Bringing hundreds of people together every year to discuss the T-Shaped Professionals was done at by IBM and Michigan State University (MSU) in 2014, 2015, and 2016.

T Summit 2014 (IBM Research Almaden, San Jose, CA)

T Summit 2015 (Michigan State University, East Lansing, MI)

T Summit 2016 (National Academies, Washington DC)

Since 2017, The T-Summits have been smaller workshop at MSU – See http://tsummit.org

Previously (2008), IBM and Cambridge University called for creation of T-shaped Professionals in a report:

Cambridge-IBM SSME Report (Cambridge University, UK):

https://www.ifm.eng.cam.ac.uk/uploads/Resources/Reports/080428cambridge_ssme_whitepaper.pdf

“4.3 Where are the opportunities to address the skill gap? Developing T-shaped professionals: Discipline-based education remains a vital role of modern universities. In order to close the skill gap, however, universities should also offer students the opportunity to gain qualifications in the interdisciplinary requirements of SSME. Such qualifications would equip graduates with the concepts and vocabulary to discuss the design and improvement of service systems with peers from other disciplines. Industry refers to these people as T-shaped professionals, who are deep problem solvers in their home discipline but also capable of interacting with and understanding specialists from a wide range of disciplines and functional areas.  Widely recognised SSME programmes would help ensure the availability of a large population of T-shaped professionals (from many home disciplines) with the ability to collaborate to create service innovations. SSME qualifications would indicate that these graduates could communicate with scientists, engineers, managers, designers, and many others involved in service systems.  Graduates with SSME qualifications would be well prepared to ‘hit the ground running’, able to become immediately productive and make significant contributions when joining a service innovation project.”

“5.1 Recommendations for education: Enable graduates from various disciplines to become T-shaped professionals, who are adaptive innovators with a service mindset and can make early contributions to the service-driven economy.  All students and employees, who wish to, should have the opportunity to learn about Service Science and develop themselves into T-shaped professionals. This can be achieved by adding SSME qualifications to an existing deep home discipline of study. As adaptive innovators, they will have a good background in the fundamentals of service innovation. With a service mindset, they can work effectively in project teams across discipline and functional silos. As research creates a truly integrated theory of service systems, students of Service Science will become system thinkers prepared to succeed in a 21st century service-driven globally integrated economy.”

IfM and IBM. (2008). Succeeding through service innovation: A service perspective for education, research, business and government. Cambridge, United Kingdom: University of Cambridge Institute for Manufacturing.  ISBN: 978-1-902546-65-0.

IDEO had called for creation of T-Shaped Professionals earlier as well.

IDEO CEO Tim Brown: T-Shaped Stars: The Backbone of IDEO’s Collaborative Culture

McKinsey & Company had also called for creation of T-Shaped Professionals even earlier.

(Presented at JAIST World Conference)

Preparing for Our Future with Open Artificial Intelligence (#OpenTechAI): A Service Science Perspective

Keywords: service science, service-dominant logic, knowledge science, computer science, artificial intelligence, open source, open technologies, open innovation, scientific repeatability

This talk will present a service science perspective on how best to prepare for our future with open artificial intelligence.  To frame this discussion, a somewhat novel introduction to the interconnected domains of knowledge science, service-dominant logic, computer science, artificial intelligence, open innovation will be offered.  Service science aims to provide a transdisciplinary explanation of the evolving ecology of service systems entities and the value propositions that interconnect them, based on a service-dominant logic world view, in which service is the basis of all exchange and the primary motivation for interaction between entities.  Service science can be thought of as the knowledge-base that allows entities to learn to play better and better win-win games over time.  Service-dominant logic has defined service as the application of knowledge for the benefit of others. From a computer science perspective, artificial intelligence capabilities of entities can be viewed as the application of knowledge to perform a task as well as or better than a person.  A timeline and roadmap will be presented for solving open source artificial intelligence (i.e., performance at about human-level on first narrow and then general tasks) for most tasks in our modern economies that are based on human knowledge and technical expertise.  Much of the progress towards solving artificial intelligence is on full display on GitHub (open source code projects) and on AI and data science leaderboard challenge websites (e.g., Kaggle).  Preparing for our future with open artificial intelligence will force a deeper examination of the rights and responsibilities of entities, their interactions and the outcomes of those interactions. Apps on smartphones will gain capabilities (e.g., voice interfaces, conversation interfaces, episodic memories, etc.) and transform into low-cost digital workers as Moore’s Law continues.  This will represent a miniaturization of the expertise economy of nations.   As factories and farms also miniaturize, entities will have the opportunity to lower costs through AI-directed local material and energy flows.  Individuals empowered by eventually hundreds of low-cost digital workers, as well as miniature factories and farms will enjoy “better building blocks” than any previous generation, as well as higher GDP (Gross Domestic Product) per employee, and higher quality of life as a result.  However, this is not utopia, as new challenges will emerge, requiring new forms of governance to gain the benefits and avoid the risks of these advances.  Open innovation challenges offer one such positive direction for entities, individuals, businesses, universities, and governments.

