Patterns of Change: The Transformation of Higher Education From Service Science & Cognitive Systems Perspectives Jim Spohrer Director, IBM Global University Programs and Cognitive Systems Institute Aspen Forum, Aspen, CO June 19, 2014 05/27/2022 (c) 2014 IBM UP (University Programs) 1
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04/11/2023 (c) 2014 IBM UP (University Programs) 1
Patterns of Change:The Transformation of Higher Education From
Service Science & Cognitive Systems Perspectives
Jim SpohrerDirector, IBM Global University Programs and Cognitive
Systems InstituteAspen Forum, Aspen, CO
June 19, 2014
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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)
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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
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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.
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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.
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Future of higher education(one possible path & assumptions)
Years Change – Possible Progress Path Service Science Aspect
0-5 Revenue Continuous Improvements Data Science & Cloud
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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?
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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.
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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
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Service Science Preliminaries
• 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)
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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
Manufacturing: Circular EconomyBaxter: Building the Future
Maker-Bot: Replicator 2
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Energy: Artificial Leaf
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Technology: Cognitive Computing
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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
worldwide accelerating regional development (IBM UPward)
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“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.”
“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
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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)04/11/2023
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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.
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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.”
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Trading Zone:Economist, Policymakers & Service Scientists
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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
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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.
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Internet Trends 2014
Industry Transformation
Donald Clark, TEDxGlasgow
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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
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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
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Kaggle: Making Data Science a Sport(146 competitions)
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Cognitive Systems
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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
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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?
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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.
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Gartner Maverick Report
• Control– Institutions– Individuals
• Autonomy– Low– High
From:Surviving the Rise of 'Smart Machines,' the Loss of 'Dream Jobs' and '90% Unemployment.
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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.
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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.
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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.
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