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.’”

 

 

 

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.

 

 

 

 

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:

  1. What are the LEAST and MOST essential skills needed for the future?
  2. Where and how will tomorrow’s workers and learners acquire the skills they really need?
  3. 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.

 

 

 

New game lets players train AI to spot legal issues — from abajournal.com by Jason Tashea

Excerpt:

Got a free minute? There’s a new game that will help train an artificial intelligence model to spot legal issues and help close the access-to-justice gap.

Called Learned Hands—yes, it’s a pun—the game takes 75,000 legal questions posted on Reddit dealing with family, consumer, criminal and other legal issues and asks the user to determine what the issue is.

While conjuring up nightmares of the first-year in law school for many lawyers, David Colarusso says it’s for a good cause.

“It’s an opportunity for attorneys to take their downtime to train machine learning algorithms to help access-to-justice issues,” says Colarusso, director of Suffolk University Law School’s Legal Innovation and Technology (LIT) Lab and partner on this project with the Stanford Legal Design Lab.

 

From learnedhands.law.stanford.edu/legalIssues

When you play the game, you’ll be spotting if different legal issues are present in people’s stories. Some of these issues will be high level categories, and others will be more specific issues.

Here are the high level categories:

 

 

7 Internet of Things examples that are super futuristic— from blog.hubspot.com by Caroline Forsey

 

Spray-on antennas will revolutionize the Internet of Things — from networkworld.com
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.

 

7 ways to keep your smart home from being hacked — from marketwatch.com

 

The coming revolution in software development — from forbes.com by Matt Bornstein

Excerpt:

Amid the deep learning hype, though, many observers miss the biggest reason to be optimistic about its future: deep learning requires coders to write very little actual code. Rather than relying on preset rules or if-then statements, a deep learning system writes rules automatically based on past examples. A software developer only has to create a “rough skeleton,” to paraphrase Andrej Karpathy from Tesla, then let the computers do the rest.

In this new world, developers no longer need to design a unique algorithm for each problem. Most work focuses, instead, on generating datasets that reflect desired behavior and managing the training process. Pete Warden from Google’s TensorFlow team pointed this outas far back as 2014: “I used to be a coder,” he wrote. “Now I teach computers to write their own programs.”

Again: the programming model driving the most important advances in software today does not require a significant amount of actual programming.

What does this mean for the future of software development?

 

 

 

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.

 

 

10 jobs that are safe in an AI world — from linkedin.com by Kai-Fu Lee

Excerpts:

Teaching
AI will be a great tool for teachers and educational institutions, as it will help educators figure out how to personalize curriculum based on each student’s competence, progress, aptitude, and temperament. However, teaching will still need to be oriented around helping students figure out their interests, teaching students to learn independently, and providing one-on-one mentorship. These are tasks that can only be done by a human teacher. As such, there will still be a great need for human educators in the future.

Criminal defense law
Top lawyers will have nothing to worry about when it comes to job displacement. reasoning across domains, winning the trust of clients, applying years of experience in the courtroom, and having the ability to persuade a jury are all examples of the cognitive complexities, strategies, and modes of human interaction that are beyond the capabilities of AI. However, a lot of paralegal and preparatory work like document review, analysis, creating contracts, handling small cases, packing cases, and coming up with recommendations can be done much better and more efficiently with AI. The costs of law make it worthwhile for AI companies to go after AI paralegals and AI junior lawyers, but not top lawyers.

 

From DSC:
In terms of teaching, I agree that while #AI will help personalize learning, there will still be a great need for human teachers, professors, and trainers. I also agree w/ my boss (and with some of the author’s viewpoints here, but not all) that many kinds of legal work will still need the human touch & thought processes. I diverge from his thinking in terms of scope — the need for human lawyers will go far beyond just lawyers involved in crim law.

 

Also see:

15 business applications for artificial intelligence and machine learning — from forbes.com

Excerpt:

Fifteen members of Forbes Technology Council discuss some of the latest applications they’ve found for AI/ML at their companies. Here’s what they had to say…

 

 

 

Skype chats are coming to Alexa devices — from engadget.com by Richard Lawlor
Voice controlled internet calls to or from any device with Amazon’s system in it.

Excerpt:

Aside from all of the Alexa-connected hardware, there’s one more big development coming for Amazon’s technology: integration with Skype. Microsoft and Amazon said that voice and video calls via the service will come to Alexa devices (including Microsoft’s Xbox One) with calls that you can start and control just by voice.