6 Rs of learning
Knowledge was in you
1. remember – index better in a dynamic memory
2. rehearse – practice
Knowledge was in someone else
3. receive – ability to understand answers to answered questions
4. reconstruct – ability to re-answer answered questions in new ways
Knowledge not previously in anyone
5. research – ability to answer unanswered questions
6. reflect – ability to ask good questions

Reference to above: http://www.learndev.org/dl/DenverSpohrer.PDF

smartphone-based AI constructivist and model-trace one-on-one cognitive tutors/coaches….

(1) AI Systems will one day (2-5 years) going to be able to take and pass online courses.

Japan – TODAI – takes U Tokyo entrance exam: http://www.businessinsider.com/robot-beat-most-students-on-university-tokyo-entrance-exam-2017-9
China – IFLYTEK – takes medical exam: http://www.chinadaily.com.cn/bizchina/tech/2017-11/10/content_34362656.htm

(2) When the above happens, there will be open source code + data + model from these systems available on GitHub

(3) Learners who want to learn from an online course can have their AI take and pass the course first, and then guide them to higher completion rate on the same material

(4) Connecting the on-line courses and education about IT applications to HICSS talks completes the loop of education and research…  see 6 R’s:

6 R’s of Learning: https://service-science.info/archives/2096
Revisiting 6 R’s: https://service-science.info/archives/4726

Since I started leading IBM’s open source AI efforts, I am frequently asked how best to prepare for our future with AI.  While I have a long presentation here, I decided to try to distill it to one slide:

Recently, one member of the audience signed up for Github, during the talk!!!  Got to give him credit where credit is due – and taking a great first step in preparing for the future with AI.

I have *not yet* found a good way to explain GitHub to people…. especially the future of GitHub, when people do not need to know how to program to use it to access AI super-powers.  However, watching this Disney Fantasia clip with Mickey Mouse called Sorcerer’s Apprentice Fantasia is a good hint at what is coming.

Programmers are the conjurers today.  However, find a friend who knows about open source AI on GitHub, even if you are not a programmer.  Find a friend who knows about Tensor2Tensor (T2T), and learn to read and execute the iPython Notebook code.  Start exploring low code environments, like the one offered by Mendix as well.  In the coming years, non-programmers will be able to access AI super-powers on GitHub.  And follow the progress of AI via the leaderboards – see this presentation here.

Question:  What should students, parents, and faculty know about actionable knowledge/code/GitHub?

Possible answer:

Wikipedia is a source of information that can be converted to knowledge.

Code (software) is a form of actionable knowledge that can be converted to value.

Every student today knows Wikipedia, and for tomorrow they need to get a GitHub account and learn to partner with a friend to do cool things with code -see: https://service-science.info/archives/4834

WHy is it important that all students have GitHub accounts and learn to search for projects related to their interests?

For example – Poetry:  https://github.com/ChaosPKU/Poetry – A RNN model to automatically generate Chinese ancient poems with the input of start words. The idea is inspired by Weiyi Zheng’s tangshi-rnn and Andrej Karpathy’s Char-RNN.

For example – Exoplanets:  https://github.com/pinardy/exoplanets-data  Discover the number of exo-planets and details of the planets given a set of data

For example – Viscous flows: https://github.com/Intro-Quantitative-Geology/Viscous-flows  Materials related to laboratory exercise 5 on viscous flow of rock and ice

Code is actionable knowledge – value comes from actionable knowledge – which is why students need to get a GitHub account and learn to search for projects relevant to their interests.

How to help me: You can help me by getting more people to think about GitHub, Kaggle, and open source AI.  Specifically, ask people to imagine a day when they can ask their smartphone to take any on-line course, and their smartphone can take the online course and pass the course (Student-Mode).  Next, the AI system can switch into Tutor-Mode and help the user pass the same online course.  Boosting skills of people is what IBM calls “Cognitive Computing” – and this is a form of “Intelligence Augmentation” – or AI for IA.  To understand the AI system in Student-Mode better – watch this TED Talk: https://www.ted.com/talks/noriko_arai_can_a_robot_pass_a_university_entrance_exam  and now imagine a world where AI systems program as well or better than people – then read this: https://service-science.info/archives/4834  The person/organization that builds the first AI system that can take and pass most on-line courses will become quite famous in the history of IA for humanity.

