vision/possibilities

From DSC:
Not too long ago, I really enjoyed watching a program on PBS regarding America’s 100 most-loved books, entitled, “The Great American Read.”

Watch “The Grand Finale”

While that’s not the show I’m talking about, it got me to thinking of one similar to it — something educational, yet entertaining. But also, something more.

The program that came to my mind would be a program that’s focused on significant topics and issues within American society — offered up in a debate/presentation style format.

For example, you could have different individuals, groups, or organizations discuss the pros and cons of an issue or topic. The show would provide contact information for helpful resources, groups, organizations, legislators, etc. These contacts would be for learning more about a subject or getting involved with finding a solution for that problem.

For example, how about this for a potential topic: Grades or no grades?

What are the pros and cons of using an A-F grading system?
What are the benefits and issues/drawbacks with using grades?
How are we truly using grades Do we use them to rank and compare individuals, schools, school systems, communities? Do we use them to “weed people out” of a program?
With our current systems, what “product” do we get? Do we produce game-players or people who enjoy learning? (Apologies for some of my bias showing up here! But my son has become a major game-player and, likely, so did I at his age.)
How do grades jibe with Individualized Education Programs (IEPs)? On one hand…how do you keep someone moving forward, staying positive, and trying to keep learning/school enjoyable yet on the other hand, how do you have those grades mean something to those who obtain data to rank school systems, communities, colleges, programs, etc.?
How do grades impact one’s desire to learn throughout one’s lifetime?

…

Such debates could be watched by students and then they could have their own debates on subjects that they propose.

Or the show could have journalists debate college or high school teams. The format could sometimes involve professors and deans debating against researchers. Or practitioners/teachers debating against researchers/cognitive psychologists.

Such a show could be entertaining, yet highly applicable and educational. We would probably all learn something. And perhaps have our eyes opened up to a new perspective on an issue.

Or better yet, we might actually resolve some more issues and then move on to address other ones!

How long before this type of thing is standard in smart classrooms & learning hubs? [Christian]

On 12/20/2018, in A/V -- audio/visual, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, Daniel S. Christian, education technology, emerging technologies, face-to-face, faculty/staff, future, future of higher education, human-computer interaction (HCI), ideas, innovation, intelligent systems, learning, learning ecosystem, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning spaces, machine-to-machine communications, multimedia, Natural Language Processing (NLP), Near Field Communication (NFC), personalized/customized learning, platforms, smart classrooms, teachers, teaching & learning, technologies for your home, technology (general), tools, universities, user experience (UX), vision/possibilities, by Daniel Christian

From DSC:
When a professor walks into the room, the mobile device that the professor is carrying notifies the system to automatically establish his or her preferred settings for the room — and/or voice recognition allows a voice-based interface to adjust the room’s settings:

The lights dim to 50%
The projector comes on
The screen comes down
The audio is turned up to his/her liking
The LMS is logged into with his/her login info and launches the class that he/she is teaching at that time of day
The temperature is checked and adjusted if too high or low
Etc.

Forecast 5.0 – The Future of Learning: Navigating the Future of Learning [Prince, Swanson, & King]

On 12/08/2018, in 21st century, adjunct faculty, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, change, colleges, community colleges, data related items, digital learning, education, education technology, emerging technologies, formal learning, future, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, instructional design, intelligent systems, intelligent tutoring, internet, leadership, learning, learning ecosystem, Learning from the Living [Class] Room, learning spaces, mobile learning, multimedia, Natural Language Processing (NLP), online learning, online tutoring, pace of change, parents/guardians, personalized/customized learning, platforms, science, smart classrooms, social learning / networks, social media, society, sociology, student teaching/teacher education, student-related, teachers, teaching & learning, teaching online, technology (general), tools, trends, United States, universities, virtual tutoring, vision/possibilities, web-based collaboration, by Daniel Christian

Forecast 5.0 – The Future of Learning: Navigating the Future of Learning — from knowledgeworks.org by Katherine Prince, Jason Swanson, and Katie King
Discover how current trends could impact learning ten years from now and consider ways to shape a future where all students can thrive.

AI Now Report 2018: 10 Recommendations for AI [AI Now Institute]

On 12/07/2018, in 21st century, Amazon, Apple, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, change, colleges, community colleges, computer science, corporate / business world, emerging technologies, ethics, Facebook / Meta Platforms, future, game-changing environment, Google, higher education, human-computer interaction (HCI), IBM, ideas, innovation, intelligent systems, internet, law schools, legislatures / government / legal, machine-to-machine communications, Microsoft, morals/values, pace of change, platforms, programming, society, sociology, surviving, technologies for your home, technology (general), the downsides of how people use tech, tools, trends, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

AI Now Report 2018 | December 2018 — from ainowinstitute.org

Meredith Whittaker , AI Now Institute, New York University, Google Open Research
Kate Crawford , AI Now Institute, New York University, Microsoft Research
Roel Dobbe , AI Now Institute, New York University
Genevieve Fried , AI Now Institute, New York University
Elizabeth Kaziunas , AI Now Institute, New York University
Varoon Mathur , AI Now Institute, New York University
Sarah Myers West , AI Now Institute, New York University
Rashida Richardson , AI Now Institute, New York University
Jason Schultz , AI Now Institute, New York University School of Law
Oscar Schwartz , AI Now Institute, New York University

With research assistance from Alex Campolo and Gretchen Krueger (AI Now Institute, New York University)

Excerpt (emphasis DSC):

Building on our 2016 and 2017 reports, the AI Now 2018 Report contends with this central problem, and provides 10 practical recommendations that can help create accountability frameworks capable of governing these powerful technologies.

