Amazon’s new bricks-&-mortar bookstore nails what the web couldn’t — from hackernoon.com by Pat Ryan

or

A title from DSC:
How Amazon uses its vast data resources to reinvent the bookstore

 

Excerpt (emphasis DSC):

Amazon’s First Foray into Physical Retail — While Utilitarian — Takes Discovery to New Levels
As a long time city dweller living in a neighborhood full of history, I had mixed feelings about the arrival of Amazon’s first bricks-and-mortar bookstore in a city neighborhood (the first four are located in malls). Like most of my neighbors around Chicago’s Southport Corridor, I prefer the charm of owner operated boutiques. Yet as a tech entrepreneur who holds Amazon founder Jeff Bezos in the highest esteem, I was excited to see how Amazon would reimagine the traditional bookstore given their customer obsession and their treasure trove of user data. Here’s what I discovered…

The Bottom Line:
I will still go to Amazon.com for the job of ordering a book that I already know that I want (and to the local Barnes and Noble if I need it today). But when I need to discover a book for gifts (Father’s Day is coming up soon enough) or for my own interest, nothing that I have seen compares to Amazon Books. We had an amazing experience and discovered more books in 20 minutes than we had in the past month or two.

 

 

The physical manifestation of the “if you like…then you’ll love…”

 

 

 

The ultra metric combining insights from disparate sources seems more compelling than standard best seller lists

 

 

 

From DSC:
In terms of learning, having to be in the same physical place as others continues to not be a requirement nearly as much as it used to be. But I’m not just talking about online learning here. I’m talking about a new type of learning environment that involves both hardware and software to facilitate collaboration (and it was designed that way from day 1). These new types of setups can provide us with new opportunities and affordances that we should begin experimenting with immediately.

Check out the following products — all of which allow a person to contribute to a discussion or conversation from anywhere they can get Internet access:

When you go to those sites, you will see words and phrase such as:

  • Visual collaboration software
  • Virtual workspace
  • Develop
  • Share
  • Inspire
  • Design
  • Global teams
  • A visual collaboration solution that links locations, teams, content, and devices in an immersive, shared workspace
  • Teamwork
  • Create and brainstorm with others
  • Digital workplace platform
  • Eliminate the distance between in-office and remote employees
  • Jumpstart spontaneous brainstorms and working sessions

So using these types of software and hardware setups, I can contribute regardless of where I’m located. Remote learning — from anywhere in the world — being combined with our face-to-face based classrooms.

Also, the push for Active Learning Classrooms (ALCs) continues across higher education. Such hands-on, project-learning based, student-centered approaches fit extremely well with the collaboration setups mentioned above.

Then, there’s the insight from Simon Dudley in this article:

“…video conferencing is increasingly an application within in a larger workflow…”

Lastly, if colleges and universities don’t have the funds to maintain their physical plants, look for higher education to move increasingly online — and these types of solutions could play a significant role in that environment. Plus, for working adults who need to reinvent themselves, this is an extremely efficient means of picking up some new skills and competencies.

So the growth of these types of setups — where the software and hardware work together to support worldwide collaboration — will likely create a powerful, new, emerging piece of our learning ecosystems.

 



 

 

 

 

 

 

 

 

 

 



 

Remote learning — from anywhere in the world — being combined with our face-to-face based classrooms.

 



 

 

From DSC:
The recent pieces below made me once again reflect on the massive changes that are quickly approaching — and in some cases are already here — for a variety of nations throughout the world.

They caused me to reflect on:

  • What the potential ramifications for higher education might be regarding these changes that are just starting to take place in the workplace due to artificial intelligence (i.e., the increasing use of algorithms, machine learning, and deep learning, etc.), automation, & robotics?
  • The need for people to reinvent themselves quickly throughout their careers (if we can still call them careers)
  • How should we, as a nation, prepare for these massive changes so that there isn’t civil unrest due to soaring inequality and unemployment?

