainability

• Resiliency

Competitive Parity – Achieved.• The NFL touts parity—the idea

that any team can win on any given Sunday. But this year, parity has truly run wild.

• Through six weeks, 11 of the NFL's 32 teams are 3-3.

• The Journal asked the statistical gurus of Massey-Peabody Analytics to run a coin-flip simulation…

2030 and Beyond…. Government, Health, Education, Finance, etc.

Welcome to the new age ofplatform technologies and

smarter service systems for every sector of business and society

nested, networks systems

“Cognitive Sport” Collaborations

Academics• Do your courses require team projects?• Are the projects real-world open

innovation challenges? Real-world data? Real-world tools?

• Are student teams multi-disciplinary?

• Are industry coaches involved?• Do faculty have multiple industry

relationships? Multiple years?

Industry• Do your employees’ annual evaluations

include coaching student team projects?• Do you provide real-world open

innovation challenges? Real-world data? Real-world tools?

• Do the best students get internships?• Do the best interns get jobs?• Do faculty relationships span multiple

years/cohorts of students?

Concepts

S-D Logic

Evolving Ecology of Entities-Interactions-Outcomes

Types of Structure

Why now?

Dynamics: Changing Rules

Dynamics: Changing Values

Service science offers fresh perspective to reorient the debate onwhat is ‘progress’ and whether or not it is slowing down, and if so, what might be done to reframe progress ‘at the speed limit of what is possible’ with universities.

Next Generation

Come visit!

IBM Research – Almaden, San Jose, CAspohrer@us.ibm.com

Entities (Actors) as Resource Integrators

Entities (Actors) as Institutions

Ostrom

Framework Ontology Logic Language

Theory Epistemology “Lawful” Learning

Model Axiology Likeness Levels

• A set of designed constraints imposed on human interactions for a purpose (desired outcomes)

• “Lawful”– Entities– Interaction– Outcomes

ISPAR: Interactions & Outcomes

Maglio, P. P., Vargo, S. L., Caswell, N., & Spohrer, J. (2009). The service system is the basic abstraction of service science. Information Systems and e-business Management, 7(4), 395-406.

Drivers shaping service phenomena

• Global economic change• ICT-enablement or technology change• Outsourcing• Business model change (value migration)• Where people live (demographic change)• How long people live• The nature of family life• A rising education level• A rising dependence on universities• A rising dependence on non-profit organizations

QuestionsThis view leads to a new set of questions for service scientists to answer, about the nature of entities, interactions, outcomes, and their dynamics over time.• What types of entities are capable of service interactions?• What types of interactions do service system entities engage in?• What types of outcomes can result when service system entities interact?• How do the types of entities and interactions change over time?• How do the spatial distributions of types of entities change over time?• How do the hierarchical structure and network relationships of entities

change over time?• How do the knowledge, competencies, resources owned and accessed by

the entities change over time?

A tableau of primitive economic activities

{P,D,C,R}P|{D,C,R} {P,D}|{C,R} {P,D,C}|R {P,D}|C|R {P,C}|{D,R}{P,C}|D|R {P,R}|{D,C} {P,R}|D|C D|{P,C,R}C|{P,D,R} R|{P,D,C}P|D|C|R{P,D,C,R}P|{D,C,R}{P,D}|{C,R}{P,D,C}|R{P,D}|C|R{P,C}|{D,R}{P,C}|D|R{P,R}|{D,C}{P,R}|D|CD|{P,C,R}C|{P,D,R}R|{P,D,C}P|D|C|R

P Production D Distribution C Consumption R Recycling

Jointness {} Separation |

169 possible patterns of service system interactions, time, space, and scale. For example, energy generation at home, city, state, national levels. For example, local to global to local again (e.g., circular economy).

Based on: Betancourt, R., & Gautschi, D. (2001). Product innovation in services: A framework for analysis. Advances in Applied Microeconomics, 10, 155-183.

Value Co-Creation Processservice systems

(market and business strategy)

resources(people,

technology, information,

organizations)

dynamically configure

access rights(own,

leased, shared,

privileged)

stakeholders(customers, providers, authorities,

competitors)

value propositions

have Interactions(person-to-person, system-to-system, person-to-system,system-to-person)

outcomes(lose-win,win-win,

lose-lose,win-lose)

develop

coordinate/ motivate

measures (quality,

productivity, compliance, sustainable innovation,

others)

establish

impacted

impact

generate

enable

win-win value-cocreation

services (business processes,

architecture and infrastructure

services)

execute

Demirkan, H & Spohrer, J (2014) “Understanding Service Systems & Innovations in Time-Space Complexity: The Abstract-Entity-Interaction-Outcome-Universals Theory,” Working Paper.

