This just in from Dick Larson (MIT):

The first is Irving Wladawsky-Berger’s  blog post, “STEM Literacy and Jobs,”
http://blog.irvingwb.com/blog/2016/09/stem-literacy-and-jobs.html
which eventually (in somewhat shortened form) made it to the WSJ.  http://www.wsj.com/news/cio-journal

We at MIT were happy that he cited two our our STEM papers:  “Stem is for Everyone” (http://www.wise-qatar.org/richard-larson-stem-mit-blossoms) and “STEM crisis or STEM surplus? Yes and yes” (http://www.bls.gov/opub/mlr/2015/article/stem-crisis-or-stem-surplus-yes-and-yes.htm) This latter paper (coauthored with my former student, Ms. Yi Xue) was selected for the Lawrence R. Klein Award representing the Best Paper of the Year in Monthly Labor Review, for someone not employed by the U.S. Department of Labor.  http://www.bls.gov/opub/mlr/2016/announcement/klein-award-recipients-announced-for-2015.htm

The second is this IBM web site:  “The classroom will learn you, Cognitive systems will provide decision support for teachers.”  http://www.research.ibm.com/cognitive-computing/machine-learning-applications/decision-support-education.shtml#fbid=eLh89r4FaS0
I’ve just Tweeted it on the BLOSSOMS Twitter site, as I agree 100% with the vision!

This just in from Ben Shaw (IBM):

Recent Press:

Samsung, Air Force, Lawrence Livermore Partnership: http://www.cnet.com/news/samsung-turns-ibms-brain-like-chip-into-a-digital-eye/
Misha Mahowald Prize: http://mahowaldprize.org/inaugural-misha-mahowald-prize-for-neuromorphic-engineering-won-by-ibm-truenorth-project/
Computer History Museum: http://www-03.ibm.com/press/us/en/pressrelease/50350.wss
16-Chip System: http://www-03.ibm.com/press/us/en/pressrelease/49424.wss
Boot Camp: http://www.wired.com/2015/08/ibms-rodent-brain-chip-make-phones-hyper-smart/

Papers:

ecosystem: https://dl.dropboxusercontent.com/u/91714474/Papers/030.Supercomputing%202016.pdf
convolution networks: http://arxiv.org/abs/1603.08270
backpropagation: https://papers.nips.cc/paper/5862-backpropagation-for-energy-efficient-neuromorphic-computing
architecture: http://www.sciencemag.org/content/345/6197/668.full.pdf
neuron model: http://www.research.ibm.com/software/IBMResearch/multimedia/IJCNN2013.neuron-model.pdf
applications: http://www.research.ibm.com/software/IBMResearch/multimedia/IJCNN2013.algorithms-applications.pdf
programming: http://www.research.ibm.com/software/IBMResearch/multimedia/IJCNN2013.corelet-language.pdf

Video:

Brain-inspired Computing: Dharmendra Modha, IBM Fellow and Principal Investigator
https://www.youtube.com/watch?v=UHPwIBiFVq0

Blog:

Blog: http://www.modha.org

Ken Goldberg just sent this excellent piece:

Multiplicity has More Potential Than Singularity
Ken Goldberg

Stephen Hawking, Bill Gates, and Elon Musk are extremely intelligent humans.  So it’s not surprising that the concerns they’ve recently raised about Artificial Intelligence (AI) surpassing human intelligence have generated widespread anxiety.  But fears of the “Singularity” are distracting attention from a far more important development: Multiplicity.

“Multiplicity” describes an emerging category of systems where diverse groups of humans work together with diverse groups of machines to solve difficult problems.  Multiplicity combines ideas from machine learning, the wisdom of crowds, and cloud computing.  Multiplicity is not science fiction; it’s central to systems we use everday: Twitter, Salesforce, Netflix, Siri, and Uber.

Consider the Internet search problem.  Given a word or two, find the relevant documents among billions and list them in order of importance.  Google’s solution requires a diverse set of algorithms and computing platforms.  It also requires ongoing input from a diverse group of humans, who make subtle decisions about content and links every time we post a tweet or update or create a web page. Humans also help Google’s search improve over time by providing ongoing feedback every time we click on one of the suggested links.