As found in the April 9th, 2017 edition of our local newspaper here:

When even our local newspaper is picking up on this trend, you know it is real and has some significance to it.

 

Then, as I was listening to the radio a day or two after seeing the above article, I heard of another related piece on NPR.  NPR is having a journalist travel across the country, trying to identify “robot-safe” jobs.  Here’s the feature on this from MarketPlace.org

 

 

What changes do institutions of traditional higher education
immediately need to begin planning for? Initiating?

What changes should be planned for and begin to be initiated
in the way(s) that we accredit new programs?

 

 

Keywords/ideas that come to my mind:

  • Change — to society, to people, to higher ed, to the workplace
  • Pace of technological change — no longer linear, but exponential
  • Career development
  • Staying relevant — as institutions, as individuals in the workplace
  • Reinventing ourselves over time — and having to do so quickly
  • Adapting, being nimble, willing to innovate — as institutions, as individuals
  • Game-changing environment
  • Lifelong learning — higher ed needs to put more emphasis on microlearning, heutagogy, and delivering constant/up-to-date streams of content and learning experiences. This could happen via the addition/use of smaller learning hubs, some even makeshift learning hubs that are taking place at locations that these institutions don’t even own…like your local Starbucks.
  • If we don’t get this right, there could be major civil unrest as inequality and unemployment soar
  • Traditional institutions of higher education have not been nearly as responsive to change as they have needed to be; this opens the door to alternatives. There’s a limited (and closing) window of time left to become more nimble and responsive before these alternatives majorly disrupt the current world of higher education.

 

 

 



Addendum from the corporate world (emphasis DSC):



 

From The Impact 2017 Conference:

The Role of HR in the Future of Work – A Town Hall

  • Josh Bersin, Principal and Founder, Bersin by Deloitte, Deloitte Consulting LLP
  • Nicola Vogel, Global Senior HR Director, Danfoss
  • Frank Møllerop, Chief Executive Officer, Questback
  • David Mallon, Head of Research, Bersin by Deloitte, Deloitte Consulting LLP

Massive changes spurred by new technologies such as artificial intelligence, mobile platforms, sensors and social collaboration have revolutionized the way we live, work and communicate – and the pace is only accelerating. Robots and cognitive technologies are making steady advances, particularly in jobs and tasks that follow set, standardized rules and logic. This reinforces a critical challenge for business and HR leaders—namely, the need to design, source, and manage the future of work.

In this Town Hall, we will discuss the role HR can play in leading the digital transformation that is shaping the future of work in organizations worldwide. We will explore the changes we see taking place in three areas:

  • Digital workforce: How can organizations drive new management practices, a culture of innovation and sharing, and a set of talent practices that facilitate a new network-based organization?
  • Digital workplace: How can organizations design a working environment that enables productivity; uses modern communication tools (such as Slack, Workplace by Facebook, Microsoft Teams, and many others); and promotes engagement, wellness, and a sense of purpose?
  • Digital HR: How can organizations change the HR function itself to operate in a digital way, use digital tools and apps to deliver solutions, and continuously experiment and innovate?
 

Federal Reserve Bank of New York: Press Briefing on Household Debt, with Focus on Student Debt — with thanks to Mr. Bryan Alexander for his post on this

 

 

 

 

 

Excerpts:

Student Debt Overview
  • Student debt was $1.3 trillion at the end of 2016, an increase of about 170% from 2006.
  • Aggregate student debt is increasing because:
    • More students are taking out loans
    • Loans are for larger amounts
    • Repayment rates have slowed down
  • About 5% of the borrowers have more than $100,000 debt in 2016, but they account for about 30% of the total debt.
  • Recent graduates with student loans leave school with about $34,000, up nearly 70% from 10 years ago.