Governments need to regulate AI by expanding the powers of sector-specific agencies to oversee, audit, and monitor these technologies by domain.
Facial recognition and affect recognition need stringent regulation to protect the public interest.
The AI industry urgently needs new approaches to governance. As this report demonstrates, internal governance structures at most technology companies are failing to ensure accountability for AI systems.
AI companies should waive trade secrecy and other legal claims that stand in the way of accountability in the public sector.
Technology companies should provide protections for conscientious objectors, employee organizing, and ethical whistleblowers.
Consumer protection agencies should apply “truth-in-advertising” laws to AI products and services.
Technology companies must go beyond the “pipeline model” and commit to addressing the practices of exclusion and discrimination in their workplaces.
Fairness, accountability, and transparency in AI require a detailed account of the “full stack supply chain.”
More funding and support are needed for litigation, labor organizing, and community participation on AI accountability issues.
University AI programs should expand beyond computer science and engineering disciplines. AI began as an interdisciplinary field, but over the decades has narrowed to become a technical discipline. With the increasing application of AI systems to social domains, it needs to expand its disciplinary orientation. That means centering forms of expertise from the social and humanistic disciplines. AI efforts that genuinely wish to address social implications cannot stay solely within computer science and engineering departments, where faculty and students are not trained to research the social world. Expanding the disciplinary orientation of AI research will ensure deeper attention to social contexts, and more focus on potential hazards when these systems are applied to human populations.

Also see:

After a Year of Tech Scandals, Our 10 Recommendations for AI — from medium.com by the AI Now Institute
Let’s begin with better regulation, protecting workers, and applying “truth in advertising” rules to AI

Also see:

Excerpt:

As we discussed, this technology brings important and even exciting societal benefits but also the potential for abuse. We noted the need for broader study and discussion of these issues. In the ensuing months, we’ve been pursuing these issues further, talking with technologists, companies, civil society groups, academics and public officials around the world. We’ve learned more and tested new ideas. Based on this work, we believe it’s important to move beyond study and discussion. The time for action has arrived.

We believe it’s important for governments in 2019 to start adopting laws to regulate this technology. The facial recognition genie, so to speak, is just emerging from the bottle. Unless we act, we risk waking up five years from now to find that facial recognition services have spread in ways that exacerbate societal issues. By that time, these challenges will be much more difficult to bottle back up.

In particular, we don’t believe that the world will be best served by a commercial race to the bottom, with tech companies forced to choose between social responsibility and market success. We believe that the only way to protect against this race to the bottom is to build a floor of responsibility that supports healthy market competition. And a solid floor requires that we ensure that this technology, and the organizations that develop and use it, are governed by the rule of law.

From DSC:
This is a major heads up to the American Bar Association (ABA), law schools, governments, legislatures around the country, the courts, the corporate world, as well as for colleges, universities, and community colleges. The pace of emerging technologies is much faster than society’s ability to deal with them!

The ABA and law schools need to majorly pick up their pace — for the benefit of all within our society.

Alexa, get me the articles (voice interfaces in academia) [Dagan]

On 12/04/2018, in 21st century, Amazon, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, communities of practice, community colleges, heutagogy, higher education, human-computer interaction (HCI), ideas, innovation, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning spaces, lifelong learning, Natural Language Processing (NLP), platforms, research, society, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, trends, universities, usability, user experience (UX), vendors, vision/possibilities, voice recognition / voice enabled interfaces, by Daniel Christian

Alexa, get me the articles (voice interfaces in academia) — from blog.libux.co by Kelly Dagan

Excerpt:

Credit to Jill O’Neill, who has written an engaging consideration of applications, discussions, and potentials for voice-user interfaces in the scholarly realm. She details a few use case scenarios: finding recent, authoritative biographies of Jane Austen; finding if your closest library has an item on the shelf now (and whether it’s worth the drive based on traffic).

Coming from an undergraduate-focused (and library) perspective, I can think of a few more:

asking if there are any group study rooms available at 7 pm and making a booking
finding out if [X] is open now (Archives, the Cafe, the Library, etc.)
finding three books on the Red Brigades, seeing if they are available, and saving the locations
grabbing five research articles on stereotype threat, to read later

Also see:

What Will Scholarly Information Providers Do About Voice User Interfaces (VUI)? — fromscholarlykitchen.sspnet.org by Jill O’Neill

LinkedIn Learning Opens Its Platform (Slightly) [Young]

On 11/09/2018, in 21st century, 24x7x365 access, adult learning, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, business side of he, career development, change, changing business models, cloud-based computing / apps / other cloud-related, collaboration, colleges, communities of practice, community colleges, competency-based learning/education, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, cost of getting a degree, credentialing, dangers of the status quo, Daniel S. Christian, data related items, digital learning, disruption, education technology, elearning, formal learning, future, future of higher education, game-changing environment, global / globalization, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, intelligent systems, intelligent tutoring, internet, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, lifelong learning, marketplaces, microlearning, Microsoft, mobile learning, more voice more choice more control, multimedia, online learning, online tutoring, pace of change, personalized/customized learning, platforms, professional development, social learning / networks, social media, society, staying relevant, streams of content, student-related, surviving, technologies for your home, training / L&D, trends, United States, universities, using teams, vendors, vision/possibilities, web-based collaboration, workplace, by Daniel Christian

LinkedIn Learning Opens Its Platform (Slightly) — from edsurge by Jeff Young

Excerpt (emphasis DSC):

A few years ago, in a move toward professional learning, LinkedIn bought Lynda.com for $1.5 billion, adding the well-known library of video-based courses to its professional social network. Today LinkedIn officials announced that they plan to open up their platform to let in educational videos from other providers as well—but with a catch or two.