Google’s search engine is a Multiplicity system that requires a diverse group of machines and a diverse group of humans.  Multiplicity is also essential for the movie and book recommendations provided by Netflix and Amazon, for Facebook’s News Feed, and for Apple’s Siri voice recognition system.  Most of the recent progress in AI, for robot driving and “deep learning” networks for understanding images and video, can be characterized in terms of Multiplicity: rather than eliminating humans, our input and feedback will play a vital ongoing role.

Multiplicity systems are extremely complex and much more research is needed to effectively combine groups of machines, groups of humans, and groups of both.  We need new statistical machine learning methods that combine input from an ensemble of algorithms.  Recent results in Ensemble Learning [1] show that a sufficiently diverse group of algorithms, each tuned to different subspaces of inputs, will be better at classification than any single algorithm.

Although Economics, Psychology, Political Science, and Sociology study group behavior at different scales, more research is needed on how humans with complementary skills can be brought together to solve problems.  It was recently shown that the diversity of a group is more important than its total IQ for collective problem-solving [2, 3]. New Research is needed on how to effectively integrate the skills of human groups with the power of cloud computing.  One example is Cloud Robotics, where demonstrations from diverse groups of humans are shared over the Cloud and combined using statistical machine learning techniques such as Partially Observed Markov Decision Processes (POMDPs) to produce policies that maximize the probability of success and self-monitor to alert humans when confidence decreases [4].  This plays an important role in Google’s approach to self-driving cars.

Multiplicity is neither science fiction nor an existential threat to humanity.  It supports many of the most sophisticated and effective systems we use every day and it involves us rather than excludes us. But Multiplicity is not yet well understood.  It deserves our attention.

Ken Goldberg is UC Berkeley Professor of Engineering.
http://goldberg.berkeley.edu

==
Summary (and video) of presentation at the world Economic Forum in January 2015:
https://amplab.cs.berkeley.edu/news/ken-goldberg-at-davos-forget-singularity-lets-talk-multiplicity/

Short Essay in Medium.com:
http://j.mp/medium-multiplicity

References

[1]: http://www.scholarpedia.org/article/Ensemble_learning

[2]: http://www.chabris.com/Woolley2010a.pdf

[3]: http://connection.mit.edu/

[4]: http://goldberg.berkeley.edu/cloud-robotics/

This just in:

CFP: Systems Journal

Dear Dr. Spohrer,

The journal Systems (ISSN 2079-8954) is currently running a Special Issue entitled “Service Systems”.

Prof. Dr. Francesco Polese, Dr. Luca Carrubbo, and Dr. Orlando Troisi, all of the University of Salerno, Fisciano (SA), Italy, are serving as Guest Editors for this issue. We think you could make an excellent contribution based on your expertise and your following paper:

Toward a Research Agenda for Human-Centered Service System Innovation. SERVICE SCIENCE 2015, 7, 1-10.

This Special Issue on Service Systems deals with the concept of Service Systems and Smart Service Systems, understood as the result of a synergic integration between two different but closely related research fields: the Systems Theories (GST and its follow up) and the Service Science, Management, Engineering and Design (SSMED). […]

For further reading, please follow the link to the Special Issue Website at: http://www.mdpi.com/si/systems/service_systems.

The submission deadline is 31 December 2016. You may send your manuscript now or up until the deadline. Submitted papers should not be under consideration for publication elsewhere. We also encourage authors to send a short abstract or tentative title to the Editorial Office in advance (systems@mdpi.com).

Systems is fully open access. Open access (unlimited and free access by readers) increases publicity and promotes more frequent citations, as indicated by several studies. Open access is supported by the authors and their institutes. No Article Processing Charges (APC) apply for well-prepared manuscripts.

For further details on the submission process, please see the instructions for authors at the journal website.

We look forward to hearing from you.