The day when an AI system can program as well or better than people, and help people learn more is something that I have been preparing for for quite some time – see the book MARCEL: Simulating the Novice Programmer: https://www.amazon.ca/MARCEL-Simulating-Programmer-James-Spohrer/dp/0893917656

I will visit Finland in March, and wanted to give you a heads up about an upcoming Opentech AI Workshop related to industry-specific AI applications and therefore, smarter/wiser service systems.

We are asking a few close colleagues to register if they have an interest (we will have about 100 participants):

What: Free Opentech AI Workshop
When: March 13-14, 2018
Where: IBM Finland HQ, Laajalahdentie 23, 00330 Helsinki, Finland
Registration: https://www.eventbrite.com/e/1st-international-workshop-on-opentech-ai-tickets-42648142743 (password “testai”)
Local FAQ & map:  http://www-05.ibm.com/fi/contact/ibmhelsinki.html

Note on registration page, if you would like to present a poster: Please contact Susan Malaika <malaika@us.ibm.com> by Feb 23, putting Helsinki poster in the subject line, if you would like to showcase your AI work in a poster on March 13 between 17:30-19:30.  Please include: Your name and the names & email address any other poster authors, The poster title, The poster abstract, Any relevant links

What is Opentech AI?

Opentech AI is open source communities doing great things with Artificial Intelligence.  Hundreds of communities are forming – For example, consider Mozilla’s Common Voice project for open AI voice technology, and Healthcare.ai has projects related to healthcare.  In addition, AI challenge/leaderboards are proliferating.   

Why Industry-Specific Opentech AI? Why Finland?

Finland’s national AI strategy is to be #1 in application of Artificial Intelligence to improve industry performance.

What is the Future of Opentech AI?

Some AI researchers are already envisioning one open source AI system that can perform reasonably well on all leaderboard challenges – see Video for vision to do this, and Measuring AI Progress Presentation for Roadmap, and related Article and Blog.

Summary of URLs:
Finland AI Strategy: http://www.vttresearch.com/Impulse/Pages/Finland-seeking-top-spot-in-application-of-artificial-intelligence-AI.aspx
Example Mozilla Open Voice: https://voice.mozilla.org/
Example Opentech AI for Healthcare: https://healthcare.ai/
Video – One AI to Learn It All: https://www.youtube.com/watch?v=8FpdEmySsuc
Presentation: https://www.slideshare.net/spohrer/leaderboards-80909263
Blog: https://opentechai.blog/
Article: I-Athlon: One AI to do Many Tasks: https://pdfs.semanticscholar.org/53f1/a7ac0398cce4ce049fd5e2d79e67925a492c.pdf

Questions? Contact Jim Spohrer <spohrer@us.ibm.com>

Register for Free AI Open Community Gathering Featuring TensorFlow

On Feb 20, 9am-1pm, leaders from enterprise AI companies and open source code foundations will meet in San Francisco to deepen collaboration efforts around TensorFlow/Keras for building and sharing open code, data, models, and measuring progress on AI challenge leaderboards.

When: Feb 20, 9am-1pm (try to arrive 30-60 minutes early to pick up badge, etc – it will be crowded.)
Where: Moscone Center, San Francisco
What: Open Source AI, featuring TensorFlow session (Google, IBM, Linux Foundation, others)
Registration required: https://developer.ibm.com/indexconf/faqs/

Contact me Jim Spohrer <spohrer@us.ibm.com>
for Feb 20 FREE code and for Feb 21-22 DISCOUNT code
STUDENTS with valid IDs can register for FREE for conference, just go to website above
OR FIND CODES HERE: https://www.meetup.com/SF-Big-Analytics/events/247405815/?_cookie-check=7ngyivw0NuPTS7Vs

TensorFlow agenda here:

https://developer.ibm.com/opentech/2018/02/03/index-feb-20-ai-open-community-gathering-featuring-tensorflow/

Anticipated agenda…. watch official website above.