The plan, announced Friday, is to let companies or colleges who already subscribe to LinkedIn Learning add content from a select group of other providers. The company or college will still have to subscribe to those other services separately, so it’s essentially an integration—but it does mark a change in approach.

For LinkedIn, the goal is to become the front door for employees as they look for micro-courses for professional development.

LinkedIn also announced another service for its LinkedIn Learning platform called Q&A, which will give subscribers the ability to pose a question they have about the video lessons they’re taking. The question will first be sent to bots, but if that doesn’t yield an answer the query will be sent on to other learners, and in some cases the instructor who created the videos.

Also see:

LinkedIn becomes a serious open learning experience platform — from clomedia.com by Josh Bersin
LinkedIn is becoming a dominant learning solution with some pretty interesting competitive advantages, according to one learning analyst.

Excerpt:

LinkedIn has become quite a juggernaut in the corporate learning market. Last time I checked the company had more than 17 million users, 14,000 corporate customers, more than 3,000 courses and was growing at high double-digit rates. And all this in only about two years.

And the company just threw down the gauntlet; it’s now announcing it has completely opened up its learning platform to external content partners. This is the company’s formal announcement that LinkedIn Learning is not just an amazing array of content, it is a corporate learning platform. The company wants to become a single place for all organizational learning content.

LinkedIn now offers skills-based learning recommendations to any user through its machine learning algorithms.

Is there demand for staying relevant? For learning new skills? For reinventing oneself?

Well…let’s see.

From DSC:
So…look out higher ed and traditional forms of accreditation — your window of opportunity may be starting to close. Alternatives to traditional higher ed continue to appear on the scene and gain momentum. LinkedIn — and/or similar organizations in the future — along with blockchain and big data backed efforts may gain traction in the future and start taking away some major market share. If employers get solid performance from their employees who have gone this route…higher ed better look out.

Microsoft/LinkedIn/Lynda.com are nicely positioned to be a major player who can offer society a next generation learning platform at an incredible price — offering up-to-date, microlearning along with new forms of credentialing. It’s what I’ve been calling the Amazon.com of higher ed (previously the Walmart of Education) for ~10 years. It will take place in a strategy/platform similar to this one.

Also, this is what a guerilla on the back looks like:

Also see:

Meet the 83-Year-Old App Developer Who Says Edtech Should Better Support Seniors — from edsurge.com by Sydney Johnson
Excerpt (emphasis DSC):
Now at age 83, Wakamiya beams with excitement when she recounts her journey, which has been featured in news outlets and even at Apple’s developer conference last year. But through learning how to code, she believes that experience offers an even more important lesson to today’s education and technology companies: don’t forget about senior citizens.Today’s education technology products overwhelmingly target young people. And while there’s a growing industry around serving adult learners in higher education, companies largely neglect to consider the needs of the elderly.

Introducing several new ideas to provide personalized, customized learning experiences for all kinds of learners! [Christian]

On 11/06/2018, in 21st century, 24x7x365 access, accessibility / UDL, adjunct faculty, analytics, Artificial Intelligence/Agents/LLMs/and Related, assistive technologies, attention, blended learning, bots, cloud-based computing / apps / other cloud-related, colleges, community colleges, content development, aggregation, repositories, Daniel S. Christian, digital learning, e-books, e-publishing related items (EPUB and more), e-readers, education, education technology, elearning, engagement / engaging students, face-to-face, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), hybrid learning, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, interaction design, interactivity, interface design, internet, K-12 related, law schools, learner profiles, learning, learning ecosystem, Learning from the Living [Class] Room, learning preferences, library / librarians, memory, more voice more choice more control, neurodivergent/special needs, personalized/customized learning, platforms, productivity / tips and tricks, reading, society, student-related, teachers, teaching & learning, technology (general), tools, traditional / tradition, training / L&D, universities, user experience (UX), user interface design, using teams, vendors, vision/possibilities, visualizing information, writing, youth, by Daniel Christian

From DSC:
I have often reflected on differentiation or what some call personalized learning and/or customized learning. How does a busy teacher, instructor, professor, or trainer achieve this, realistically?

It’s very difficult and time-consuming to do for sure. But it also requires a team of specialists to achieve such a holy grail of learning — as one person can’t know it all. That is, one educator doesn’t have the necessary time, skills, or knowledge to address so many different learning needs and levels!

Think of different cognitive capabilities — from students that have special learning needs and challenges to gifted students
Or learners that have different physical capabilities or restrictions
Or learners that have different backgrounds and/or levels of prior knowledge
Etc., etc., etc.

Educators and trainers have so many things on their plates that it’s very difficult to come up with _X_ lesson plans/agendas/personalized approaches, etc. On the other side of the table, how do students from a vast array of backgrounds and cognitive skill levels get the main points of a chapter or piece of text? How can they self-select the level of difficulty and/or start at a “basics” level and work one’s way up to harder/more detailed levels if they can cognitively handle that level of detail/complexity? Conversely, how do I as a learner get the boiled down version of a piece of text?

Well… just as with the flipped classroom approach, I’d like to suggest that we flip things a bit and enlist teams of specialists at the publishers to fulfill this need. Move things to the content creation end — not so much at the delivery end of things. Publishers’ teams could play a significant, hugely helpful role in providing customized learning to learners.