Kind regards,

Ms. Weina Li
Managing Editor

Systems (ISSN 2079-8954; http://www.mdpi.com/journal/systems) is a journal published by MDPI AG, Basel, Switzerland. Systems maintains rigorous peer-review and a rapid publication process. All articles are published with a CC BY 4.0 license. For more information on the CC BY license, please see: http://creativecommons.org

This just in from Marialuisa Saviano…

Dear Colleagues,
as anticipated during our last email interaction for the paper to be published in JOSM, we are very pleased to announce you the next WOSC Congress that will be held in Rome at Sapienza, 25-27 January 2017, in collaboration between the World Organisation of Systems and Cybernetics (WOSC) and the Association for research on Viable Systems (ASVSA).
We cordially invite you to join the Congress and would be very grateful if you could share this announcement and the following Call for Abstracts with your colleagues and friends.
Looking forward to seeing you in Rome,
Kind regards,
Sergio Barile
WOSC 2017 Chair
Marialuisa Saviano
WOSC 2017 General Coordinator

WOSC 2017 Call for Abstracts

Dear Friends and Colleagues
We are happy to invite you to join us at the WOSC 17th Congress:
Science with and for Society –
Contributions of Cybernetics and Systems

Please, visit the website http://wosc2017rome.asvsa.org/ for further information.

WOSC 2017, the 17th Congress of World Organisation of Systems and Cybernetics, will offer a space for conversations about social dynamics from a cyber-systemic perspective.
Its realisation is supported by a network of scientists from different parts of the world, which foretells an event more integrated than the usual running of parallel tracks.
The construction of its agenda has been highly participative; efforts have been made to support diversity within the shared thematic of Science with and for Society. In particular, we want to focus on challenges of the 21st century.
We will welcome submissions of extended abstracts, focused on any of the Congress´s 16 tracks, which have been organised in three themes.
Themes and tracks
Theme1: People, technology and governance for sustainability
1. Human aspects of managing systems
2. Smartness and sustainability
3. Smart technologies and big data
4. The Brain of the future
5. Governance in the Anthropocene: cybersystemic possibilities
Theme 2: Democracy, interactions and organisation
6. Community self-organization
7. Democracy and transparency
8. Interactions revolution: how to harmonise interactions within and between complex adaptive systems
9. Law, commons, social dynamics
10. Knowledge to manage the knowledge society: non explicit, non invasive and non directive management
11. The role of emergence within organizations
12. The role of Higher Education for Sustainable Development
Theme 3: Cyber-systemic thinking, modelling and epistemology
13. How can systems thinking help to bring solutions to humankind problems in the 21st century?
14. Think outside the box with Systems Dynamics
15. Quantum Modelling
16. Reflexivity, Second order science, and Context
Submitting an abstract:
Submitted and accepted extended abstracts, presented at the Congress will be published in the “WOSC 2017 Book of Abstracts”.
In order to submit an extended abstract, authors need to consider Author Guidelines
Refereed Publication of Congress papers
Authors with an accepted abstract will be invited to submit a full research paper and attend the Congress. Papers, presented at the Congress, will be considered for the publication in one of the following journals:
• Kybernetes,
• International Journal of Systems and Society,
• Futures,
• International Journal of Markets and Business Systems
Further leading journals are under consideration for Special Issues. Please, follow updates on the website.
Instructions for full paper submission will be available in Instructions for Full Paper Submissions in the Submission option of the website.
Summary of Congress Schedule
• 30 August 2016: extended abstracts submission deadline
• 15 October 2016: notification of acceptance
• 15 November 2016: early registration deadline
• 15 November 2016: registration deadline for accepted authors
• 20 December 2016: tentative congress program
• 10 January 2017: full papers submission
• 15 January 2017: official congress program
• 25-27 January 2017: WOSC 2017 Congress
Please register on http://wosc2017rome.asvsa.org/

Looking forward to seeing you in Rome,
Professor Raul Espejo
Scientific Director WOSC 2017
Director General of the WOSC
http://www.wosc.co
Professor Sergio Barile
Chair WOSC 2017
Sapienza, University of Rome
www.uniroma1.it

Prof. Irene Ng (UK, U Warwick) wrote in Scientific American opinion blog:

Google, Facebook and most other big tech companies don’t typically give customers exclusive custodial rights over their data. As threats to their security and reputations mount, however, these companies are starting to change their tune. In the case of Whatsapp, Facebook still retains customer metadata that can be used for ad targeting but has essentially locked itself out of customer messages. As with Apple, it’s unclear whether this approach shields Facebook from having to unlock encrypted Whatsapp messages if the government demands it.