Intuitive Examples:Entities-Interactions-Outcomes

Domain Entities Pattern

Physics Atoms fission, fusion, reactions

Physics Celestial Bodies orbit, collide, sling shot

Chemistry Molecules equilibrium, reactions

Biology Organisms mutualism, predator-prey

Business Firms exchange, divest, merge

Government Nations trade, dissolution, annex

Six questions

Question DescriptionDoes the entity still exist after the interaction?

Some interactions do or do not preserve (conserve) entities.

Does the interaction giver rise to new entities?

Some interactions do or do not give rise to new entities.

Does the interaction change the state of the entities?

Some interactions do or do not change an entity’s state.

Does the state change include a record of the interaction?

Some entities can and some cannot record interaction histories.

Does the state change include a process-of-valuing the outcome?

Some entities can and some cannot estimate value of outcomes.

Does the state change include the result of simulating other entities?

Some entities can and some cannot simulate other entities valuing.

What is meant by “lawful”

• Physical interaction laws do not change*– However, innovations change the costs– Intel, IBM, OpenPOWER (computing costs)– AT&T, Corning, Cisco (communications costs)

• Social interaction laws do change– And innovations change the costs– Google (Internet search) and copyright– Uber (ride sharing) and taxi regulations– Airbnb (home sharing) and rental regulations

* = of course, our understanding of physical laws does change, other caveats apply.

Do any social interaction laws not change? Yes, mathematical truths!

• Ricardo – Law of Comparative Advantage– Do a little more of what you do best (low cost)– Do a little less of what you do least well (high cost)– Learning curve effects in people, businesses,

countries (interaction can be mutually beneficial)• Assumptions (On when to specialize…)

– Entities can do multiple things at variable costs– Learning interaction is not zero cost transfer

Dynamics: Changing Roles

In Sum, The Quest

• Service science to better understand the laws of service that can inform systematic service innovation– Get the conceptual foundations right– Not unlike “Factory Physics” quest

• Articulate a “Moore’s Law” of service system scaling– Investments that lead to sustainable and resilient

value co-creation and capability co-elevation

AbstractEntity-Interaction-Outcome

Universals• When entities interact, what are the logically

possible outcomes?• For example:

– Game Theory: Win-Win, Lose-Lose, Win-Lose, Lose-Win

– Pi-Calculus: Set of rules for agents-processes-channels to model and reason about complex systems (cell to city)

– Service Science: ISPAR, Ecology, etc.

From Biological to Organizational Ecology: Populations of Entities-Interactions-Outcomes

Populations of Entities Evolving

Service science transdisciplinary framework

SYSTEMS

DISCIPLINEStransportation & supply chain

water & waste

food & products

energy & electricity

ICT & cloud

building & construction

retail & hospitality

banking & finance

healthcare & family

education & work

city secure

state scale nation laws

behavioral sciencese.g., marketing

management sciencee.g., operations

political sciencese.g., public policylearning sciences

e.g., game theory & strategy

cognitive sciencese.g., psychologysystem sciences

e.g., industrial engineeringinformation sciences

e.g., computer scienceorganization sciences

e.g., knowledge managementsocial sciencese.g., econ & law

decision sciencese.g., stats & design

run professionse.g., knowledge worker

transform professions

e.g., consultant

innovate professionse.g., entrepreneurs

changevalue

technology

information

organizations

transform (copy)

systems that govern

stakeholdersresources

customer

provider

authority

competitors

people

Innovate (invent)

history (data analytics)

future (roadmap)

systems that focus on flows of things systems that support people's activities

Observing the stakeholders (As-Is)

Change Potential: Thinking (Has-Been & Might-Become)

Observing their Resources & Access (As-Is)

Value Realization: Doing (To-Be)

A New Era of Smart Systems• Cognitive systems allow us to do more and dream

bigger, boosting both productivity and creativity

How many cognitive systems?

• Are you using cognitive systems yet?

