Reimagining the Higher Education Ecosystem — from edu2030.agorize.com
How might we empower people to design their own learning journeys so they can lead purposeful and economically stable lives?

Excerpts:

The problem
Technology is rapidly transforming the way we live, learn, and work. Entirely new jobs are emerging as others are lost to automation. People are living longer, yet switching jobs more often. These dramatic shifts call for a reimagining of the way we prepare for work and life—specifically, how we learn new skills and adapt to a changing economic landscape.

The changes ahead are likely to hurt most those who can least afford to manage them: low-income and first generation learners already ill-served by our existing postsecondary education system. Our current system stifles economic mobility and widens income and achievement gaps; we must act now to ensure that we have an educational ecosystem flexible and fair enough to help all people live purposeful and economically stable lives. And if we are to design solutions proportionate to this problem, new technologies must be called on to scale approaches that reach the millions of vulnerable people across the country.

 

The challenge
How might we empower people to design their own learning journeys so they can lead purposeful and economically stable lives?

The Challenge—Reimagining the Higher Education Ecosystem—seeks bold ideas for how our postsecondary education system could be reimagined to foster equity and encourage learner agency and resilience. We seek specific pilots to move us toward a future in which all learners can achieve economic stability and lead purposeful lives. This Challenge invites participants to articulate a vision and then design pilot projects for a future ecosystem that has the following characteristics:

Expands access: The educational system must ensure that all people—including low-income learners who are disproportionately underserved by the current higher education system—can leverage education to live meaningful and economically stable lives.

Draws on a broad postsecondary ecosystem: While college and universities play a vital role in educating students, there is a much larger ecosystem in which students learn. This ecosystem includes non-traditional “classes” or alternative learning providers, such as MOOCs, bootcamps, and online courses as well as on-the-job training and informal learning. Our future learning system must value the learning that happens in many different environments and enable seamless transitions between learning, work, and life.

 

From DSC:
This is where I could see a vision similar to Learning from the Living [Class] Room come into play. It would provide a highly affordable, accessible platform, that would offer more choice, and more control to learners of all ages. It would be available 24×7 and would be a platform that supports lifelong learning. It would combine a variety of AI-enabled functionalities with human expertise, teaching, training, motivation, and creativity.

It could be that what comes out of this challenge will lay the groundwork for a future, massive new learning platform.

 

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

 

Also see:

 

Computers that never forget a face — from Future Today Institute

Excerpts:

In August, the U.S. Customs and Border Protection will roll out new technology that will scan the faces of drivers as they enter and leave the United States. For years, accomplishing that kind of surveillance through a car windshield has been difficult. But technology is quickly advancing. This system, activated by ambient light sensors, range finders and remote speedometers, uses smart cameras and AI-powered facial recognition technology to compare images in government files with people behind the wheel.

Biometric borders are just the beginning. Faceprints are quickly becoming our new fingerprints, and this technology is marching forward with haste. Faceprints are now so advanced that machine learning algorithms can recognize your unique musculatures and bone structures, capillary systems, and expressions using thousands of data points. All the features that make up a unique face are being scanned, captured and analyzed to accurately verify identities. New hairstyle? Plastic surgery? They don’t interfere with the technology’s accuracy.

Why you should care. Faceprints are already being used across China for secure payments. Soon, they will be used to customize and personalize your digital experiences. Our Future Today Institute modeling shows myriad near-future applications, including the ability to unlock your smart TV with your face. Retailers will use your face to personalize your in-store shopping experience. Auto manufacturers will start using faceprints to detect if drivers are under the influence of drugs or alcohol and prevent them from driving. It’s plausible that cars will soon detect if a driver is distracted and take the wheel using an auto-pilot feature. On a diet but live with others? Stash junk food in a drawer and program the lock to restrict your access. Faceprints will soon create opportunities for a wide range of sectors, including military, law enforcement, retail, manufacturing and security. But as with all technology, faceprints could lead to the loss of privacy and widespread surveillance.