Some of the ways that this could happen:

Use an HTML like language when writing a textbook, such as:

<MainPoint> The text for the main point here. </MainPoint>

<SubPoint1>The text for the subpoint 1 here.</SubPoint1>

<DetailsSubPoint1>More detailed information for subpoint 1 here.</DetailsSubPoint1>

<SubPoint2>The text for the subpoint 2 here.</SubPoint2>

<DetailsSubPoint2>More detailed information for subpoint 2 here.</DetailsSubPoint2>

<SubPoint3>The text for the subpoint 3 here.</SubPoint3>

<DetailsSubPoint3>More detailed information for subpoint 3 here.</DetailsSubPoint1>

<SummaryOfMainPoints>A list of the main points that a learner should walk away with.</SummaryOfMainPoints>

<BasicsOfMainPoints>Here is a listing of the main points, but put in alternative words and more basic ways of expressing those main points. </BasicsOfMainPoints>

<Conclusion> The text for the concluding comments here.</Conclusion>

<BasicsOfMainPoints> could be called <AlternativeExplanations>
Bottom line: This tag would be to put things forth using very straightforward terms.

Another tag would be to address how this topic/chapter is relevant:
<RealWorldApplication>This short paragraph should illustrate real world examples
of this particular topic. Why does this topic matter? How is it relevant?</RealWorldApplication>

On the students’ end, they could use an app that works with such tags to allow a learner to quickly see/review the different layers. That is:

Show me just the main points
Then add on the sub points
Then fill in the details
OR
Just give me the basics via an alternative ways of expressing these things. I won’t remember all the details. Put things using easy-to-understand wording/ideas.

It’s like the layers of a Microsoft HoloLens app of the human anatomy:

Or it’s like different layers of a chapter of a “textbook” — so a learner could quickly collapse/expand the text as needed:

This approach could be helpful at all kinds of learning levels. For example, it could be very helpful for law school students to obtain outlines for cases or for chapters of information. Similarly, it could be helpful for dental or medical school students to get the main points as well as detailed information.

Also, as Artificial Intelligence (AI) grows, the system could check a learner’s cloud-based learner profile to see their reading level or prior knowledge, any IEP’s on file, their learning preferences (audio, video, animations, etc.), etc. to further provide a personalized/customized learning experience.

To recap:

“Textbooks” continue to be created by teams of specialists, but add specialists with knowledge of students with special needs as well as for gifted students. For example, a team could have experts within the field of Special Education to help create one of the overlays/or filters/lenses — i.e., to reword things. If the text was talking about how to hit a backhand or a forehand, the alternative text layer could be summed up to say that tennis is a sport…and that a sport is something people play. On the other end of the spectrum, the text could dive deeply into the various grips a person could use to hit a forehand or backhand.
This puts the power of offering differentiation at the point of content creation/development (differentiation could also be provided for at the delivery end, but again, time and expertise are likely not going to be there)
Publishers create “overlays” or various layers that can be turned on or off by the learners
Can see whole chapters or can see main ideas, topic sentences, and/or details. Like HTML tags for web pages.
Can instantly collapse chapters to main ideas/outlines.

“The global companies that failed to adapt to change.” [Rao] | DC: Higher ed likely has something to learn here.

On 11/05/2018, in 21st century, 24x7x365 access, active learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business side of he, colleges, community colleges, corporate / business world, cost of getting a degree, dangers of the status quo, Daniel S. Christian, future, future of higher education, game-changing environment, global / globalization, ideas, innovation, intelligent systems, internet, law schools, leadership, learning, learning ecosystem, Learning from the Living [Class] Room, MBA, new business models, organizational change, pace of change, reinvent, society, staying relevant, strategy, student-related, surviving, training / L&D, universities, vendors, vision/possibilities, workplace, by Daniel Christian

The global companies that failed to adapt to change. — from trainingmag.com by Professor M.S. Rao, Ph.D.

Excerpt:

Eastman Kodak, a leader for many years, filed for bankruptcy in 2012. Blockbuster Video became defunct in 2013. Similarly, Borders — one of the largest book retailers in the U.S. — went out of business in 2011. Why did these companies, which once had great brands, ultimately fail? It is because they failed to adapt to change. Additionally, they failed to unlearn and relearn.
…
Former GE CEO Jack Welch once remarked, “If the rate of change on the outside exceeds the rate of change on the inside, the end is near.” Thus, accept change before the change is thrust on you.
…
Leaders must adopt tools and techniques to adapt to change. Here is a blueprint to embrace change effectively:

Keep the vision right and straight, and articulate it effectively.
Create organizational culture conducive to bring about change.
Communicate clearly about the need to change.
Enlighten people about the implications of the status quo.
Show them benefits once the change is implemented.
Coordinate all stakeholders effectively.
Remove the roadblocks by allaying their apprehensions.
Show them small gains to ensure that entire change takes place smoothly without any resistance.

From DSC:
Though I’m not on board with all of the perspectives in that article, institutions of traditional higher education likely have something to learn from the failures of these companies….while there’s still time to change and to innovate.

“Affordable and at-scale” [Schroeder] + “Trends for the future of education with Jeff Selingo” [Steelcase]

On 10/31/2018, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assistive technologies, business side of he, career development, change, colleges, communities of practice, community colleges, computer science, cost of getting a degree, dangers of the status quo, digital learning, disruption, distance education, education, education reform, education technology, emerging technologies, face-to-face, future, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, intelligent systems, intelligent tutoring, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning spaces, lifelong learning, MOOCs -- Massive Open Online Courses, new business models, online learning, United States, universities, vendors, vision/possibilities, web-based collaboration, by Daniel Christian

Affordable and at-scale — from insidehighered.com by Ray Schroeder
Affordable degrees at scale have arrived. The momentum behind this movement is undeniable, and its impact will be significant, Ray Schroeder writes.

Excerpt (emphasis DSC):

How many times have we been told that major change in our field is on the near horizon? Too many times, indeed.