Non-Zero is a deep principle

• Service Definition – Win-win (Non-Zero Sum)– Informal: Knowledge application for mutual benefits– Formal: Value co-creation and capability co-elevation– Context: Abstract-Entity-Interaction-Outcome-Universals

(AEIOU) [Evolving Ecology of Nested-Networked Service System Entities]

• Service Science in Brief (How to integrate…)– An emerging transdiscipline that borrows from

all disciplines without replacing any of them– Short for Service Science, Management, Engineering, plus

Design, Arts, Public Policy (SSME+DAPP)

Early Motivations (Aspiration 1)

Ten Reasons• Universities are complex service systems of fundamental importance.• Disciplines are infusing service innovation concepts into curriculum.• Service science can help universities overcome discipline silos.• University-based startups are often new types of online service.• Professional associations are adding service science SIGs.• Cities, home to most universities, are complex service systems.• Service failures can be costly and can derail the careers of students.• Service science can help universities move up in rankings.• Service science can contribute to good industry-university relations

and interactions.• Service science can help all universities improve their service

excellence "game.”

Higher Education: Five Trends

• Revenue from key sources is continuing to fall, putting many institutions at severe financial risk.

• Demands are rising for a greater return on investment in higher education.

• Greater transparency about student outcomes is becoming the norm.

• New business and delivery models are gaining traction.

• The globalization of education is accelerating.

Higher Education Business Model• Who do we serve, and what are they trying to do?• How do we help those we intend to serve do what they are trying to do?• How do we deliver our services to those we are trying to serve?• What is the nature of the relationship we have with those we serve?• How do these prior components translate into revenue for our institution?• What are the key activities that create the services we provide?• What are the key resources we need to create the services we provide?• Who are the key partners that help us create the services we provide to

those we serve?• How do the key partners, resources, and activities translate into our

institution's cost model?Denna, E. (2014) The Business Model of Higher Education. ViewPoint.EDUCAUSE Review. March 24, 2014. URL: http://www.educause.edu/ero/article/business-model-higher-education

IT Solutions• Administrative solutions for education• Asset management for education• Campus solutions for higher education• Classroom solutions for education• Data and analytics for Smarter Education• Enterprise risk management for higher education• Framework for smarter education• Academic performance and insights• Business analytics software for education• VCL solutions for cloud• Innovation in research• School solutions

What is Service Science?

• Early motivations & aspirations

• Six principles, concepts, scope

• Growing literature• Service-Dominant Logic• In sum, service science

Early Motivations (Growth 1)

Early Motivations (Convergence)

The Elephant in the Room

Growing literature

HAT: Hub-of-All-Things• The HAT project’s impact on policy lies in informing current policies on

personal data privacy and legal issues. By creating a platform for ‘digital labour’, we aim to demonstrate how markets could be created from incentivising more digital visibility in return for offerings to serve lived lives.

Innovation (Rick Miller, Olin)

Gartner Maverick Report

• Control– Institutions– Individuals

• Autonomy– Low– High

From:Surviving the Rise of 'Smart Machines,' the Loss of 'Dream Jobs' and '90% Unemployment.

AI Will Disrupt Higher Education• Our next move: My [Dr. Dyens deputy provost McGill University] proposal

is to think of chess as an analogy for education.

• Gary Kasparov, in the New York Review of Books… wrote:

• The surprise came at the conclusion of the event. The winner was revealed to be not a grandmaster with a state-of-the-art PC but a pair of amateur American chess players using three computers at the same time. Their skill at manipulating and “coaching” their computers to look very deeply into positions effectively counteracted the superior chess understanding of their grandmaster opponents and the greater computational power of other participants. Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process.

Universities Matter #1

ChinaGermany

France

United KingdomItaly

Russia SpainBrazilCanada

IndiaMexico AustraliaSouth Korea

NetherlandsTurkey

Sweden

y = 0,7489x + 0,3534R² = 0,719

0 1 2 3 4 5 6 7 8 9

% top 500 universities

Nation’s % WW GDP and % Top 500 Universities (2009 Data)

…But it can be costly, American student loan debt is over $900M

“When we combined the impact of Harvard’s direct spending on payroll, purchasing and construction – the indirect impact of University spending – and the direct and indirect impact of off-campus spending by Harvard students – we can estimate that Harvard directly and indirectly accounted for nearly $4.8 billion in economic activity in the Boston area in fiscal year 2008, and more than 44,000 jobs.”