It’s possible for both risk and opportunity to coexist. The point here is not alarmist hand-wringing, or pointless calls for cease-and-desist demands on the development and use of faceprint technology. Instead, it’s to acknowledge an important emerging trend––faceprints––and to think about the associated risks and opportunities for you and your organization well in advance. Approach biometric borders and faceprints with your (biometrically unique) eyes wide open.

Near-Futures Scenarios (2018 – 2028):

OptimisticFaceprints make us safer, and they bring us back to physical offices and stores.  

Pragmatic: As faceprint adoption grows, legal challenges mount. 
In April, a U.S. federal judge ruled that Facebook must confront a class-action lawsuit that alleges its faceprint technology violates Illinois state privacy laws. Last year, a U.S. federal judge allowed a class-action suit to go forth against Shutterfly, claiming the company violated the Illinois Biometric Information Privacy Act, which ensures companies receive written releases before collecting biometric data, including faces. Companies and device manufacturers, who are early developers but late to analyzing legal outcomes, are challenged to balance consumer privacy with new security benefits.

CatastrophicFaceprints are used for widespread surveillance and authoritative control.

 

 

 

How AI is helping sports teams scout star play — from nbcnews.com by Edd Gent
Professional baseball, basketball and hockey are among the sports now using AI to supplement traditional coaching and scouting.

 

 

 

Preparing students for workplace of the future  — from educationdive.com by Shalina Chatlani

Excerpt:

The workplace of the future will be marked by unprecedentedly advanced technologies, as well as a focus on incorporating artificial intelligence to drive higher levels of production with fewer resources. Employers and education stakeholders, noting the reality of this trend, are turning a reflective eye toward current students and questioning whether they will be workforce ready in the years to come.

This has become a significant concern for higher education executives, who find their business models could be disrupted as they fail to meet workforce demands. A 2018 Gallup-Northeastern University survey shows that of 3,297 U.S. citizens interviewed, only 22% with a bachelor’s degree said their education left them “well” or “very well prepared” to use AI in their jobs.

In his book “Robot-Proof: Higher Education in the Age of Artificial Intelligence,” Northeastern University President Joseph Aoun argued that for higher education to adapt advanced technologies, it has to focus on life-long learning, which he said says prepares students for the future by fostering purposeful integration of technical literacies, such as coding and data literacy, with human literacies, such as creativity, ethics, cultural agility and entrepreneurship.

“When students combine these literacies with experiential components, they integrate their knowledge with real life settings, leading to deep learning,” Aoun told Forbes.

 

 

Amazon’s A.I. camera could help people with memory loss recognize old friends and family — from cnbc.com by Christina Farr

  • Amazon’s DeepLens is a smart camera that can recognize objects in front of it.
  • One software engineer, Sachin Solkhan, is trying to figure out how to use it to help people with memory loss.
  • Users would carry the camera to help them recognize people they know.

 

 

Microsoft acquired an AI startup that helps it take on Google Duplex — from qz.com by Dave Gershgorn

Excerpt:

We’re going to talk to our technology, and everyone else’s too. Google proved that earlier this month with a demonstration of artificial intelligence that can hop on the phone to book a restaurant reservation or appointment at the hair salon.

Now it’s just a matter of who can build that technology fastest. To reach that goal, Microsoft has acquired conversational AI startup Semantic Machines for an undisclosed amount. Founded in 2014, the startup’s goal was to build AI that can converse with humans through speech or text, with the ability to be trained to converse on any language or subject.

 

 

Researchers developed an AI to detect DeepFakes — from thenextweb.com by Tristan Greene

Excerpt:

A team of researchers from the State University of New York (SUNY) recently developed a method for detecting whether the people in a video are AI-generated. It looks like DeepFakes could meet its match.

What it means: Fear over whether computers will soon be able to generate videos that are indistinguishable from real footage may be much ado about nothing, at least with the currently available methods.

