Bio (150 words):
Dr. James (“Jim”) C. Spohrer is Director, Understanding Cognitive Systems working in IBM Research’s Chief Science Office Cognitive. He advocates for cognitive mediators for all people – especially professionals who are future-ready adaptive innovators, with T-shaped skillsets and mindsets. Previously, he led IBM Global University Programs and IBM’s Cognitive Systems Institute. Jim co-founded IBM’s first Service Research group, ISSIP Service Science community, and was founding CTO of IBM’s Venture Capital Relations Group in Silicon Valley. He was awarded Apple Computers’ Distinguished Engineer Scientist and Technology title for his work on next generation learning platforms. Jim has a Yale PhD in Computer Science/Artificial Intelligence and MIT BS in Physics. His research priorities include service science, cognitive science, and wise service systems. With over ninety publications and nine patents, he is also a PICMET Fellow and a winner of the Evert Gummesson Service Research award as well as the S-D Logic award.
Picture (2008, yep – time to update, I am older):
Picture – October 15, 2016 Chongqing China – keynoting at 9th ICSS
Title and Contact:
Dr. James (“Jim”) C. Spohrer
Director, Understanding Cognitive Systems
Last role, Director, IBM UPward = University Programs worldwide, accelerating regional development
Cognitive Systems Institute = improving productivity and creativity of cognitive systems research (problem-solving professionals)
Innovation Champion (http://www-03.ibm.com/ibm/history/ibm100/us/en/icons/servicescience/)
IBM Almaden Research Center, 650 Harry Road, San Jose, CA 95120 USA
email@example.com 408-927-1928 (office)
firstname.lastname@example.org 408-829-3112 (iPhone)
Social Media Me:
LinkedIn: Jim Spohrer (http://www.linkedin.com/in/spohrer/)
Twitter: @JimSpohrer (https://twitter.com/JimSpohrer)
Patents and Publications
(h-index all = 34, meaning that 34 of my publications have been cited 34 times or more)
Understanding Cognitive Systems
My mission is “understanding cognitive systems” – what does that mean? People, dogs, cats, crows, and even bees and ants are cognitive systems with social intelligence, and someday so will our smart phones, our homes, our offices, our cars, and yes, even our clothes will be cognitive systems with social intelligence. Hard to believe in 2016, but I bet it is coming. Socio-technical hint: Someday everything will have some form of blockchain episodic memory about its interactions for legal reasons. Even businesses and governments will become cognitive businesses and cognitive governments, cognitive system entities with episodic memories and social intelligence.
I am trying to understand how people build, understand, and work with cognitive systems. Digital cognitive systems are progressing from tool to assistant to collaborator to coach to mediator. This is an evolutionary progression – a progression of both technology (capability) and trust (responsibility). Do you trust your smart phone? To me this is a hard research problem – trying to understand socio-technical system design and evolution. This type of research is a kind of transdisciplinary integration of service science and cognitive science. It requires thinking a lot about people-centered systems redesign. That is the kind of research I enjoy doing the most. Caution: Powerful things can be misused – guns, planes, trucks, computers, and words. People-centered systems redesign has to take this into account: as the building blocks get better, so must the wisdom and responsibility of the people using them. That is the really hard part. If you are interested in this type of research too – I recommend reading these books and articles – and then we can have a good conversation:
To understand the socio-technical systems design loop read:
Kline, S. J. (1995). Conceptual foundations for multidisciplinary thinking. Stanford University Press.
To understand the philosophical foundation of institutional facts read:
Searle JR. (1995). The construction of social reality. Simon and Schuster.
To understand software social organisms read:
Forbus KD. (2016). Software Social Organisms: Implications for Measuring AI Progress. AI Magazine. Mar 1;37(1).
To understand memory, including episodic memory read:
Schank RC. (1983). Dynamic memory: A theory of reminding and learning in computers and people. Cambridge University Press; Jan 1.
To understand a bit, just a hint, about service science and cognitive science integration read:
Spohrer J, Banavar G. (2015). Cognition as a Service: An Industry Perspective. AI Magazine. Dec 1;36(4).
To understand a bit more about service science read (you could also read the Handbook of Service Science, but this is a lot shorter):
Spohrer J, Maglio PP.(2008). The emergence of service science: Toward systematic service innovations to accelerate co‐creation of value. Production and operations management. May 6;17(3):238-46.
If you read all of the above, we could have a really fun conversation about the better building blocks of the future.
The best way to predict the future is to inspire the next generation of students to build it better.
Currently trying to understand cognitive systems better based on my three foundations (1) my PhD from Yale is in Computer Science, specialized in Artificial Intelligence and Cognitive Science (1982-1989) – see: https://scholar.google.com/citations?user=7T2Pz1YAAAAJ (scroll down to get to the Artificial Intelligence and Cognitive Science papers), (2) my four years doing machine learning for speech recognition and natural language understanding at the Verbex company (1978-1982) after I graduated MIT in Physics (1974-1978), and (3) my nearly ten years building intelligent tutoring systems and students models at University Rome in Italy (1989) and at Apple Computer (1989-1998).
IBM University Programs (the 6 R’s of IBM UP) include:
1. Research (ibm.com/university/awards)
2. Readiness (ibm.com/developerworks/university/academicinitiative/)
3. Recruiting (ibm.com/jobs or ibm.com/developerworks/university/students/)
4. Revenue (ibm.com/education and ibm.com/systems)
5. Responsibility (ibm.com/responsibility, ibm.com/ibm/ondemandcommunity and en.wikipedia.org/wiki/World_Community_Grid)
6. Regions (ibm.com/partnerworld/isv/startup)
Local “On Campus IBMers” (where available) help with the above…
IBM UP Priorities include:
1. Smarter Cities & Service Innovation
2. Cloud & Analytics/DEEP QA, including High Performance Systems & Cybersecurity, Social Business
3. Growth Markets universities linked to Developed Markets universities to accelerate regional innovation
Doing more with less is the theme throughout business and societal systems, and to do this sustainably year over year…
Doing more with less decision-making & investment discipline: Run-Transform-Innovate or Iterate-Imitate-Innovate (I-cubed)
I-cubed investment discipline steadily automates “Iterate” (5%/yr cost cut) lowering costs, to invest more in “Imitate & Innovate”
I-cubed is Moore’s Law equivalent for business & societal systems (smarter service systems improve as IT capabilities grow)
I-cubed supports escaping the pull of the past and escaping the commodity trap
View of University Priorities include:
1. Knowledge transfer (teaching) – student tuition & government loans
2. Knowledge creation (research) – government grants & corporate partners
3. Knowledge application (entrepreneurship) – local incentives & alumni donations
4. Knowledge integration (bridge silos) – lowers costs without compromising depth
University business model is evolving (to fund the above, and continuously renew physical infrastructure)…
Some universities, governments, and businesses are adopting I-cubed investment discipline to do more with less year over year.
I-cubed investment discipline can be applied to education as a service system for continuous improvement
“Civilization advances by extending the number of important operations which we can perform without thinking of them.”
Alfred North Whitehead, English mathematician
While I really like this quote, one possible implication is consciousness goes to zero. Perhaps there are other possibilities too. For example, read this: De Chardin T. Pierre. (1959). The phenomenon of man. Trans. Bernard Wall. New York: Harper & Row.