Nation

State/ProvinceCity/Region

UniversityCollege

Cultural &ConferenceHotels

HospitalMedical

Research

Worker(professional)

Family(household)

For-profits:Business Entrepreneurship

Non-profitsSocial Entrepreneurship

U-BEEJob Creator/Sustainer

U-BEEs = University-Based Entrepreneurial Ecosystems

“The future is already here (at universities),it is just not evenlydistributed.”

“The best way topredict the futureis to (inspire the nextgeneration of studentsto) build it better.”

“Multilevel nested, networked holistic service systems (HSS) that provision whole service (WS) tothe people inside them. WS includes flows (transportation, water, food, energy, communications), development (buildings, retail ,finance, health, education), and governance (city, state, nation). ”

University Four Missions1. Learning2. Discovery3. Engagement4. Convergence

Reimagining Higher Education

• “Universities weren’t designed to change curricula and introduce new classes at the pace required by changing industry requirements.” – Dennis Yang, president and chief operating officer of Udemy

Example

Trading Zone:Economist, Policymakers & Service Scientists

Future of higher education(one possible path & assumptions)

Years Change – Possible Progress Path Service Science Aspect

0-5 Revenue Continuous Improvements Data Science & Cloud

5-10 Learning Continuous Improvement Organization Science

10-15 Engagement Continuous Improvement Economic Science

15-20 Discovery Continuous Improvements Cognitive Science

Four Missions Four Types of Costs Service Science Aspect

Learning/Teaching & Lectures Knowledge Transfer Specialization

Discovery/Research Knowledge Creation Specialization

Engagement/Entrepreneurship & Employment

Knowledge Application Integration

Convergence/Consilience Knowledge Integration Integration

Backup: Readings (some details)• Spohrer, J., Fodell, D., & Murphy, W. (2012). Ten Reasons Service Science Matters to Universities. Educause Review, 47(6), 52-64.• Lusch, R., & Wu, C. (2012). A service science perspective on higher education—Linking service productivity theory and higher education

reform. Center for American Progress, August.• Denna, E. (2014) The Business Model of Higher Education. Educause ViewPoint. March 24, 2014.• Henry, T, Pagano, E, Puckett, J, Wilson, J (2014) Five Trends to Watch in Higher Education. BCG Perspectives.• Meeker, M (2014) Internet Trends 2014 – Code Conference• Sledge, L & Dovey-Fishman, T (2014) Reimagining higher education: How colleges, universities, businesses, and governments can prepare for a

new age of lifelong learning. Deloitte University Press. • IBM (2014) Education for a Smarter Planet• Goldbloom, A (2011) Making data science a sport. O’Reilly Media Strata Conference. • Johnson, RC (2013) IBM Unveils Cognitive Systems Institute. EETimes. October 3, 2013.• MSU & IBM (2014) T-Summit 2014: Cultivating Tomorrow’s Talent Today. Website & Conferences.• Spohrer J (2014) 21C Talent and 21C Citizens. Service Science Community Website Blog Post Entry.• Dyens, O (2014) How artificial intelligence is about to disrupt higher education. UA/AU University Affairs Affaires universitaires. April 30,

2014.• Kenneth F. Brant , KF, Gupta, A, Sommer, D (2013) Maverick* Research: Surviving the Rise of 'Smart Machines,' the Loss of 'Dream Jobs' and

'90% Unemployment.’• Spohrer, J., Giuiusa, A., & Demirkan, H. (2013). Service science: reframing progress with universities. Systems Research and Behavioral Science,

30(5), 561-569. • Pentland, A. (2014). Social Physics: How Good Ideas Spread-The Lessons from a New Science. Penguin.• Moore, GA (2012) Escape Velocity: Free Your Company’s Future From The Pull Of The Past. Harper Business.• Florida, R (2009) Who’s Your City? Basic Books.• Ng, Irene (2013) Hat: Hub-of-All-Things website. Research Councils UK (RCUK) Digital Economy.• Carmichael, A (2011) Announcing: The Complete QS Guide to Self Tracking. Quantified Self website. January 12, 2011.• Board of Life Science (2014) Convergence: Facilitating Transdisciplinary Integration of Life Science, Physical Sciences, Engineering, and Beyond.