The SUNY team observed that the training method for creating AI that makes fake videos involves feeding it images – not video. This means that certain human physiological quirks – like breathing and blinking – don’t show up in computer-generated videos. So they decided to build an AI that uses computer vision to detect blinking in fake videos.

 

 

Bringing It Down To Earth: Four Ways Pragmatic AI Is Being Used Today — from forbes.com by Carlos Melendez

Excerpt:

Without even knowing it, we are interacting with pragmatic AI day in and day out. It is used in the automated chatbots that answer our calls and questions and the customer service rep that texts with us on a retail site, providing a better and faster customer experience.

Below are four key categories of pragmatic AI and ways they are being applied today.

1. Speech Recognition And Natural Language Processing (NLP)
2. Predictive Analytics
3. Image Recognition And Computer Vision
4. Self-Driving Cars And Robots

 

 

Billable Hour ‘Makes No Sense’ in an AI World — from biglawbusiness.com by Helen Gunnarsson

Excerpt:

Artificial intelligence (AI) is transforming the practice of law, and “data is the new oil” of the legal industry, panelist Dennis Garcia said at a recent American Bar Association conference.Garcia is an assistant general counsel for Microsoft in Chicago. Robert Ambrogi, a Massachusetts lawyer and blogger who focuses on media, technology, and employment law, moderated the program.“The next generation of lawyers is going to have to understand how AI works” as part of the duty of competence, panelist Anthony E. Davis told the audience. Davis is a partner with Hinshaw & Culbertson LLP in New York.

Davis said AI will result in dramatic changes in law firms’ hiring and billing, among other things. The hourly billing model, he said, “makes no sense in a universe where what clients want is judgment.” Law firms should begin to concern themselves not with the degrees or law schools attended by candidates for employment but with whether they are “capable of developing judgment, have good emotional intelligence, and have a technology background so they can be useful” for long enough to make hiring them worthwhile, he said.

 

 

Deep Learning Tool Tops Dermatologists in Melanoma Detection — from healthitanalytics.com
A deep learning tool achieved greater accuracy than dermatologists when detecting melanoma in dermoscopic images.

 

 

Apple’s plans to bring AI to your phone — from wired.com by Tom Simonite

Excerpt:

HomeCourt is built on tools announced by Federighi last summer, when he launched Apple’s bid to become a preferred playground for AI-curious developers. Known as Core ML, those tools help developers who’ve trained machine learning algorithms deploy them on Apple’s mobile devices and PCs.

At Apple’s Worldwide Developer Conference on Monday, Federighi revealed the next phase of his plan to enliven the app store with AI. It’s a tool called Create ML that’s something like a set of training wheels for building machine learning models in the first place. In a demo, training an image-recognition algorithm to distinguish different flavors of ice cream was as easy as dragging and dropping a folder containing a few dozen images and waiting a few seconds. In a session for developers, Apple engineers suggested Create ML could teach software to detect whether online comments are happy or angry, or predict the quality of wine from characteristics such as acidity and sugar content. Developers can use Create ML now but can’t ship apps using the technology until Apple’s latest operating systems arrive later this year.

 

 

 

Andrew Ng is probably teaching more students than anyone else on the planet. (Without a university involved.) — from edsurge.com by Jeff Young

Excerpt:

One selling point of MOOCs (massive online open courses) has been that students can access courses from the world’s most famous universities. The assumption—especially in the marketing messages from major providers like Coursera and edX—is that the winners of traditional higher education will also end up the winners in the world of online courses.

But that isn’t always happening.

In fact, three of the 10 most popular courses on Coursera aren’t produced by a college or university at all, but by a company. That company—called Deeplearning.ai—is a unique provider of higher education. It is essentially built on the reputation of its founder, Andrew Ng, who teaches all five of the courses it offers so far.