 


 

  • While the total level of household debt has nearly returned to the 2008 peak, debt types and borrower profiles have changed.
    • Debt growth is now driven by non-housing sectors, and debt is held by older, more creditworthy borrowers.
  • Student debt has expanded significantly because of higher levels of borrowing and slower rates of repayment.
  • Student debt defaults peaked with the 2011 cohort and have improved somewhat since. However, payment progress has declined.
  • College attendance is associated with significantly higher homeownership rates regardless of debt status. Yet, student debt appears to dampen homeownership rates among those with the same level of education.
  • College attendance appears to mitigate the impact of economic background on homeownership rates.

 

 

 


 

Also see:

 


 

 

 

Retailers cut tens of thousands of jobs. Again. — from money.cnn.com by Paul R. La Monica
The dramatic reshaping of the American retail industry has, unfortunately, led to massive job losses in the sector.

Excerpt (emphasis DSC):

The federal government said Friday that retailers shed nearly 30,000 jobs in March. That follows a more than 30,000 decline in the number of retail jobs in the previous month.

So-called general merchandise stores are hurting the most.

That part of the sector, which includes struggling companies like Macy’s, Sears, and J.C. Penney, lost 35,000 jobs last month. Nearly 90,000 jobs have been eliminated since last October.

“There is no question that the Amazon effect is overwhelming,” said Scott Clemons, chief investment strategist of private banking for BBH. “There has been a shift in the way we buy things as opposed to a shift in the amount of money spent.”

To that end, Amazon just announced plans to hire 30,000 part-time workers.

 

From DSC:
One of the reasons that I’m posting this item is for those who say disruption isn’t real…it’s only a buzz word…

A second reason that I’m posting this item is because those of us working within higher education should take note of the changes in the world of retail and learn the lesson now before the “Next Amazon.com of Higher Education*” comes on the scene. Though this organization has yet to materialize, the pieces of its foundation are beginning to come together — such as the ingredients, trends, and developments that I’ve been tracking in my “Learning from the Living [Class] Room” vision.

This new organization will be highly disruptive to institutions of traditional higher education.

If you were in an influential position at Macy’s, Sears, and/or at J.C. Penney today, and you could travel back in time…what would you do?

We in higher education have the luxury of learning from what’s been happening in the retail business. Let’s be sure to learn our lesson.

 



 

* Effective today, what I used to call the “Forthcoming Walmart of Education — which has already been occurring to some degree with things such as MOOCs and collaborations/partnerships such as Georgia Institute of Technology, Udacity, and AT&T — I now call the “Next Amazon.com of Higher Education.”

Cost. Convenience. Selection. Offering a service on-demand (i.e., being quick, responsive, and available 24×7). <– These all are powerful forces.

 



 

P.S. Some will say you can’t possibly compare the worlds of retail and higher education — and that may be true as of 2017. However, if:

  • the costs of higher education keep going up and we continue to turn a deaf ear to the struggling families/students/adult learners/etc. out there
  • alternatives to traditional higher education continue to come on the landscape
  • the Federal Government continues to be more open to financially supporting such alternatives
  • technologies such as artificial intelligence, machine learning, deep learning continue to get better and more powerful — to the point that they can effectively deliver a personalized education (one that is likely to be fully online and that utilizes a team of specialists to create and deliver the learning experiences)
  • people lose their jobs to artificial intelligence, robotics, and automation and need to quickly reinvent themselves

…I can assure you that people will find other ways to make ends meet. The Next Amazon.com of Education will be just what they are looking for.

 



 

 

 

From DSC:
It seems to me that we are right on the precipice of major changes — throughout the globe — that are being introduced by the growing use and presence of automation, robotics, and artificial intelligence/machine learning/deep learning, as well as other emerging technologies. But it’s not just the existence of these technologies, but it’s also that the pace of adoption of these technologies continues to increase.

These things made me wonder….what are the ramifications of the graphs below — and this new trajectory/pace of change that we’re on — for how we accredit new programs within higher education?

For me, it speaks to the need for those of us who are working within higher education to be more responsive, and we need to increase our efforts to provide more lifelong learning opportunities. People are going to need to reinvent themselves over and over again. In order for higher education to be of the utmost service to people, the time that it takes to accredit a program must be greatly reduced in cost and in time.


