Has cutting your way to greatness ever worked? — from insidehighered.com by Matt Reed
 I can’t think of a time that it has, yet it remains a common default mode.  

Excerpt:

Has cutting your way to greatness ever worked?

I can’t think of a time that it has, yet it remains a common default mode.

In places with declining enrollments and without generous external benefactors, it’s easy to fall into the trap of constant cutting. Each year is a fresh emergency, bringing another round of short-term patches and “temporary” workarounds that quickly become new baselines.

Over time, though, the cuts do damage that starts to show up in enrollments. Too many classes cancelled or calls unreturned lead to attrition, which leads to calls for still more cuts. Cut an off-campus location to save money, and whoops, you lose its enrollments, leading to a need for more cutting. Add an inexorably rising underlying cost — say, just hypothetically, health insurance — and you have the makings of a death spiral.

The task for the emerging generation of leadership isn’t just fiscal; it’s narrative.

 

 

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?
 

Looking to build the campus of tomorrow? 5 trends you should know — from ecampusnews.com by Laura Ascione
Today’s trends will bring about a new vision for the traditional college campus.

Excerpt:

“Innovations in physical space must be made to accommodate demands for accessibility, flexibility and affordability,” according to The State of Higher Education in 2017, a report from professional services firm Grant Thornton.

Changes in infrastructure are being driven by a handful of trends, including:

  • Digital technology is decoupling access to the classroom and information from any specific geographic location.
  • Learning is becoming more “modular,” credentialing specific competencies, such as certificates and badges,, rather than the model of four years to a degree via fixed-class schedules. This requires a less broad range of academic buildings on campus.
  • Students will engage with their coursework at their own time and pace, as they do in every other aspect of their lives.
  • Price pressure on colleges will create incentives for cost efficiencies, discouraging the fixed-cost commitment embodied in physical structures.
  • Deferred maintenance is a problem so large that it can’t be solved by most colleges within their available resources; the result may be reducing the physical plant footprint or just letting it deteriorate further.

These developments will prompt physical space transformation that will lead to a new kind of campus.

 

 


The State of Higher Education in 2017 — from grantthornton.com

 

Browse the report articles:

 

 

Innovative thinking will be vital to successfully moving into the future.

 

 

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.

 



 

 

 

Ideo studied innovation in 100+ companies – here’s what it found — from fastcodesign.com by Katharine Schwab
Innovation is hard to pin down, but with these six insights Ideo says it’s cracking the code.

Excerpt:

  1. Don’t Get Stuck On One Idea (Or Even Three)
  2. Everyone Should Feel Comfortable Challenging The Status Quo
  3. A Clear, Consistent Purpose Fuels Innovation
  4. Remote Team Members Are Actually Good For Collaboration
  5. Touch Base Daily–It Leads To More Successful Launches
  6. Leaders, Your Job Is To Help Your Team–Not The Other Way Around

 

 

 

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)

 

 

 

From DSC:
The following questions came to my mind today:

  • What are the future ramifications — for higher education — of an exponential population growth curve, especially in regards to providing access?
  • Are our current ways of providing an education going to hold up?
  • What about if the cost of obtaining a degree maintains its current trajectory?
  • What changes do we need to start planning for and/or begin making now?

 

 

 

 

 

Links to sources:

 

 

The 2017 Top 10 IT Issues — a new report from Educause
It’s all about student success.

Excerpt:

Colleges and universities are concentrating on student success to address concerns about the costs, value, and outcomes of higher education. Student success initiatives are making use of every available resource and opportunity and involving every relevant stakeholder. Institutional technology is all three: resource, opportunity, and stakeholder.

The 2017 issues list identifies the four focus areas for higher education information technology:

  • Develop the IT foundations
  • Develop the data foundations
  • Ensure effective leadership
  • Enable successful students

These issues and focus areas are not just about today. Higher education information technology is very clearly building foundations for student success to last into the future.

 

 

 


 

Also see:

Educause Announces Top IT Issues, Trends and Tech Report for 2017 — from campustechnology.com by Dian Schaffhauser

Excerpt:

Expanding on the preview of its annual ranking of IT issues for higher education released last fall, Educause today announced its full report on the key issues, trends and technologies poised to impact higher ed in 2017. The prevailing themes across the board, according to the higher education technology association with a membership of 2,100 colleges, universities and other education organizations: information security, student success and data-informed decision-making.

