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.

 

 

 

LinkedIn Learning Opens Its Platform (Slightly) [Young]

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:

 

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.

 

 
 

Robots won’t replace instructors, 2 Penn State educators argue. Instead, they’ll help them be ‘more human.’ — from edsurge.com by Tina Nazerian

Excerpt:

Specifically, it will help them prepare for and teach their courses through several phases—ideation, design, assessment, facilitation, reflection and research. The two described a few prototypes they’ve built to show what that might look like.

 

Also see:

The future of education: Online, free, and with AI teachers? — from fool.com by Simon Erickson
Duolingo is using artificial intelligence to teach 300 million people a foreign language for free. Will this be the future of education?

Excerpts:

While it might not get a lot of investor attention, education is actually one of America’s largest markets.

The U.S. has 20 million undergraduates enrolled in colleges and universities right now and another 3 million enrolled in graduate programs. Those undergrads paid an average of $17,237 for tuition, room, and board at public institutions in the 2016-17 school year and $44,551 for private institutions. Graduate education varies widely by area of focus, but the average amount paid for tuition alone was $24,812 last year.

Add all of those up, and America’s students are paying more than half a trillion dollars each year for their education! And that doesn’t even include the interest amassed for student loans, the college-branded merchandise, or all the money spent on beer and coffee.

Keeping the costs down
Several companies are trying to find ways to make college more affordable and accessible.

 

But after we launched, we have so many users that nowadays if the system wants to figure out whether it should teach plurals before adjectives or adjectives before plurals, it just runs a test with about 50,000 people. So for the next 50,000 people that sign up, which takes about six hours for 50,000 new users to come to Duolingo, to half of them it teaches plurals before adjectives. To the other half it teaches adjectives before plurals. And then it measures which ones learn better. And so once and for all it can figure out, ah it turns out for this particular language to teach plurals before adjectives for example.

So every week the system is improving. It’s making itself better at teaching by learning from our learners. So it’s doing that just based on huge amounts of data. And this is why it’s become so successful I think at teaching and why we have so many users.

 

 

From DSC:
I see AI helping learners, instructors, teachers, and trainers. I see AI being a tool to help do some of the heavy lifting, but people still like to learn with other people…with actual human beings. That said, a next generation learning platform could be far more responsive than what today’s traditional institutions of higher education are delivering.

 

 

Google already knows what you did next summer — from bloomberg.com by Nikki Ekstein
The company’s new travel tools put the focus on artificial intelligence, helping to best predict what you’re going to love—no matter where you go.

Excerpt:

But it’s not a hotel or travel agency that’s cracking the golden acorn. It’s Google. The tech titan is leveraging its immense artificial intelligence and machine-learning capabilities to boost its travel offerings, which currently cover everything from flight and hotel search to activity recommendations, destination guides, and mapping services

The proof is in the pudding. Over the past few months, Google has quietly launched an array of travel-focused features and updates that highlight just how intuitive its AI technology has become. Put them all together and you’ll have enough reason to believe your next travel agent might just be a Google-powered bot.

 

Should self-driving cars have ethics? — from npr.org by Laurel Wamsley

Excerpt:

In the not-too-distant future, fully autonomous vehicles will drive our streets. These cars will need to make split-second decisions to avoid endangering human lives — both inside and outside of the vehicles.

To determine attitudes toward these decisions a group of researchers created a variation on the classic philosophical exercise known as “the Trolley problem.” They posed a series of moral dilemmas involving a self-driving car with brakes that suddenly give out…

 

 

 

Gartner: Immersive experiences among top tech trends for 2019 — from campustechnology.com by Dian Schaffhauser

Excerpt:

IT analyst firm Gartner has named its top 10 trends for 2019, and the “immersive user experience” is on the list, alongside blockchain, quantum computing and seven other drivers influencing how we interact with the world. The annual trend list covers breakout tech with broad impact and tech that could reach a tipping point in the near future.

 

 

 

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

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.