 

 

 

 

 

 

 

 

 

 

 


Somewhat relevant addendums:


 

A quote from “Response: What Teaching in the Year 2047 Might Look Like

To end the metaphor, what I am simply trying to say is that schools cannot afford to evolve at ¼ of the pace the world is around it and not face the possibility of becoming dangerously irrelevant. So, to answer the question – do I think the classrooms of 2040 look like the classrooms of today? Yes, I think they look more like them than they do not. Unfortunately, in my opinion, that is not the way to best serve our kids in our ever-changing world. Let me be clear, great teaching and instruction has not fundamentally changed in the past 2000 years and will not in the next 30. The context of learning and doing our best to meet the needs of the society we are preparing kids for is how and why schools must be revolutionized, not simply evolve at their own pace.

 


An excerpt from “
The global forces inspiring a new narrative of progress” (from mckinsey.com by Ezra Greenberg, Martin Hirt, and Sven Smit; emphasis DSC):

The next three tensions highlight accelerating industry disruption. Digitization, machine learning, and the life sciences are advancing and combining with one another to redefine what companies do and where industry boundaries lie. We’re not just being invaded by a few technologies, in other words, but rather are experiencing a combinatorial technology explosion. Customers are reaping some of the rewards, and our notions of value delivery are changing. In the words of Alibaba’s Jack Ma, B2C is becoming “C2B,” as customers enjoy “free” goods and services, personalization, and variety. And the terms of competition are changing: as interconnected networks of partners, platforms, customers, and suppliers become more important, we are experiencing a business ecosystem revolution.

 

38% of American Jobs Could be Replaced by Robots, According to PwC Report — from bigthink.com by David Ryan Polgar

Excerpt:

Nearly 4 out of 10 American jobs may be replaced through automation by the early 2030s, according to a new report by Price Waterhouse Cooper (PwC). In the report, the United States was viewed as the country most likely to lost jobs through automation–ahead of the UK, Germany, and Japan. This is probably not what the current administration had in mind with an “America First” policy.

 

 

 

 

The disruption of digital learning: Ten things we have learned — from joshbersin.com

Excerpt:

Over the last few months I’ve had a series of meetings with Chief Learning Officers, talent management leaders, and vendors of next generation learning tools. My goal has been simple: try to make sense of the new corporate learning landscape, which for want of a better word, we can now call “Digital Learning.” In this article I’d like to share ten things to think about, with the goal of helping L&D professionals, HR leaders, and business leaders understand how the world of corporate learning has changed.

 

Digital Learning does not mean learning on your phone, it means “bringing learning to where employees are.” 

It is a “way of learning” not a “type of learning.”

 

 

 

 

 

 

The traditional LMS is no longer the center of corporate learning, and it’s starting to go away.

 

 

 

What Josh calls a Distributed Learning Platform, I call a Learning Ecosystem:

 

 



Also see:

  • Watch Out, Corporate Learning: Here Comes Disruption — from forbes.com by Josh Bersin
    Excerpt:
    The corporate training market, which is over $130 billion in size, is about to be disrupted. Companies are starting to move away from their Learning Management Systems (LMS), buy all sorts of new tools for digital learning, and rebuild a whole new infrastructure to help employees learn. And the impact of GSuite,  Microsoft Teams, Slack, and Workplace by Facebook could be enormous.

    We are living longer, jobs are changing faster than ever, and automation is impinging on our work lives more every day. If we can’t look things up, learn quickly, and find a way to develop new skills at work, most of us would prefer to change jobs, rather than stay in a company that doesn’t let us reinvent ourselves over time.

 



 

 

The Enterprise Gets Smart
Companies are starting to leverage artificial intelligence and machine learning technologies to bolster customer experience, improve security and optimize operations.