All of this uncertainty opens the door to new types of services that allow people to store personal information apart from the Apples and Googles of the world. The HAT Foundation’s “hub of all things” project, for example, offers the equivalent of a personal Internet data container—sometimes referred to as a microservice container—and lets people set the terms for how businesses, Web sites and others online services contribute to and access this data.

Here is Irene’s article

http://blogs.scientificamerican.com/guest-blog/what-the-apple-versus-fbi-debacle-taught-us/

Her blog on HAT and rights

HATs and Rights

Irene Ng

Director, International Institute of Product and Service Innovation
Professor of Marketing and Service Systems
WMG, University of Warwick
ESRC/InnovateUK Innovation Caucus Thought leader
http://www.ireneng.com

This just in from Christoph Breidbach:

Jim,

I very much enjoy reading through service-science.info and was hoping that you could include a CfP on the page.

My colleagues Daviel Beverungen, Jens Poeppelbuss, Virpi Tuunainen and I are editing a Special Issue on

‘Smart Service Systems: An Interdisciplinary Perspective’ for the Information Systems Journal.

The CfP is attached. You can also find it here:

http://onlinelibrary.wiley.com/store/10.1111/(ISSN)1365-2575/asset/homepages/ISJ_SI_Smart_Service_Systems.pdf?v=1&s=ad591e2aaf7ec78f31c424c12184c15ef8721922&isAguDoi=false

If you do have any questions, please let me know.

Thank you,

Christoph

Dr Christoph Breidbach
Lecturer, Department of Computing and Information Systems
Melbourne School of Engineering
The University of Melbourne, Victoria 3010
T: +61 383 442 987 | E: christoph.breidbach@unimelb.edu.au W: www.cis.unimelb.ed.au

Currently, I am working on a new “science of cognitive computing” curriculum for IBM with our partner universities and others to allow people of all ages to design, build, understand, and work with cognitive mediators.  The curriculum is inspired in part by the work of Douglas Engelbart, an American engineer and inventor, and an early computer and Internet pioneer, who urged us to work quickly to augment human intellect to address complex, urgent problems.

Initially,  we plan to use the curriculum to show people how to design and build cognitive mediators that augment their personal and professional memories and suggest profitable connections and conversations between people – a type of relationship-oriented computing.   Later, we plan to use the curriculum to help people understand how intelligence (capabilities to perform useful tasks) develops in people and machines using specific data sets and learning algorithms, both unsupervised (evolution) and supervised (culture).  Finally, we plan to use the curriculum to help people explore how best to work with their cognitive mediators, individually and collectively.

Cognitive mediators begin to address some of the problems associated with “bounded rationality” in decision making – the condition noted by Herbert Simon, a Nobel Prize laureate, was an American political scientist, economist, sociologist, psychologist, and computer scientist whose research ranged across the fields of cognitive psychology, cognitive science, computer science, public administration, economics, management, philosophy of science, sociology, and political science, unified by studies of decision-making.     Cognitive mediators can help facilitate value co-creation and capability co-elevation interactions between entities at multiple scales.

People with their cognitive mediators can be thought of as systems in networks.  For example, a smart service system can be viewed as a type of sociotechnical system in which most people are augmented with cognitive mediators to get and give service offerings.    A wise service system goes beyond smart, to improve multi-scale entity interaction opportunities generation over generation improving individual and collective quality of life into the future.

Ideally, the new curriculum will inspire students and professionals to see the world more like Douglas Engelbart (opportunity to augmented the intellect of people individually and collectively to address complex, urgent problems) and Herbert Simon did (opportunity to use physical-symbol-systems to overcome some of the challenges faced by people with bounded rationality, who are making decisions in diverse types of organizations, ranging from families to businesses to nations).  They both had a transdisciplinary or future-ready T-shaped perspective, and saw the world as interacting physical-symbol-systems with great potential to use technology to improve how people interact with each other in organizations.  They both saw the world as people interacting socially and economically to solve problems, with more and more advanced technologies being designed to facilitate those interactions.  Technology was seen by both Engelbart and Simon as a great enabler of improved interactions and decision-making between people in business and society, especially value co-creation and capability co-elevation interactions between entities at multiple scales, personal, business, and national levels of entity interactions.