 

The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

 

 

 

 

 

 

 

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 Now Law and Policy Reading List — from medium.com by the AI Now Institute

Excerpt:

Data-driven technologies are widely used in society to make decisions that affect many critical aspects of our lives, from health, education, employment, and criminal justice to economic, social and political norms. Their varied applications, uses, and consequences raise a number of unique and complex legal and policy concerns. As a result, it can be hard to figure out not only how these systems work but what to do about them.

As a starting point, AI Now offers this Law and Policy Reading List tailored for those interested in learning about key concepts, debates, and leading analysis on law and policy issues related to artificial intelligence and other emerging data-driven technologies.

 

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.

 

 
 

Smart Machines & Human Expertise: Challenges for Higher Education — from er.educause.edu by Diana Oblinger

Excerpts:

What does this mean for higher education? One answer is that AI, robotics, and analytics become disciplines in themselves. They are emerging as majors, minors, areas of emphasis, certificate programs, and courses in many colleges and universities. But smart machines will catalyze even bigger changes in higher education. Consider the implications in three areas: data; the new division of labor; and ethics.

 

Colleges and universities are challenged to move beyond the use of technology to deliver education. Higher education leaders must consider how AI, big data, analytics, robotics, and wide-scale collaboration might change the substance of education.

 

Higher education leaders should ask questions such as the following:

  • What place does data have in our courses?
  • Do students have the appropriate mix of mathematics, statistics, and coding to understand how data is manipulated and how algorithms work?
  • Should students be required to become “data literate” (i.e., able to effectively use and critically evaluate data and its sources)?

Higher education leaders should ask questions such as the following:

  • How might problem-solving and discovery change with AI?
  • How do we optimize the division of labor and best allocate tasks between humans and machines?
  • What role do collaborative platforms and collective intelligence have in how we develop and deploy expertise?


Higher education leaders should ask questions such as the following:

  • Even though something is possible, does that mean it is morally responsible?
  • How do we achieve a balance between technological possibilities and policies that enable—or stifle—their use?
  • An algorithm may represent a “trade secret,” but it might also reinforce dangerous assumptions or result in unconscious bias. What kind of transparency should we strive for in the use of algorithms?

 

 

 

25 skills LinkedIn says are most likely to get you hired in 2018 — and the online courses to get them — from businessinsider.com by Mara Leighton

Excerpt:

With the introduction of far-reaching and robust technology, the job market has experienced its own exponential growth, adaptation, and semi-metamorphosis. So much so that it can be difficult to guess what skills employer’s are looking for and what makes your résumé — and not another — stand out to recruiters.

Thankfully, LinkedIn created a 2018 “roadmap”— a list of hard and soft skills that companies need the most.

LinkedIn used data from their 500+ million members to identify the skills companies are currently working the hardest to fill. They grouped the skills members add to their profiles into several dozen categories (for example, “Android” and “iOS” into the “Mobile Development” category). Then, the company looked at all of the hiring and recruiting activity that happened on LinkedIn between January 1 and September 1 (billions of data points) and extrapolated the skill categories that belonged to members who were “more likely to start a new role within a company and receive interest from companies.”

LinkedIn then coupled those specific skills with related jobs and their average US salaries — all of which you can find below, alongside courses you can take (for free or for much less than the cost of a degree) to support claims of aptitude and stay ahead of the curve.

The online-learning options we included — LinkedIn Learning, Udemy, Coursera, and edX— are among the most popular and inexpensive.

 

 

Also see:

 

 

 

Six tech giants sign health data interoperability pledge — from medicaldevice-network.com by GlobalData Healthcare

Excerpt:

Google, Amazon, and IBM joined forces with Microsoft, Salesforce, and Oracle to pledge to speed up the progress of health data standards and interoperability.

This big new alliance’s pledge will have a very positive impact on healthcare as it will become easier to share medical data among hospitals. Both physicians and patients will have easier access to information, which will lead to faster diagnosis and treatment.

The companies claim that this project will lead to better outcomes, higher patient satisfaction, and lower costs—a so-called “Triple Aim.”