Ng is seen as one of the leading figures in artificial intelligence, having founded and directed the Google Brain project and served as the chief scientist at the Chinese search giant Baidu, as well as having directed the artificial intelligence laboratory at Stanford University. He also happens to be the co-founder of Coursera itself, and it was his Stanford course on machine learning that helped launch the MOOC craze in the first place.

In fact, Ng’s original Stanford MOOC remains the most popular course offered by Coursera. Since the course began in 2012, it has drawn more than 1.7 million enrollments. (It now runs on demand, so people can sign up anytime.) And his new series of courses through Deeplearning.ai, which kicked off last year, have already exceeded 250,000 signups. Even allowing for the famously low completion rates of MOOCs, it still means that hundreds of thousands of people have sat through lecture videos by Ng.

 

 

 

 

 

 

 

Below are some excerpted slides from her presentation…

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Also see:

  • 20 important takeaways for learning world from Mary Meeker’s brilliant tech trends – from donaldclarkplanb.blogspot.com by Donald Clark
    Excerpt:
    Mary Meeker’s slide deck has a reputation of being the Delphic Oracle of tech. But, at 294 slides it’s a lot to take in. Don’t worry, I’ve been through them all. It has tons on economic stuff that is of marginal interest to education and training but there’s plenty to to get our teeth into. We’re not immune to tech trends, indeed we tend to follow in lock-step, just a bit later than everyone else. Among the data are lots of fascinating insights that point the way forward in terms of what we’re likely to be doing over the next decade. So here’s a really quick, top-end summary for folk in the learning game.

 

“Educational content usage online is ramping fast” with over 1 billion daily educational videos watched. There is evidence that use of the Internet for informal and formal learning is taking off.

 

 

 

 

 

 

10 Big Takeaways From Mary Meeker’s Widely-Read Internet Report — from fortune.com by  Leena Rao

 

 

 

 

Skill shift: Automation and the future of the workforce — from mckinsey.com by Jacques Bughin, Eric Hazan, Susan Lund, Peter Dahlström, Anna Wiesinger, and Amresh Subramaniam
Demand for technological, social and emotional, and higher cognitive skills will rise by 2030. How will workers and organizations adapt?

Excerpt:

Skill shifts have accompanied the introduction of new technologies in the workplace since at least the Industrial Revolution, but adoption of automation and artificial intelligence (AI) will mark an acceleration over the shifts of even the recent past. The need for some skills, such as technological as well as social and emotional skills, will rise, even as the demand for others, including physical and manual skills, will fall. These changes will require workers everywhere to deepen their existing skill sets or acquire new ones. Companies, too, will need to rethink how work is organized within their organizations.

This briefing, part of our ongoing research on the impact of technology on the economy, business, and society, quantifies time spent on 25 core workplace skills today and in the future for five European countries—France, Germany, Italy, Spain, and the United Kingdom—and the United States and examines the implications of those shifts.

Topics include:
How will demand for workforce skills change with automation?
Shifting skill requirements in five sectors
How will organizations adapt?
Building the workforce of the future

 

 

Alexa creepily recorded a family’s private conversations, sent them to business associate — from usatoday.com by Elizabeth Weise

Excerpt:

In this instance, a random series of disconnected conversations got interpreted by Alexa as a specific and connected series of commands.

It doesn’t appear that the family members actually heard Alexa asking who it should send a message to, or confirming that it should be sent.

That’s probably a function of how good the Echo’s far field voice recognition is. Each speaker has seven microphones which are arrayed so the cylindrical speaker can pick up voice commands from far away or even in noisy rooms with lots of conversations going on.

Amazon says it is evaluating options to make cases such as happened to the Portland family less likely.

But given that Forrester predicts by 2020 almost 50% of American households will contain a smart speaker, expect more such confusions in the future.