 

 

Amazon Hardware Event 2018
From techcrunch.com

 

Echo HomePod? Amazon wants you to build your own — by Brian Heater
One of the bigger surprises at today’s big Amazon event was something the company didn’t announce. After a couple of years of speculation that the company was working on its own version of the Home…

 

 

The long list of new Alexa devices Amazon announced at its hardware event — by Everyone’s favorite trillion-dollar retailer hosted a private event today where they continued to…

 

Amazon introduces APL, a new design language for building Alexa skills for devices with screensAlong with the launch of the all-new Echo Show, the Alexa-powered device with a screen, Amazon also introduced a new design language for developers who want to build voice skills that include multimedia…

Excerpt:

Called Alexa Presentation Language, or APL, developers will be able to build voice-based apps that also include things like images, graphics, slideshows and video, and easily customize them for different device types – including not only the Echo Show, but other Alexa-enabled devices like Fire TV, Fire Tablet, and the small screen of the Alexa alarm clock, the Echo Spot.

 

From DSC:
This is a great move by Amazon — as NLP and our voices become increasingly important in how we “drive” and utilize our computing devices.

 

 

Amazon launches an Echo Wall Clock, because Alexa is gonna be everywhere — by Sarah Perez

 

 

Amazon’s new Echo lineup targets Google, Apple and Sonos — from engadget.com by Nicole Lee
Alexa, dominate the industry.

The business plan from here is clear: Companies pay a premium to be activated when users pose questions related to their products and services. “How do you cook an egg?” could pull up a Food Network tutorial; “How far is Morocco?” could enable the Expedia app.
Also see how Alexa might be a key piece of smart classrooms in the future:
 

Why emerging technology needs to retain a human element — from forbes.com by Samantha Radocchia
Technology opens up new, unforeseen issues. And humans are necessary for solving the problems automated services can’t.

Excerpt (emphasis DSC):

With technological advancements comes change. Rather than avoiding new technology for as long as possible, and then accepting the inevitable, people need to be actively thinking about how it will change us as individuals and as a society.

Take your phone for instance. The social media, gaming and news apps are built to keep you addicted so companies can collect data on you. They’re designed to be used constantly so you back for more the instant you feel the slightest twinge of boredom.

And yet, other apps—sometimes the same ones I just mentioned—allow you to instantly communicate with people around the world. Loved ones, colleagues, old friends—they’re all within reach now.

Make any technology decisions carefully, because their impact down the road may be tremendous.

This is part of the reason why there’s been a push lately for ethics to be a required part of any computer science or vocational training program. And it makes sense. If people want to create ethical systems, there’s a need to remember that actual humans are behind them. People make bad choices sometimes. They make mistakes. They aren’t perfect.

 

To ignore the human element in tech is to miss the larger point: Technology should be about empowering people to live their best lives, not making them fearful of the future.

 

 

 

 

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?

 

 

 

Microsoft’s AI-powered Sketch2Code builds websites and apps from drawings — from alphr.com by Bobby Hellard
Microsoft Released on GitHub, Microsoft’s AI-powered developer tool can shave hours off web and app building

Excerpt:

Microsoft has developed an AI-powered web design tool capable of turning sketches of websites into functional HTML code.

Called Sketch2Code, Microsoft AI’s senior product manager Tara Shankar Jana explained that the tool aims to “empower every developer and every organisation to do more with AI”. It was born out of the “intrinsic” problem of sending a picture of a wireframe or app designs from whiteboard or paper to a designer to create HTML prototypes.

 

 

 

 

 

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:

 

 

 

How blockbuster MOOCs could shape the future of teaching — from edsurge.com by Jeff Young

Excerpt:

There isn’t a New York Times bestseller list for online courses, but perhaps there should be. After all, so-called MOOCs, or massive open online courses, were meant to open education to as many learners as possible, and in many ways they are more like books (digital ones, packed with videos and interactive quizzes) than courses.

The colleges and companies offering MOOCs can be pretty guarded these days about releasing specific numbers on how many people enroll or pay for a “verified certificate” or microcredential showing they took the course. But both Coursera and EdX, two of the largest providers, do release lists of their most popular courses. And those lists offer a telling snapshot of how MOOCs are evolving and what their impact is on the instructors and institutions offering them.

Here are the top 10 most popular courses for each provider:

 

Coursera Top 10 Most Popular Courses (over past 12 months)

 

edX Top 10 Most Popular Courses (all time)

 

 

So what are these blockbuster MOOCs, then? Experiential textbooks? Gateways to more rigorous college courses? A new kind of entertainment program?

Maybe the answer is: all of the above.

 

 

 
© 2025 | Daniel Christian