Earlier draft…

Part 1 – TensorFlow 9-noon Pacific
9:00 Welcome – Ruchir Puri IBM Fellow and IBM Watson Chief Architect
9:05 TensorFlow Opening Session  (15m) – Google’s  Wolff Dobson
9:20 Community update: The TensorFlow Universe (10m) – Edd-Wilder James, Google
9:30 TensorFlow process and support (15m) – Pete Warden, Google
9:45 How we build and test TensorFlow (15m) – Gunhan Gulsoy, Google
10:00 Tensor2Tensor (15m) – Lukasz Kaiser, Google
10:15 TensorFlow/R integration, Andrie de Vries, RStudio
10:30 BREAK
11:00 Kubeflow (30m) – Jeremy Lewi, Google
11:30 TensorFlow & Kubeflow Town Hall / Q&A (30m) – Panelists: Jeremy Lewi, Martin Wicke, Pete Warden; chair Edd Wilder-James.
12:00 END TENSORFLOW – BEGIN COMMUNITY AI

Part 2 – AI Communities noon-1pm Pacific
12:00 The Linux Foundation and AI (20m),  Sheryl Chamberlain &  Philip DesAutels, Linux Foundation
AI framework project, IBM’s Waldermar Hummer or Scott Boag
And Apache Foundation Talk – stay tuned…
ISO/IEC JTC 1 SC 42 – subcommittee on AI, stay tuned, perhaps for IBM’s Steve Holbrook
Running TensorFlow  & Data Science software on mainframes and PowerAI/Mainframes/etc.
12:40pm Final Remarks (20m) – IBM Fellow and IBM Watson Chief Architect Ruchir Puri
1:00pm END MORNING

Register for Free AI community day.   Contact me for FREE code <spohrer@us.ibm.com>

Just returning from HICSS conference, where one of the keynotes was on augmented intelligence….  got me thinking about augmented intelligence for individuals, businesses, and families – three important types of service system entities.

To see where I am coming from, this Politico article is a worthwhile careful read:

The Real Future of Work
https://www.politico.com/magazine/story/2018/01/04/future-work-independent-contractors-alternative-work-arrangements-216212

…these perspectives surprised me:

“It was also clear from the Katz-Krueger data that the shift to contingent work wasn’t driven by the rise of the sharing economy. Just 0.5 percent of workers are in the sharing economy, accounting for at most 10 percent of the labor market shift over the past 10 years. In other words, for all the concerns about Uber and other sharing economy companies using independent contractors to skirt state and federal labor laws, the shift toward these workplace arrangements predates those companies. They’re followers, not leaders.“

“Congress didn’t create similar workplace protections for independent contractors because they were considered to effectively be their own small business, setting their own hours and responsibilities, providing their own benefits and determining their own economic outcomes. More independence came with fewer social protections, a trade-off that many Americans support. According to a 2015 Government Accountability Office report, independent contractors are slightly more likely to be satisfied with their jobs than full-time employees, and fewer than 10 percent said they would prefer a different type of employment.”

“If the workplace is changing so much, would it be possible to invent a new kind of worker? One solution that has begun to arise among labor experts is to create a third, hybrid worker classification—something between an employee and a contractor, offering protections to people, like Uber drivers, who might not be “employees” but work chiefly for one company. But this argument has already started to break down along partisan lines. Republicans tend to support it as overdue acknowledgment that many workers in the modern workplace don’t fit neatly into the employee or contractor box. Democrats are wary of creating a category that might let employers shift even more employees into less-stable work arrangements.”

Like the above read, which shows which category of workers is growing fastest – I still think “why” is not clearly understood, my hunch is there is a wealth effect happening at the extended family-level due to costs dropping from technology deflation, but I could be wrong.  I think the most vulnerable in society could be those without large “extended families” living near to them.   Not sure what data would show this, since “extended family” does not have to be blood relatives – it is “a network of people who care about and support each other as they make smart/wise service exchanges,” but that is my hunch just looking around and thinking about the situation the most people in the world are in…  The individual is probably not the right unit of analysis for worker policy anymore, maybe it never has been.  Augmented intelligence for extended families is a good area for study I think.

Thanks to Bill Daul for sending the pointer to the Politico article.

At HICSS conference one of my favorite presentations was about simulating service systems entities following Service-Dominant logic principles.  Abstractly one can think about the actors as individuals, businesses, or families learning one of three skills for surviving (operant resources) – two skills involve gathering resources from nature (the environment) and one of the skills involves gathering resources through trade/exchange (the social network).  See paper by Fujita, Vaughan, and Vargo:

https://scholarspace.manoa.hawaii.edu/bitstream/10125/50087/1/paper0200.pdf

Augmented intelligence may work best for entities that use a service-dominant architect.

Thinking about a service-dominant architecture for businesses was another interesting HICSS paper: https://scholarspace.manoa.hawaii.edu/bitstream/10125/50091/1/paper0204.pdf

We also need service-dominant architecture for individuals and families.