The promises of technologies and practices have fallen short more often than not. Just seven years ago, I was part of the early MOOC movement and felt the pulsating potential of teaching thousands of students around the world in a single class. The “year of the MOOC” was declared in 2012. Three years later, skeptics declared that the MOOC had died an ignominious death with high “failure” rates and relatively little recognition by employers.

However, the skeptics were too impatient, misunderstood the nature of MOOCs and lacked the vision of those at Georgia Tech, the University of Illinois, Arizona State University, Coursera, edX and scores of other institutions that have persevered in building upon MOOCs’ premises to develop high-quality, affordable courses, certificates and now, degrees at scale.

No, these degrees are not free, but they are less than half the cost of on-campus versions. No, they are not massive in the hundreds of thousands, but they are certainly at large scale with many thousands enrolled. In computer science, the success is felt across the country.

Georgia Tech alone has enrolled 10,000 students over all in its online master’s program and is adding thousands of new students each semester in a top 10-ranked degree program costing less than $7,000. Georgia Tech broke the new ground through building collaborations among several partners. Yet, that was just the beginning, and many leading universities have followed.

Also see:

Trends for the future of education with Jeff Selingo — from steelcase.com
How the future of work and new technology will make place more important than ever.

Excerpt:

Selingo sees artificial intelligence and big data as game changers for higher education. He says AI can free up professors and advisors to spend more time with students by answering some more frequently-asked questions and handling some of the grading. He also says data can help us track and predict student performance to help them create better outcomes. “When they come in as a first-year student, we can say ‘People who came in like you that had similar high school grades and took similar classes ended up here. So, if you want to get out of here in four years and have a successful career, here are the different pathways you should follow.’”

Academics Propose a ‘Blockchain University,’ Where Faculty (and Algorithms) Rule — from edsurge.com by Jeff Young

Excerpt:

A group of academics affiliated with Oxford University have proposed a new model of higher education that replaces traditional administrators with “smart contracts” on the blockchain, the same technology that drives Bitcoin and other cryptocurrencies.

“Our aim is to create a university in which the bulk of administrative tasks are either eliminated or progressively automated,” said the effort’s founders in a white paper released earlier this year. Those proposing the idea added the university would be “a decentralised, non-profit, democratic community in which the use of blockchain technology will provide the contractual stability needed to pursue a full course of study.”

Experiments with blockchain in higher education are underway at multiple campuses around the country, and many of researchers are looking into how to use the technology to verify and deliver credentials. Massachusetts Institute for Technology, for example, began issuing diplomas via blockchain last year.

The plan by Oxford researchers goes beyond digital diplomas—and beyond many typical proposals to disrupt education in general. It argues for a completely new framework for how college is organized, how professors are paid, and how students connect with learning. In other words, it’s a long shot.

But even if the proposed platform never emerges, it is likely to spur debates about whether blockchain technology could one day allow professors to reclaim greater control of how higher education operates through digital contracts.

The platform would essentially allow professors to organize their own colleges, and teach and take payments from students directly. “

Reflections on “Inside Amazon’s artificial intelligence flywheel” [Levy]

On 10/19/2018, in 21st century, 24x7x365 access, A/V -- audio/visual, Amazon, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, colleges, communities of practice, community colleges, competency-based learning/education, computer science, content development, aggregation, repositories, corporate / business world, cost of getting a degree, dangers of the status quo, Daniel S. Christian, data related items, digital learning, disruption, distance education, e-books, e-publishing related items (EPUB and more), e-readers, education, education reform, education technology, educational games / serious games, elearning, emerging technologies, engagement / engaging students, entrepreneurship, experimentation, future, future of higher education, game-changing environment, generational differences, global / globalization, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, interactivity, internet, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, library / librarians, lifelong learning, microlearning, mobile learning, MOOCs -- Massive Open Online Courses, more voice more choice more control, multimedia, Natural Language Processing (NLP), new business models, online learning, online media, online tutoring, personalized/customized learning, platforms, reinvent, second screen apps, social learning / networks, society, staying relevant, streams of content, student-related, surviving, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), vision/possibilities, voice recognition / voice enabled interfaces, workplace, by Daniel Christian

Inside Amazon’s artificial intelligence flywheel — from wired.com by Steven Levy
How deep learning came to power Alexa, Amazon Web Services, and nearly every other division of the company.

Excerpt (emphasis DSC):

Amazon loves to use the word flywheel to describe how various parts of its massive business work as a single perpetual motion machine. It now has a powerful AI flywheel, where machine-learning innovations in one part of the company fuel the efforts of other teams, who in turn can build products or offer services to affect other groups, or even the company at large. Offering its machine-learning platforms to outsiders as a paid service makes the effort itself profitable—and in certain cases scoops up yet more data to level up the technology even more.

It took a lot of six-pagers to transform Amazon from a deep-learning wannabe into a formidable power. The results of this transformation can be seen throughout the company—including in a recommendations system that now runs on a totally new machine-learning infrastructure. Amazon is smarter in suggesting what you should read next, what items you should add to your shopping list, and what movie you might want to watch tonight. And this year Thirumalai started a new job, heading Amazon search, where he intends to use deep learning in every aspect of the service.

“If you asked me seven or eight years ago how big a force Amazon was in AI, I would have said, ‘They aren’t,’” says Pedro Domingos, a top computer science professor at the University of Washington. “But they have really come on aggressively. Now they are becoming a force.”

Maybe the force.

From DSC:
When will we begin to see more mainstream recommendation engines for learning-based materials? With the demand for people to reinvent themselves, such a next generation learning platform can’t come soon enough!