 

 

 

 

 

 

Google’s robot assistant now makes eerily lifelike phone calls for you — from theguardian.com by Olivia Solon
Google Duplex contacts hair salon and restaurant in demo, adding ‘er’ and ‘mmm-hmm’ so listeners think it’s human

Excerpt:

Google’s virtual assistant can now make phone calls on your behalf to schedule appointments, make reservations in restaurants and get holiday hours.

The robotic assistant uses a very natural speech pattern that includes hesitations and affirmations such as “er” and “mmm-hmm” so that it is extremely difficult to distinguish from an actual human phone call.

The unsettling feature, which will be available to the public later this year, is enabled by a technology called Google Duplex, which can carry out “real world” tasks on the phone, without the other person realising they are talking to a machine. The assistant refers to the person’s calendar to find a suitable time slot and then notifies the user when an appointment is scheduled.

 

 

Google employees quit over the company’s military AI project — from thenextweb.com by Tristan Greene

Excerpt:

About a dozen Google employees reportedly left the company over its insistence on developing AI for the US military through a program called Project Maven. Meanwhile 4,000 others signed a petition demanding the company stop.

It looks like there’s some internal confusion over whether the company’s “Don’t Be Evil” motto covers making machine learning systems to aid warfare.

 

 

 

The link between big tech and defense work — from wired.com by Nitasha Tiku

Except:

FOR MONTHS, A growing faction of Google employees has tried to force the company to drop out of a controversial military program called Project Maven. More than 4,000 employees, including dozens of senior engineers, have signed a petition asking Google to cancel the contract. Last week, Gizmodo reported that a dozen employees resigned over the project. “There are a bunch more waiting for job offers (like me) before we do so,” one engineer says. On Friday, employees communicating through an internal mailing list discussed refusing to interview job candidates in order to slow the project’s progress.

Other tech giants have recently secured high-profile contracts to build technology for defense, military, and intelligence agencies. In March, Amazon expanded its newly launched “Secret Region” cloud services supporting top-secret work for the Department of Defense. The same week that news broke of the Google resignations, Bloomberg reported that Microsoft locked down a deal with intelligence agencies. But there’s little sign of the same kind of rebellion among Amazon and Microsoft workers.

 

 

Amazon urged not to sell facial recognition tool to police — from wpxi.com by Gene Johnson

Excerpt:

Facebook SEATTLE (AP) – The American Civil Liberties Union and other privacy advocates are asking Amazon to stop marketing a powerful facial recognition tool to police, saying law enforcement agencies could use the technology to “easily build a system to automate the identification and tracking of anyone.”

The tool, called Rekognition, is already being used by at least one agency – the Washington County Sheriff’s Office in Oregon – to check photographs of unidentified suspects against a database of mug shots from the county jail, which is a common use of such technology around the country.

 

 

From DSC:
Google’s C-Suite — as well as the C-Suites at Microsoft, Amazon, and other companies — needs to be very careful these days, as they could end up losing the support/patronage of a lot of people — including more of their own employees. It’s not an easy task to know how best to build and use technologies in order to make the world a better place…to create a dream vs. a nightmare for our future. But just because we can build something, doesn’t mean we should.

 

 

The Complete Guide to Conversational Commerce | Everything you need to know. — from chatbotsmagazine.com by Matt Schlicht

Excerpt:

What is conversational commerce? Why is it such a big opportunity? How does it work? What does the future look like? How can I get started? These are the questions I’m going to answer for you right now.

The guide covers:

  • An introduction to conversational commerce.
  • Why conversational commerce is such a big opportunity.
  • Complete breakdown of how conversational commerce works.
  • Extensive examples of conversational commerce using chatbots and voicebots.
  • How artificial intelligence impacts conversational commerce.
  • What the future of conversational commerce will look like.

 

Definition: Conversational commerce is an automated technology, powered by rules and sometimes artificial intelligence, that enables online shoppers and brands to interact with one another via chat and voice interfaces.