Internet Trends 2014

Industry Transformation

Donald Clark, TEDxGlasgow

Kaggle: Making Data Science a Sport(146 competitions)

Cognitive Systems

T-Shaped Talent• Academia Optimizes

– I for individual work– Individual IQ– Disciplines

• Business Optimizes– T for team work– Team IQ– Systems

• Both Important– Depth & Breadth – Disciplines & Systems

University & Industry Score Card• do your annual performance evaluations for your

employees include coaching student teams? • do the coached team projects have

multidisciplinary participants? • do the coached team projects include industry

participants from diverse sectors• do the coached team projects have multicultural

participants? • do the coached team projects focus on real

world challenges to improve local systems? • what percentage of your customer offerings

change every year? • do new offerings highlight new research finding

from journals that highlight new knowledge? • do new offerings highlight new entrepreneurial

ecosystem partners, applying new knowledge to create value?

• do new offerings and team projects build the social networks of your employees?

• do your courses include team projects for your students?

• do the team projects have multidisciplinary teams?

• do the team projects include industry participants from diverse sectors?

• do the team projects have multicultural teams?

• do the team projects focus on real-world challenges to improve local systems?

• what percentage of your course lectures change every year?

• do new lectures highlight new research finding from journals that highlight new knowledge?

• do new lectures highlight new entrepreneurs, applying new knowledge to create value?

• do new lectures and team projects build the social networks of your students?

Escape Velocity• What if there is some

hidden force that is working against your best efforts? That force, I submit, is the pull of the past...

• The larger and more successful the enterprise, the greater the inertial mass, the harder it is to alter course and speed.

What are Cognitive Systems?

• 3 L’s = Language, Learning, Levels• How many cognitive systems?• How much investment?• Technology underlying new era…• In sum, a picture…

Questions & Framing

• In 5-10-15-20 years, what will be different?– How will higher education have changed?– How will skills & jobs have changed?– How will business & society have changed?

• Service science, a lens for looking at change– Capabilities & constraints – technology systems– Rights & responsibilities – rule systems– What is “lawful” (physical, social) change?

Watson Business Unit

• $1B Investment: Far beyond Jeopardy!

Watson Foundations Big Data and Analytics

Cognitive Systems108

Ecosystem ProgramBusiness PartnersDevelopersResearchers

SolutionsCustomer EngagementHealthcareFinanceAccelerated Research

ServicesWatson Discovery AdvisorWatson ExplorerWatson Analytics

Land-population-energy-carbon

Carlo Ratti:Senseable Cities

IBM Platforms for Entrepreneurs

• Smarter Cities Intelligent Operations Center Platform• IBM Watson & Cognitive Computing Platform• IBM UP helping university startups to scale-up (growth)

Universities Matter

In sum, service science• Service System Entities

– Types: Businesses, Universities, Governments, etc.– Nested & Networked Globally– S-D Logic (A2A; Resource Integrators)

• Value Co-Creation Interactions– Types: Value-Proposition & Governance Mech-based– Collaboration & Competition Blended– SD Logic (Operant & Operant Resources)

• Builds On…– Decades of Service Research (Marketing, Operations, etc.)– SSME+DAPP; From I to T to Pi-shapes… and beyond!– T Summit 2014 & 2015..

• Measures– Productivity, Quality, Compliance, Sustainable Innovation– Holistic Service Systems

• Quality of Life, Balance Challenge & Routine• Innovativeness, Equity, Sustainability, Resilience

Today’s talk

• Preamble• What is service science? Service systems?• What are cognitive systems? • What are the trends?

– Why makes universities/cities such special service systems/cognitive systems?

• Backup: Readings (some details)

Preamble• Abstract & Readings Summary• Future of higher education

– One possible path & assumptions– Best way to predict future is to design it

• Questions & framing• What is meant by “lawful”• Do any social interaction laws not change?• Service science preliminaries• Who I am & my biases• Universities and our future/history

Abstract• Patterns of Change: Transformation of Higher Education From Service Science and Cognitive

Systems Perspectives

This talk will discuss the forces reshaping higher education from service science and cognitive systems perspectives, and presents an optimistic view of the likely outcome. These same forces are reshaping business and society globally. Higher education is just one of many interconnected service systems that make up our world. However, higher education is special in many ways. For most, higher education is the bridge to cross from youthful family life to meaningful service to society. Also, all great cities have a major university that includes the broad spectrum of human knowledge, concentrated in experts and an army of energetic students within typically a square mile region. Universities are increasingly startup engines for regional economic development and growth. Within two decades most people on the planet will have a smart phone (disrupted and reconfigured), including a personal cognitive system, which is both an expert professional coach and an executive assistant. Cloud, Big Data Analytics, Mobile, Social, Cognitive, Internet of Things and Humans provide the integrated platform for reframing the meaning of progress with universities, leading to an era of T-shaped professionals engaged in meaningful, creative cognitive sport.