Turning over control to learners to create/enhance their own web-based learner profiles; and allowing people to say who can access their learning profiles.
AI-based recommendation engines to help people identify curated, effective digital playlists for what they want to learn about.
Voice-driven interfaces.
Matching employees to employers.
Matching one’s learning preferences (not styles) with the content being presented as one piece of a personalized learning experience.
From cradle to grave. Lifelong learning.
Multimedia-based, interactive content.
Asynchronously and synchronously connecting with others learning about the same content.
Online-based tutoring/assistance; remote assistance.
Reinvent. Staying relevant. Surviving.
Competency-based learning.

We’re about to embark on a period in American history where career reinvention will be critical, perhaps more so than it’s ever been before. In the next decade, as many as 50 million American workers—a third of the total—will need to change careers, according to McKinsey Global Institute. Automation, in the form of AI (artificial intelligence) and RPA (robotic process automation), is the primary driver. McKinsey observes: “There are few precedents in which societies have successfully retrained such large numbers of people.”

Bill Triant and Ryan Craig

Also relevant/see:

Online education’s expansion continues in higher ed with a focus on tech skills — from educationdive.com by James Paterson

Dive Brief:

Online learning continues to expand in higher ed with the addition of several online master’s degrees and a new for-profit college that offers a hybrid of vocational training and liberal arts curriculum online.
Inside Higher Ed reported the nonprofit learning provider edX is offering nine master’s degrees through five U.S. universities — the Georgia Institute of Technology, the University of Texas at Austin, Indiana University, Arizona State University and the University of California, San Diego. The programs include cybersecurity, data science, analytics, computer science and marketing, and they cost from around $10,000 to $22,000. Most offer stackable certificates, helping students who change their educational trajectory.
Former Harvard University Dean of Social Science Stephen Kosslyn, meanwhile, will open Foundry College in January. The for-profit, two-year program targets adult learners who want to upskill, and it includes training in soft skills such as critical thinking and problem solving. Students will pay about $1,000 per course, though the college is waiving tuition for its first cohort.

AI Forces Shaping Work & Learning in 2030 [IFTF and Lumina Foundation]

On 10/18/2018, in 21st century, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, change, changing business models, colleges, community colleges, competency-based learning/education, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, future, future of higher education, game-changing environment, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, K-12 related, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, lifelong learning, personalized/customized learning, platforms, programming, society, staying relevant, student-related, technologies for your home, technology (general), tools, training / L&D, trends, United States, universities, vendors, vision/possibilities, by Daniel Christian

In the 2030 and beyond world, employers will no longer be a separate entity from the education establishment. Pressures from both the supply and demand side are so large that employers and learners will end up, by default, co-designing new learning experiences, where all learning counts.

OBJECTIVES FOR CONVENINGS

Identify the skills everyone will need to navigate the changing relationship between machine intelligence and people over the next 10-12 years.
Develop implications for work, workers, students, working learners, employers, and policymakers.
Identify a preliminary set of actions that need to be taken now to best prepare for the changing work + learn ecosystem.

Three key questions guided the discussions:

What are the LEAST and MOST essential skills needed for the future?
Where and how will tomorrow’s workers and learners acquire the skills they really need?
Who is accountable for making sure individuals can thrive in this new economy?

This report summarizes the experts’ views on what skills will likely be needed to navigate the work + learn ecosystem over the next 10–15 years—and their suggested steps for better serving the nation’s future needs.

In a new world of work, driven especially by AI, institutionally-sanctioned curricula could give way to AI-personalized learning. This would drastically change the nature of existing social contracts between employers and employees, teachers and students, and governments and citizens. Traditional social contracts would need to be renegotiated or revamped entirely. In the process, institutional assessment and evaluation could well shift from top-down to new bottom-up tools and processes for developing capacities, valuing skills, and managing performance through new kinds of reputation or accomplishment scores.

…

In October 2017, Chris Wanstrath, CEO of Github, the foremost code-sharing and social networking resource for programmers today, made a bold statement: “The future of coding is no coding at all.” He believes that the writing of code will be automated in the near future, leaving humans to focus on “higher-level strategy and design of software.” Many of the experts at the convenings agreed. Even creating the AI systems of tomorrow, they asserted, will likely require less human coding than is needed today, with graphic interfaces turning AI programming into a drag-and-drop operation.

Digital fluency does not mean knowing coding languages. Experts at both convenings contended that effectively “befriending the machine” will be less about teaching people to code and more about being able to empathize with AIs and machines, understanding how they “see the world” and “think” and “make decisions.” Machines will create languages to talk to one another.

…

Here’s a list of many skills the experts do not expect to see much of—if at all—in the future:

Coding. Systems will be self-programming.
Building AI systems. Graphic interfaces will turn AI programming into drag-and-drop operations.
Calendaring, scheduling, and organizing. There won’t be need for email triage.
Planning and even decision-making. AI assistants will pick this up.
Creating more personalized curricula. Learners may design more of their own personalized learning adventure.
Writing and reviewing resumes. Digital portfolios, personal branding, and performance reputation will replace resumes.
Language translation and localization. This will happen in real time using translator apps.
Legal research and writing. Many of our legal systems will be automated.
Validation skills. Machines will check people’s work to validate their skills.
Driving. Driverless vehicles will replace the need to learn how to drive.

Here’s a list of the most essential skills needed for the future:

Quantitative and algorithmic thinking.
Managing reputation.
Storytelling and interpretive skills.
First principles thinking.
Communicating with machines as machines.
Augmenting high-skilled physical tasks with AI.
Optimization and debugging frame of mind.
Creativity and growth mindset.
Adaptability.
Emotional intelligence.
Truth seeking.
Cybersecurity.