Excerpt:

Assembling the right talent is another critical component of an AI initiative. While existing enterprise software platforms that add AI capabilities will make the technology accessible to mainstream business users, there will be a need to ramp up expertise in areas like data science, analytics and even nontraditional IT competencies, says Guarini.

“As we start to see the land grab for talent, there are some real gaps in emerging roles, and those that haven’t been as critical in the past,” Guarini  says, citing the need for people with expertise in disciplines like philosophy and linguistics, for example. “CIOs need to get in front of what they need in terms of capabilities and, in some cases, identify potential partners.”

 

 

 

Asilomar AI Principles

These principles were developed in conjunction with the 2017 Asilomar conference (videos here), through the process described here.

 

Artificial intelligence has already provided beneficial tools that are used every day by people around the world. Its continued development, guided by the following principles, will offer amazing opportunities to help and empower people in the decades and centuries ahead.

Research Issues

 

1) Research Goal: The goal of AI research should be to create not undirected intelligence, but beneficial intelligence.

2) Research Funding: Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies, such as:

  • How can we make future AI systems highly robust, so that they do what we want without malfunctioning or getting hacked?
  • How can we grow our prosperity through automation while maintaining people’s resources and purpose?
  • How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI?
  • What set of values should AI be aligned with, and what legal and ethical status should it have?

3) Science-Policy Link: There should be constructive and healthy exchange between AI researchers and policy-makers.

4) Research Culture: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI.

5) Race Avoidance: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards.

Ethics and Values

 

6) Safety: AI systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible.

7) Failure Transparency: If an AI system causes harm, it should be possible to ascertain why.

8) Judicial Transparency: Any involvement by an autonomous system in judicial decision-making should provide a satisfactory explanation auditable by a competent human authority.

9) Responsibility: Designers and builders of advanced AI systems are stakeholders in the moral implications of their use, misuse, and actions, with a responsibility and opportunity to shape those implications.

10) Value Alignment: Highly autonomous AI systems should be designed so that their goals and behaviors can be assured to align with human values throughout their operation.

11) Human Values: AI systems should be designed and operated so as to be compatible with ideals of human dignity, rights, freedoms, and cultural diversity.

12) Personal Privacy: People should have the right to access, manage and control the data they generate, given AI systems’ power to analyze and utilize that data.

13) Liberty and Privacy: The application of AI to personal data must not unreasonably curtail people’s real or perceived liberty.

14) Shared Benefit: AI technologies should benefit and empower as many people as possible.

15) Shared Prosperity: The economic prosperity created by AI should be shared broadly, to benefit all of humanity.

16) Human Control: Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives.

17) Non-subversion: The power conferred by control of highly advanced AI systems should respect and improve, rather than subvert, the social and civic processes on which the health of society depends.

18) AI Arms Race: An arms race in lethal autonomous weapons should be avoided.

Longer-term Issues

 

19) Capability Caution: There being no consensus, we should avoid strong assumptions regarding upper limits on future AI capabilities.

20) Importance: Advanced AI could represent a profound change in the history of life on Earth, and should be planned for and managed with commensurate care and resources.

21) Risks: Risks posed by AI systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact.

22) Recursive Self-Improvement: AI systems designed to recursively self-improve or self-replicate in a manner that could lead to rapidly increasing quality or quantity must be subject to strict safety and control measures.

23) Common Good: Superintelligence should only be developed in the service of widely shared ethical ideals, and for the benefit of all humanity rather than one state or organization.

 

 

 

Excerpts:
Creating human-level AI: Will it happen, and if so, when and how? What key remaining obstacles can be identified? How can we make future AI systems more robust than today’s, so that they do what we want without crashing, malfunctioning or getting hacked?