Service-dominant architecture for individuals and families will depend on cognitive assistants, evolving on our smartphones and home devices, which brings us to this HICSS paper:  https://scholarspace.manoa.hawaii.edu/bitstream/10125/50092/1/paper0205.pdf

We need better data collection and simulation tools to inform policy development.  The early stage simulation above is a good step towards tools that can help understand the evolving ecology of service system entities, with their capabilities and constraints, rights and responsibilities.   The three skills (operant resources) that it begins to model are all exploitation-oriented from the perspective of March’s exploitation-exploration capabilities of learning systems (all organizations are learning systems).   So to add a fourth skill (operant resoure) to the SD logic simulator, it would be interesting to think about a skill associated with exploration that can create new types of resources, either finding them in nature or finding them in social networks.   See this article to understand exploitation-exploration in organizational learning: http://www.analytictech.com/mb874/papers/march.pdf

…will be great if you can attend the AI Workshop in Helsinki March 14th: https://opentechai.blog/2017/12/29/opentech-ai-workshop/

Also, keep me posted if you see any AI Challenge Leaderboards related to education:

China Medical Entrance Exam AI Challenge: https://phys.org/news/2017-06-ai-so-so-grade-chinese-university.html
Japan Tokyo U Entrance Exam AI Challenge: http://www.businessinsider.com/robot-beat-most-students-on-university-tokyo-entrance-exam-2017-9

Delighted if you can help me find more, better AI Challenge Leaderboard/League Table examples.

Leaderboards or League Tables are a type of standing/ranking mechanism for entities with capabilities: https://en.wikipedia.org/wiki/Standings

Leaderboards are appearing for more and more AI capabilities – see Question Answering Leaderboard example here:  https://rajpurkar.github.io/SQuAD-explorer/

Daniel Pakkala (VTT) and my IBM team are building an AI Progress Benchmark Roadmap based on Leaderboards (download from here): https://www.slideshare.net/spohrer/leaderboards-80909263

Frontiers in Service Conference 2018

http://www.frontiers2018.com

NOTE!! Deadline for abstracts is February 1, 2018

2018 Frontiers in Service Conference 

Call for Abstracts 

https://frontiers2018.exordo.com/

The Frontiers in Service Conference is the world’s leading annual conference on service research. It is co-sponsored annually by the AMA Service SIG and the INFORMS Service Science Section.

In 2018, the 27th Annual Frontiers in Service Conference will be hosted by Texas State University in Austin, Texas, September 6-9, 2018. The main conference sessions and events will occur within the Hilton Austin Hotel, which is just one block away from Austin’s famed 6th Street Entertainment District.

The 2018 Frontiers in Service Conference will explore a wide variety of service topics, including service marketing, service management, service operations, service design, service engineering, service science, and service IT.

You are invited, as a service academic or practitioner, to submit a 450-word abstract (https://frontiers2018.exordo.com/) for possible presentation at the conference. The Frontiers in Service Conference routinely attracts submissions from over 40 countries.

Case studies by business practitioners are encouraged, and a “Best Practitioner Presentation” will be awarded at the conference.

The average number of attendees is around 300 scholars and practitioners. Fewer than half of the submitted abstracts are accepted for presentations.

Abstracts may focus on any service topic, including (but not limited to) the topics below:

Analytics and Service

Big Data and Service

Customer Relationship Management

Digital Service & Collaborative Economy

E-Service & E-Government

Healthcare Service

Internet of Everything and Service

IT as a Service

Public Sector Service

Service Design

Service Operations

Service Management

Service Marketing

Service Engineering

Service Productivity

Service Innovation

Servicescapes

Service Science

Service at the “Bottom of the Pyramid”

Social Networks and Service

Smart Service Systems

Technology-based Service (Apps)

Theoretical Perspectives on Service

Transformative Service Research

For more information, please contact us at admin@frontiers2018.com

Website – www.frontiers2018.com
————————————————————————————
Raymond P. Fisk
Professor and Chair
Department of Marketing
McCoy College of Business Administration
Texas State University
601 University Drive
San Marcos, Texas 78666
Work Phone: (512) 245-9614
Work Fax: (512) 245-7475
Cell Phone: (512) 618-0985
E-Mail: Ray.Fisk@txstate.edu
Private E-Mail: RayFisk@icloud.com
Skype Name: rayfisk
http://marketing.mccoy.txstate.edu/faculty-staff/faculty/fisk.html

I am planning to visit JAIST Ishikawa campus Feb 27-28, and IBM Research – Tokyo March 1st, and evening JAIST Tokyo campus.  Coming soon information about the presentations I will be making.