The rise of machine intelligence is just one of the many powerful social, technological, economic, environmental, and political forces that are rapidly and disruptively changing the way everyone will work and learn in the future. Because this largely tech-driven force is so interconnected with other drivers of change, it is nearly impossible to understand the impact of intelligent agents on how we will work and learn without also imagining the ways in which these new tools will reshape how we live.

An open letter to Microsoft and Google’s Partnership on AI [Leonhard]

On 10/12/2018, in 21st century, 24x7x365 access, Amazon, analytics, Apple, Artificial Intelligence/Agents/LLMs/and Related, Asia, Australia, bots, business, Canada, change, cloud-based computing / apps / other cloud-related, computer science, corporate / business world, data related items, emerging technologies, engineering, ethics, Europe, future, game-changing environment, Google, hearts -- matters of the heart, human-computer interaction (HCI), ideas, innovation, intelligent systems, internet, IT in HE, law schools, machine-to-machine communications, morals/values, platforms, robotics, society, technologies for your home, technology (general), the downsides of how people use tech, tools, trends, UK, United States, vendors, vision/possibilities, workplace, by Daniel Christian

An open letter to Microsoft and Google’s Partnership on AI — from wired.com by Gerd Leonhard
In a world where machines may have an IQ of 50,000, what will happen to the values and ethics that underpin privacy and free will?

Excerpt:

This open letter is my modest contribution to the unfolding of this new partnership. Data is the new oil – which now makes your companies the most powerful entities on the globe, way beyond oil companies and banks. The rise of ‘AI everywhere’ is certain to only accelerate this trend. Yet unlike the giants of the fossil-fuel era, there is little oversight on what exactly you can and will do with this new data-oil, and what rules you’ll need to follow once you have built that AI-in-the-sky. There appears to be very little public stewardship, while accepting responsibility for the consequences of your inventions is rather slow in surfacing.

In a world where machines may have an IQ of 50,000 and the Internet of Things may encompass 500 billion devices, what will happen with those important social contracts, values and ethics that underpin crucial issues such as privacy, anonymity and free will?

My book identifies what I call the “Megashifts”. They are changing society at warp speed, and your organisations are in the eye of the storm: digitization, mobilisation and screenification, automation, intelligisation, disintermediation, virtualisation and robotisation, to name the most prominent. Megashifts are not simply trends or paradigm shifts, they are complete game changers transforming multiple domains simultaneously.

If the question is no longer about if technology can do something, but why…who decides this?

Gerd Leonhard

From DSC:
Though this letter was written 2 years ago back in October of 2016, the messages, reflections, and questions that Gerd puts on the table are very much still relevant today. The leaders of these powerful companies have enormous power — power to do good, or to do evil. Power to help or power to hurt. Power to be a positive force for societies throughout the globe and to help create dreams, or power to create dystopian societies while developing a future filled with nightmares. The state of the human heart is extremely key here — though many will hate me saying that. But it’s true. At the end of the day, we need to very much care about — and be extremely aware of — the characters and values of the leaders of these powerful companies.

Also relevant/see:

Spray-on antennas will revolutionize the Internet of Things — from networkworld.com by Patrick Nelson
Researchers at Drexel University have developed a method to spray on antennas that outperform traditional metal antennas, opening the door to faster and easier IoT deployments.

From DSC:
Again, it’s not too hard to imagine in this arena that technologies can be used for good or for ill.

To higher ed: When the race track is going 180mph, you can’t walk or jog onto the track. [Christian]

On 09/25/2018, in 21st century, 24x7x365 access, accreditation, adult learning, analytics, Artificial Intelligence/Agents/LLMs/and Related, Augmented Reality (AR), Blockchain, bots, business side of he, career development, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, community colleges, competency-based learning/education, corporate / business world, corporate universities / corporate training, cost of getting a degree, curriculum, dangers of the status quo, Daniel S. Christian, digital learning, disruption, distance education, education reform, education technology, emerging technologies, engineering, entrepreneurship, future, future of higher education, game-changing environment, generational differences, global / globalization, heutagogy, higher education, human-computer interaction (HCI), IBM, ideas, innovation, intelligent systems, internet, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, lifelong learning, Mixed Reality (MR), more voice more choice more control, online learning, organizational change, pace of change, personalized/customized learning, platforms, professional development, robotics, science, social learning / networks, society, staying relevant, student-related, surviving, technologies for your home, technology (general), tools, training / L&D, TVs, universities, vendors, Virtual Reality (VR) / worlds / learning, vision/possibilities, web-based collaboration, XR - extended reality, by Daniel Christian

From DSC:
When the race track is going 180mph, you can’t walk or jog onto the track. What do I mean by that?

Consider this quote from an article that Jeanne Meister wrote out at Forbes entitled, “The Future of Work: Three New HR Roles in the Age of Artificial Intelligence:”*

This emphasis on learning new skills in the age of AI is reinforced by the most recent report on the future of work from McKinsey which suggests that as many as 375 million workers around the world may need to switch occupational categories and learn new skills because approximately 60% of jobs will have least one-third of their work activities able to be automated.

Go scan the job openings and you will likely see many that have to do with technology, and increasingly, with emerging technologies such as artificial intelligence, deep learning, machine learning, virtual reality, augmented reality, mixed reality, big data, cloud-based services, robotics, automation, bots, algorithm development, blockchain, and more.

From Robert Half’s 2019 Technology Salary Guide

How many of us have those kinds of skills? Did we get that training in the community colleges, colleges, and universities that we went to? Highly unlikely — even if you graduated from one of those institutions only 5-10 years ago. And many of those institutions are often moving at the pace of a nice leisurely walk, with some moving at a jog, even fewer are sprinting. But all of them are now being asked to enter a race track that’s moving at 180mph. Higher ed — and society at large — are not used to moving at this pace.