Readings Summary• Spohrer, J., Fodell, D., & Murphy, W. (2012). Ten Reasons Service Science Matters to Universities. Educause Review, 47(6), 52-64.• Lusch, R., & Wu, C. (2012). A service science perspective on higher education—Linking service productivity theory and higher education

reform. Center for American Progress, August.• Denna, E. (2014) The Business Model of Higher Education. Educause ViewPoint. March 24, 2014.• Henry, T, Pagano, E, Puckett, J, Wilson, J (2014) Five Trends to Watch in Higher Education. BCG Perspectives.• Meeker, M (2014) Internet Trends 2014 – Code Conference• Sledge, L & Dovey-Fishman, T (2014) Reimagining higher education: How colleges, universities, businesses, and governments can prepare for a

new age of lifelong learning. Deloitte University Press. • IBM (2014) Education for a Smarter Planet• Goldbloom, A (2011) Making data science a sport. O’Reilly Media Strata Conference. • Johnson, RC (2013) IBM Unveils Cognitive Systems Institute. EETimes. October 3, 2013.• MSU & IBM (2014) T-Summit 2014: Cultivating Tomorrow’s Talent Today. Website & Conferences.• Spohrer J (2014) 21C Talent and 21C Citizens. Service Science Community Website Blog Post Entry.• Dyens, O (2014) How artificial intelligence is about to disrupt higher education. UA/AU University Affairs Affaires universitaires. April 30,

2014.• Kenneth F. Brant , KF, Gupta, A, Sommer, D (2013) Maverick* Research: Surviving the Rise of 'Smart Machines,' the Loss of 'Dream Jobs' and

'90% Unemployment.’• Spohrer, J., Giuiusa, A., & Demirkan, H. (2013). Service science: reframing progress with universities. Systems Research and Behavioral Science,

30(5), 561-569. • Pentland, A. (2014). Social Physics: How Good Ideas Spread-The Lessons from a New Science. Penguin.• Moore, GA (2012) Escape Velocity: Free Your Company’s Future From The Pull Of The Past. Harper Business.• Florida, R (2009) Who’s Your City? Basic Books.• Ng, Irene (2013) Hat: Hub-of-All-Things website. Research Councils UK (RCUK) Digital Economy.• Carmichael, A (2011) Announcing: The Complete QS Guide to Self Tracking. Quantified Self website. January 12, 2011.• Board of Life Science (2014) Convergence: Facilitating Transdisciplinary Integration of Life Science, Physical Sciences, Engineering, and Beyond.

What is meant by “lawful”

• Physical interaction laws do not change*– However, innovations change the costs– Intel, IBM, OpenPOWER (computing costs)– AT&T, Corning, Cisco (communications costs)

• Social interaction laws do change– And innovations change the costs– Google (Internet search) and copyright– Uber (ride sharing) and taxi regulations– Airbnb (home sharing) and rental regulations

* = of course, our understanding of physical laws does change, other caveats apply.

Do any social interaction laws not change? Yes, mathematical truths!

• Ricardo – Law of Comparative Advantage– Do a little more of what you do best (low cost)– Do a little less of what you do least well (high cost)– Learning curve effects in people, businesses,

countries (interaction can be mutually beneficial)• Assumptions (On when to specialize…)

– Entities can do multiple things at variable costs– Learning interaction is not zero cost transfer

Who I am & my biases

• Change is hard to make happen (“predict”)– My professional experiences

• No shortage of useful things to do– I am very optimistic about the future

• Better mechanisms needed– “Cognitive sport” & “improve weakest link”

Universities and our future

• The future is already here at universities, it is just not yet well distributed.– With apologies to Gibson/King

• The best way to predict the future is to inspire the next generation of students to build it better.– With apologies to Kay/Engelbart

Early Motivations (Growth 2)

Gerstner decidesto grow service

Early Motivations (Aspiration 2)

Principle 1: Resources

Principle 2: Value Propositions

Principle 3: Access Rights

Principle 4: Outcomes

Principle 5: Dynamics

Principle 5: Dynamics (Revisited)

Principle 6: Entities

In sum, a picture…

Courtesy Jean Paul Jacob, IBM Research Emeritus

ProfessionalCognitiveAssistants- Language- Learning- Levels

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