A goal of some members of the artificial intelligence community is develop intelligent entities with self-awareness, and the capability to collectively establish appropriate, ethical rights and responsibilities between intelligent interacting entities. The best/classic starting point is the book The Sciences of the Artificial.  For modern techniques, see the book  Artificial Intelligence: A Modern Approach.  A good/classic starting point to understand self-awareness in intelligent systems (physical-symbol-systems) is the online article Cognitive Economy.

A goal of some members of the cognitive science community is to understand the development and functioning of intelligence in people.  The best/classic starting points are the two books Scripts, Plans, Goals and Understanding: An Inquiry into Human Knowledge Structures and Things That Make Us Smart: Defending Human Attributes in the Age of the Machine, as well as the online article Augmenting Human Intellect: A Conceptual Framework.

A goal of the community developing the new curriculum is to help all interested people design-build, understand, and work with their own personal cognitive mediator, to augment human intellect to address complex, urgent problems (Engelbart) and to systematically address some of the problems of bounded-rationality in decision-making (Simon).  Recently, it has been suggested that the development of Software Social Organisms: Implications for Measuring AI Progress has benefits for the advancement of knowledge in all academic disciplines.

IBM has initially termed the new curriculum – “the science of cognitive computing.”

However, more broadly the new curriculum is intended to empower all interested people to learn about the design, engineering, management, public policy, and especially the science of personal and professional cognitive mediators (intelligent systems, cognitive computing, smart machines) for all business and societal roles.

The curriculum will be especially useful to learners who wish to understand and enhance the beneficial impact of cognitive mediators in business and society as part of smart service systems.  The curriculum is being developed with the intention to help everyone understand and benefit from intelligent technology (cognitive computing) that enables the use of personal and professional cognitive mediators to enhance social and economic interactions between people.

References:

* Spohrer J, Banavar G (2015). Cognition as a Service: An Industry Perspective. AI Magazine. 36(4): 71-86.

* The complete Winter 2015 issue of  AI Magazine can be accessed here: http://www.aaai.org/ojs/index.php/aimagazine/issue/view/212/showToc

* Spohrer J (2016). Innovation for Jobs with Cognitive Assistants: A Service Science Perspective.  In “Disrupting Unemployment: Reflection on a Sustainable, Middle Class Economic Recovery,” editors Nordfors D, Cerf V, Senges M. Kansas City, MO USA: Ewing Marion Kauffman Foundation. Pp. 157-174.

* The complete book is available on Amazon here  http://www.amazon.com/Disrupting-Unemployment-David-Nordfors/dp/152384583X

* Spohrer J, Bassano C, Piciochhi P, Siddike MAK (2016). What Marks a System Smart? Wise? Proceedings of AHFE Human-Side of Service Engineering (HSSE) Conference.

* The concept of smart service system has been an exploratory development of the USA National Science Foundation, and a number of major universities and companies, and government organizations from around the world.

* MIT-NSF Event: http://web.mit.edu/mitssrc/nsf/

* NSF LinkedIn group: https://www.linkedin.com/groups/5109582

* HICSS Conference tracks: https://www.linkedin.com/pulse/innovations-smart-service-systems-analytics-big-data-haluk-demirkan

A colleague of mine, whom I have great respect for, just sent a fascinating email to a group of global computer science researchers as well as social science and policy making scholars.  He wrote in part:

Building robust cognitive systems requires moving beyond task-specific systems, to cognitive architectures where the same system (1) handles multiple tasks, (2) takes an active role in its own learning, and (3) does so over weeks, months, and years without humans who understand its internals in the loop.  Of those three things, the first has been done to a limited degree, in that cognitive architectures are capable of doing many tasks.