This is why I think that higher education and its regional accrediting organizations are going to either need to up their game hugely — and go through a paradigm shift in the required thinking/programming/curricula/level of responsiveness — or watch while alternatives to institutions of traditional higher education increasingly attract their learners away from them.

This is also, why I think we’ll see an online-based, next generation learning platform take place. It will be much more nimble — able to offer up-to-the minute, in-demand skills and competencies.

The below graphic is from:
Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages

* Three New HR Roles To Create Compelling Employee Experiences
These new HR roles include:

IBM: Vice President, Data, AI & Offering Strategy, HR
Kraft Heinz Senior Vice President Global HR, Performance and IT
SunTrust Senior Vice President Employee Wellbeing & Benefits

What do these three roles have in common? All have been created in the last three years and acknowledge the growing importance of a company’s commitment to create a compelling employee experience by using data, research, and predictive analytics to better serve the needs of employees. In each case, the employee assuming the new role also brought a new set of skills and capabilities into HR. And importantly, the new roles created in HR address a common vision: create a compelling employee experience that mirrors a company’s customer experience.

An excerpt from McKinsey Global Institute | Notes from the Frontier | Modeling the Impact of AI on the World Economy

Workers.
A widening gap may also unfold at the level of individual workers. Demand for jobs could shift away from repetitive tasks toward those that are socially and cognitively driven and others that involve activities that are hard to automate and require more digital skills.12 Job profiles characterized by repetitive tasks and activities that require low digital skills may experience the largest decline as a share of total employment, from some 40 percent to near 30 percent by 2030. The largest gain in share may be in nonrepetitive activities and those that require high digital skills, rising from some 40 percent to more than 50 percent. These shifts in employment would have an impact on wages. We simulate that around 13 percent of the total wage bill could shift to categories requiring nonrepetitive and high digital skills, where incomes could rise, while workers in the repetitive and low digital skills categories may potentially experience stagnation or even a cut in their wages. The share of the total wage bill of the latter group could decline from 33 to 20 percent.13 Direct consequences of this widening gap in employment and wages would be an intensifying war for people, particularly those skilled in developing and utilizing AI tools, and structural excess supply for a still relatively high portion of people lacking the digital and cognitive skills necessary to work with machines.

Aligning the business model of college with student needs: How WGU is disrupting higher education [Dunagan]

On 09/15/2018, in 21st century, 24x7x365 access, adjunct faculty, adult learning, business side of he, changing business models, cloud-based computing / apps / other cloud-related, colleges, community colleges, competency-based learning/education, cost of getting a degree, digital learning, disruption, education, education technology, elearning, faculty/staff, higher education, learning, learning ecosystem, Learning from the Living [Class] Room, lifelong learning, more voice more choice more control, online learning, society, staying relevant, student-related, teaching online, tools, United States, universities, using teams, vision/possibilities, by Daniel Christian

Aligning the business model of college with student needs: How WGU is disrupting higher education — from christenseninstitute.org by Alana Dunagan

Excerpt:

Since its inception, Western Governors University (WGU) has aimed to serve learners otherwise shut out of the traditional system. Now, the groundbreaking institution has both graduated 100,000 students and has over 100,000 students currently enrolled. These milestones demonstrate WGU’s ability to scale its high-quality, low-cost model, signaling a momentous shift in the higher education landscape.

In the mid-1990s, governors of 19 states across the western United States were concerned about bringing accessible college education to rural populations, especially working adults.These governors, led by Utah Governor Mike Leavitt, decided to explore building a new university to address the challenge. As the memorandum of understanding between those governors that officially marked the founding of WGU stated, “The strength and well-being of our states and the nation depend increasingly on a strong higher education system that helps individuals adapt to our rapidly changing economy and society. States must look to telecommunications and information technologies to provide greater access and choice to a population that increasingly must have affordable education and training opportunities and the certification of competency throughout their lives.”

Now in its third decade, WGU has students in every U.S. state and has over 100,000 enrolled students—a 230% increase since 2011.

Excerpts from their paper:

The potential of competency-based education
Competency-based education is an approach to learning that allows students to determine the pace of their learning and move ahead once they demonstrate mastery in a concept. As described by Clayton Christensen and Michelle Weise:

Competency-based programs have no time-based unit. Learning is fixed, and time is variable; pacing is flexible. Students cannot move on until they have demonstrated proficiency and mastery of each competency but are encouraged to try as many times as necessary to demonstrate their proficiency. Although skeptics may question the “rigor” behind an experience that allows students to keep trying until they have mastered a competency, this model is actually far more rigorous than the traditional model, as students are not able to flunk or get away with a merely average understanding of the material; they must demonstrate mastery—and therefore dedicated work toward gaining mastery—in any competency.

Competency-based education first took hold in the K-12 education system, but it is also growing in higher education. As of fall 2015, roughly 600 institutions were using or exploring competency-based programs in higher education.13 However, only a handful of institutions are using competency-based education exclusively and have designed their business models around it.

…

WGU offers programs across four industry areas: education, business, information technology, and healthcare. All of these programs are offered online; unlike most higher education institutions, WGU has no physical campus. Instead, it has invested heavily in a technology platform that allows it to deliver curriculum asynchronously, to wherever students are. In addition to its online platform, another unique aspect of WGU’s resources is its approach to faculty. In traditional institutions, faculty are responsible for academic research, course development, teaching, assessment, and advising students. Alternatively, WGU’s model unbundles the faculty role into component parts, with specialists in each role.

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