 

 

 

Notes from the AI frontier: Applications and value of deep learning — from mckinsey.com by Michael Chui, James Manyika, Mehdi Miremadi, Nicolaus Henke, Rita Chung, Pieter Nel, and Sankalp Malhotra

Excerpt:

Artificial intelligence (AI) stands out as a transformational technology of our digital age—and its practical application throughout the economy is growing apace. For this briefing, Notes from the AI frontier: Insights from hundreds of use cases (PDF–446KB), we mapped both traditional analytics and newer “deep learning” techniques and the problems they can solve to more than 400 specific use cases in companies and organizations. Drawing on McKinsey Global Institute research and the applied experience with AI of McKinsey Analytics, we assess both the practical applications and the economic potential of advanced AI techniques across industries and business functions. Our findings highlight the substantial potential of applying deep learning techniques to use cases across the economy, but we also see some continuing limitations and obstacles—along with future opportunities as the technologies continue their advance. Ultimately, the value of AI is not to be found in the models themselves, but in companies’ abilities to harness them.

It is important to highlight that, even as we see economic potential in the use of AI techniques, the use of data must always take into account concerns including data security, privacy, and potential issues of bias.

  1. Mapping AI techniques to problem types
  2. Insights from use cases
  3. Sizing the potential value of AI
  4. The road to impact and value

 

 

 

AI for Good — from re-work.co by Ali Shah, Head of Emerging Technology and Strategic Direction – BBC

 

 

 

Algorithms are making the same mistakes assessing credit scores that humans did a century ago — from qz.com by Rachel O’Dwyer

 

 

 

 

ABA set to approve more online credits for law students — from law.com by Karen Sloan
Supporters say allowing J.D. students to take up to one-third of their credits online, including some during their first year, is validation that distance education can work in law schools.

 

7 things lawyers should know about Artificial Intelligence — from abovethelaw.com by Amy Larson
AI is here to make practicing law easier, so keep these things in mind if you’re thinking of implementing it in your practice. 

Excerpt:

6. Adopting AI means embracing change.
If you intend to implement AI technologies into your legal organization, you must be ready for change. Not only will your processes and workflows need to change to incorporate AI into the business, but you’ll also likely be working with a whole new set of people. Whether they are part of your firm or outside consultants, expect to collaborate with data analysts, process engineers, pricing specialists, and other data-driven professionals.

 

 

 


Addendum on 5/18/18:


 

  • Technology & Innovation: Trends Transforming The Legal Industry — from livelaw.in by Richa Kachhwaha
    Excerpt:
    Globally, the legal industry is experiencing an era of transformation. The changes are unmistakable and diverse. Paperwork and data management- long practiced by lawyers- is being replaced by software solutions; trans-national boundaries are legally shrinking; economic forces are re-defining law practices; innovative in-house law departments are driving significant value creation; consumer trends have begun to dominate the legal landscape; …

 

 

 

Microsoft’s meeting room of the future is wild — from theverge.com by Tom Warren
Transcription, translation, and identification

Excerpts:

Microsoft just demonstrated a meeting room of the future at the company’s Build developer conference.

It all starts with a 360-degree camera and microphone array that can detect anyone in a meeting room, greet them, and even transcribe exactly what they say in a meeting regardless of language.

Microsoft takes the meeting room scenario even further, though. The company is using its artificial intelligence tools to then act on what meeting participants say.

 

 

From DSC:
Whoa! Many things to think about here. Consider the possibilities for global/blended/online-based learning (including MOOCs) with technologies associated with translation, transcription, and identification.

 

 

Educause Releases 2018 Horizon Report Preview — from campustechnology.com by Rhea Kelly

Excerpt:

After acquiring the rights to the New Media Consortium’s Horizon project earlier this year, Educause has now published a preview of the 2018 Higher Education Edition of the Horizon Report — research that was in progress at the time of NMC’s sudden dissolution. The report covers the key technology trends, challenges and developments expected to impact higher ed in the short-, mid- and long-term future.

 

Also see:

 

 

 

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