>>> Opinion: For those with more time to read…

I agree with: “(1) handles multiple tasks, (2) takes an active role in its own learning,”

I disagree with: “(3) does so over weeks, months, and years without humans who understand its internals in the loop.”

Our processes for building robust cognitive systems in academia, industry, and government are not open, agile, or thoughtful enough yet to make rapid and purposeful progress IMHO.

A new teaching curriculum for education, a new discovery process for research, and a new political philosophy for why we are doing this work for economic and societal good are all three much needed.

Picture instead a large population of cognitive entities cooperating…  watching and learning from each other – both people and machines.

Reframing “taking an active role its own learning” as Computer-Supported Collaborative Work (CSCW) for test-taking machines and people would greatly accelerate purposeful progress.

=== Reframing hard problems with better processes: A good example

For those with an interest in reframing hard problems with better processes – this is a good example and fun read (though I prefer learn-faster to fail-quicker in the title)…

See: http://www.fastcodesign.com/1663488/wanna-solve-impossible-problems-find-ways-to-fail-quicker

MacCready’s insight was that everyone who was working on solving human-powered flight would spend upwards of a year building an airplane on conjecture and theory without a base of knowledge based on empirical tests. Triumphantly, they would complete their plane and wheel it out for a test flight. Minutes later, a year’s worth of work would smash into the ground.

Even in successful flights, the flight would end with the pilot physically exhausted just a couple hundred meters later. With that single new data point, the team would work for another year to rebuild, re-test, and re-learn. Progress was slow for obvious reasons, but that was to be expected in pursuit of such a difficult vision. That’s just how it was, went the common thinking.

The problem was the problem. MacCready realized that what needed to be solved was not, in fact, human-powered flight. That was a red herring. The problem was the process itself. And a negative side effect was the blind pursuit of a goal without a deeper understanding of how to tackle deeply difficult challenges. He came up with a new problem that he set out to solve: How can you build a plane that could be rebuilt in hours, not months?

===

By thoughtful and purposeful, I mean simultaneously improving people’s skills and machines’ capabilities, in this case for taking-tests.

“Why do one and not both?” Prof. Elliot Soloway (then at Yale, now at University of Michigan) once asked me.

This is the question that shifted my research work at Yale in the 1980’s from building intelligent systems to building tutoring systems with better student models.

Masters research:
Spohrer JC, Riesbeck CK. 1984. ESAU ( Economic Story Analyzer and Understanding): Reasoning-driven memory modification in the economics domain. Yale University. Department of Computer Science.

Doctoral research & later book.
Spohrer, J.C., 1989. Marcel: a generate-test-and-debug (gtd) impasse/repair model of student programmers. Yale University. Department of Computer Science.

Spohrer JC. 1992. MARCEL: Simulating the novice programmer.  Intellect Books.

Done right, with the right processes,  it is possible to accelerate progress both for people’s skills and machines’ capabilities – value co-creation and capability co-elevation is the basis of service science, an area I have been researching for several years now: https://scholar.google.com/citations?user=7T2Pz1YAAAAJ

New teaching curriculum, discovery process, and political philosophy are much needed IMHO.

Engelbart at work

Shared on Facebook, a yound Doug Engelbart having fun

Of course, this was the focus of the life work of Doug Engelbart, see Augmenting Human Intellect, whom I met when I arrived in Silicon Valley in the 1990’s.   Attaching two photographs of Doug – one at work and one when he was much younger

>>>

Startups are hard work and most will fail.

However,  most students and early career professionals will become more future-ready T-shaped adaptive innovators if they work hard and learn fast at one or more startups.

Steve Miller (IBM Analytics) sent me these interesting reads:

Check out one experience about how hard it really is to spin up a company.
http://techcrunch.com/2016/04/28/bitlock-crowdfunded-a-smart-bike-lock-in-2013-what-happened-next

Then there’s this.
http://www.theverge.com/2015/11/18/9758214/coolest-cooler-amazon-kickstater-shipping-production-delay

A good list of successful ones in terms of raising money.

https://en.wikipedia.org/wiki/List_of_highest_funded_crowdfunding_projects