  • Talks:
    • Demis Hassabis (DeepMind)
    • Ray Kurzweil (Google) (video)
    • Yann LeCun (Facebook/NYU) (pdf) (video)
  • Panel with Anca Dragan (Berkeley), Demis Hassabis (DeepMind), Guru Banavar (IBM), Oren Etzioni (Allen Institute), Tom Gruber (Apple), Jürgen Schmidhuber (Swiss AI Lab), Yann LeCun (Facebook/NYU), Yoshua Bengio (Montreal) (video)
  • Superintelligence: Science or fiction? If human level general AI is developed, then what are likely outcomes? What can we do now to maximize the probability of a positive outcome? (video)
    • Talks:
      • Shane Legg (DeepMind)
      • Nick Bostrom (Oxford) (pdf) (video)
      • Jaan Tallinn (CSER/FLI) (pdf) (video)
    • Panel with Bart Selman (Cornell), David Chalmers (NYU), Elon Musk (Tesla, SpaceX), Jaan Tallinn (CSER/FLI), Nick Bostrom (FHI), Ray Kurzweil (Google), Stuart Russell (Berkeley), Sam Harris, Demis Hassabis (DeepMind): If we succeed in building human-level AGI, then what are likely outcomes? What would we like to happen?
    • Panel with Dario Amodei (OpenAI), Nate Soares (MIRI), Shane Legg (DeepMind), Richard Mallah (FLI), Stefano Ermon (Stanford), Viktoriya Krakovna (DeepMind/FLI): Technical research agenda: What can we do now to maximize the chances of a good outcome? (video)
  • Law, policy & ethics: How can we update legal systems, international treaties and algorithms to be more fair, ethical and efficient and to keep pace with AI?
    • Talks:
      • Matt Scherer (pdf) (video)
      • Heather Roff-Perkins (Oxford)
    • Panel with Martin Rees (CSER/Cambridge), Heather Roff-Perkins, Jason Matheny (IARPA), Steve Goose (HRW), Irakli Beridze (UNICRI), Rao Kambhampati (AAAI, ASU), Anthony Romero (ACLU): Policy & Governance (video)
    • Panel with Kate Crawford (Microsoft/MIT), Matt Scherer, Ryan Calo (U. Washington), Kent Walker (Google), Sam Altman (OpenAI): AI & Law (video)
    • Panel with Kay Firth-Butterfield (IEEE, Austin-AI), Wendell Wallach (Yale), Francesca Rossi (IBM/Padova), Huw Price (Cambridge, CFI), Margaret Boden (Sussex): AI & Ethics (video)

 

 

 

A smorgasboard of ideas to put on your organization’s radar! [Christian]

From DSC:
At the Next Generation Learning Spaces Conference, held recently in San Diego, CA, I moderated a panel discussion re: AR, VR, and MR.  I started off our panel discussion with some introductory ideas and remarks — meant to make sure that numerous ideas were on the radars at attendees’ organizations. Then Vinay and Carrie did a super job of addressing several topics and questions (Mary was unable to make it that day, as she got stuck in the UK due to transportation-related issues).

That said, I didn’t get a chance to finish the second part of the presentation which I’ve listed below in both 4:3 and 16:9 formats.  So I made a recording of these ideas, and I’m relaying it to you in the hopes that it can help you and your organization.

 


Presentations/recordings:


 

Audio/video recording (187 MB MP4 file)

 

 


Again, I hope you find this information helpful.

Thanks,
Daniel

 

 

 

Growth of AI Means We Need To Retrain Workers… Now — from forbes.com by Ryan Wibberley

Excerpt:

On the more positive side, AI could take over mundane, repetitive tasks and enable the workers who perform them to take on more interesting and rewarding work. But that will also mean many workers will need to be retrained. If you’re in a business where AI-based automation could be a potentially significant disruptor, then the time to invest in worker training and skill development is now. One could argue that AI will impact just about every industry. For example, in the financial services industry, we have already seen the creation of the robo advisor. While I don’t believe that the robo advisor will fully replace the human financial advisor because of the emotional aspects of investing, I do believe that it will play a part in the relationship with an advisor and his/her client.

 
© 2016 Learning Ecosystems