The top 10 IT issues for 2017, reiterated in today’s report:

  1. Information security;
  2. Student success and completion;
  3. Data-informed decision-making;
  4. Strategic leadership;
  5. Sustainable funding;
  6. Data management and governance;
  7. Higher education affordability;
  8. Sustainable staffing;
  9. Next-generation enterprise IT; and
  10. Digital transformation of learning.

 

 

 

How will leadership change in the cognitive era? — from forbes.com by Chris Cancialosi

Excerpt:

Technological innovation is continuing to accelerate on a hockey stick growth curve. Companies like IBM, Microsoft, Facebook, and Amazon are bringing cognitive computing capability to the masses. And it’s only a matter of time until nearly every aspect of our work and personal lives are impacted.

These advances are still relatively new. Time will tell when and how they change things, but it will happen, and it will happen quickly. In a recent article, Steve Denning reminds us that a repeating pattern of massive transformation has occurred regularly over the last 250 years.

With massive change at our doorstep, now is the time to begin a collective discussion to help leaders navigate this new age.

 

Leadership behaviors that yielded success in the past may no longer be effective as the way we work changes over time.

 

 

From DSC:
First, some items regarding the enormous emphasis being put towards the use of robotics and automation:

  • $18.867 billion paid to acquire 50 robotics companies in 2016 — from robohub.org by Frank Tobe
    Excerpt:
    2016 was a banner year for acquisitions of companies involved in robotics and automation: 50 sold; 11 for amounts over $500 million; five were over a billion. 30 of the 50 companies disclosed transaction amounts which totaled up to a colossal $18.867 billion!
    .
  • 2017: The year people are forced to learn new skills… or join the Lost Generation — from enterpriseirregulars.com by Phil Fersht
    Excerpt (emphasis DSC):
    Let’s cut to the chase – there have never been times as uncertain as these in the world of business. There is no written rule-book to follow when it comes to career survival. The “Future of Work” is about making ourselves employable in a workforce where the priority of business leaders is to invest in automation and digital technology, more than training and developing their own workforces. As our soon-to-be-released State of Operations and Outsourcing 2017 study, conducted in conjunction with KPMG across 454 major enterprise buyers globally, shows a dramatic shift in priorities from senior managers (SVPs and above), where 43% are earmarking significant investment in robotic automation of processes, compared with only 28% placing a similar emphasis on training and change management. In fact, the same number of senior managers are as focused on cognitive computing as their own people… yes, folks, this is the singularity of enterprise operations, where cognitive computing now equals employees’ brains when it comes to investment!

    My deep-seated fear for today’s workforce is that we’re in danger of becoming this “Lost Generation” of workers if we persist in relying on what we already know, versus avoiding learning new skills that business leaders now need. We have to become students again, put our egos aside, and broaden our capabilities to avoid the quicksand of legacy executives no longer worth employing.

 

 

 

Below are some other resources along these lines:

 

From DSC:
Given that these trends continue (i.e., to outsource work to software and to robots), what will the ramifications be for:

  • Society at large? Will enough people have enough income to purchase the products/services made by the robots and the software?
  • Will there be major civil unrest / instability? Will crime rates shoot through the roof as peoples’ desperation and frustration escalate?
  • How we should change our curricula within K-12?
  • How should we change our curricular within higher education?
  • How should corporate training & development departments/groups respond to these trends?
  • Is there some new criteria that we need to use (or increase the usage of) in selecting C-level executives?

People don’t want to hear about it. But if the only thing that the C-level suites out there care about is maximizing profits and minimizing costs — REGARDLESS of what happens to humankind — then we are likely going to be creating a very dangerous future. Capitalism will have gone awry. (By the way, the C-level suite is probably making their decisions based upon how their performance is judged by Wall Street and by shareholders. So I can’t really put all the blame on them. Perhaps the enemy is ourselves…?) 

Bottom line: We need to be careful which technologies we implement — and how they are implemented. We need to create a dream in our futures, not a nightmare. We need people at the helms who care about their fellow humankind, and who use the power of these technologies responsibly.

 

 
© 2016 Learning Ecosystems