 

From DSC:
No doubt that security will have to be very tight around these efforts.

 

 

State of AI — from stateof.ai

Excerpt:

In this report, we set out to capture a snapshot of the exponential progress in AI with a focus on developments in the past 12 months. Consider this report as a compilation of the most interesting things we’ve seen that seeks to trigger informed conversation about the state of AI and its implication for the future.

We consider the following key dimensions in our report:

  • Research: Technology breakthroughs and their capabilities.
  • Talent: Supply, demand and concentration of talent working in the field.
  • Industry: Large platforms, financings and areas of application for AI-driven innovation today and tomorrow.
  • Politics: Public opinion of AI, economic implications and the emerging geopolitics of AI.

 

definitions of terms involved in AI

definitions of terms involved in AI

 

hard to say how AI is impacting jobs yet -- but here are 2 perspectives

 

 

There’s nothing artificial about how AI is changing the workplace — from forbes.com by Eric Yuan

Excerpt:

As I write this, AI has already begun to make video meetings even better. You no longer have to spend time entering codes or clicking buttons to launch a meeting. Instead, with voice-based AI, video conference users can start, join or end a meeting by simply speaking a command (think about how you interact with Alexa).

Voice-to-text transcription, another artificial intelligence feature offered by Otter Voice Meeting Notes (from AISense, a Zoom partner), Voicefox and others, can take notes during video meetings, leaving you and your team free to concentrate on what’s being said or shown. AI-based voice-to-text transcription can identify each speaker in the meeting and save you time by letting you skim the transcript, search and analyze it for certain meeting segments or words, then jump to those mentions in the script. Over 65% of respondents from the Zoom survey said they think AI will save them at least one hour a week of busy work, with many claiming it will save them one to five hours a week.

 

 

 

AI can now ‘listen’ to machines to tell if they’re breaking down — from by Rebecca Campbell

Excerpt:

Sound is everywhere, even when you can’t hear it.

It is this noiseless sound, though, that says a lot about how machines function.

Helsinki-based Noiseless Acoustics and Amsterdam-based OneWatt are relying on artificial intelligence (AI) to better understand the sound patterns of troubled machines. Through AI they are enabling faster and easier problem detection.

 

Making sound visible even when it can’t be heard. With the aid of non-invasive sensors, machine learning algorithms, and predictive maintenance solutions, failing components can be recognized at an early stage before they become a major issue.

 

 

 

Chinese university uses facial recognition for campus entry — from cr80news.com by Andrew Hudson

Excerpt:

A number of higher education institutions in China have deployed biometric solutions for access and payments in recent months, and adding to the list is Peking University. The university has now installed facial recognition readers at perimeter access gates to control access to its Beijing campus.

As reported by the South China Morning Post, anyone attempting to enter through the southwestern gate of the university will no longer have to provide a student ID card. Starting this month, students will present their faces to a camera as part of a trial run of the system ahead of full-scale deployment.

From DSC:
I’m not sure I like this one at all — and the direction that this is going in. 

 

 

 

Will We Use Big Data to Solve Big Problems? Why Emerging Technology is at a Crossroads — from blog.hubspot.com by Justin Lee

Excerpt:

How can we get smarter about machine learning?
As I said earlier, we’ve reached an important crossroads. Will we use new technologies to improve life for everyone, or to fuel the agendas of powerful people and organizations?

I certainly hope it’s the former. Few of us will run for president or lead a social media empire, but we can all help to move the needle.

Consume information with a critical eye.
Most people won’t stop using Facebook, Google, or social media platforms, so proceed with a healthy dose of skepticism. Remember that the internet can never be objective. Ask questions and come to your own conclusions.

Get your headlines from professional journalists.
Seek credible outlets for news about local, national and world events. I rely on the New York Times and the Wall Street Journal. You can pick your own sources, but don’t trust that the “article” your Aunt Marge just posted on Facebook is legit.

 

 

 

 
© 2025 | Daniel Christian