Making sure the machines don’t take over — from raconteur.net by Mark Frary
Preparing economic players for the impact of artificial intelligence is a work in progress which requires careful handling

 

From DSC:
This short article presents a balanced approach, as it relays both the advantages and disadvantages of AI in our world.

Perhaps it will be one of higher education’s new tasks — to determine the best jobs to go into that will survive the next 5-10+ years and help you get up-to-speed in those areas. The liberal arts are very important here, as they lay a solid foundation that one can use to adapt to changing conditions and move into multiple areas. If the C-suite only sees the savings to the bottom line — and to *&^# with humanity (that’s their problem, not mine!) — then our society could be in trouble.

 

Also see:

 

 

 

7 out of the ordinary things job hunters can do to get noticed on LinkedIn — from finance.yahoo.com by Hannah Morgan

Excerpt:

Even if you use all the right job buzz words, your LinkedIn profile still may not catch the attention of your potential new boss when on a job search. Isn’t it time you stopped lurking on LinkedIn and took control of your search?

Before you start applying these new ideas, search to see how many people or companies have viewed your profile. LinkedIn now summarizes this information for you when you view your profile. You will see two numbers immediately below your summary section. LinkedIn tells you how many people or companies have viewed your profile and how many people have viewed your posts. (You may also see the number of connections you have.) If you click on either number it will take you to a new page with greater detail. Write these numbers down and check them after you’ve begun implementing your new actions on LinkedIn. You will notice a difference. And this will help you in your search for a new job through the platform.

  • Publish an article on LinkedIn.
  • Create a career summary using SlideShare.
  • Like, comment or share one article every day.
  • Tag someone.
  • Reach out with a personalized invite to connect.
  • Turn on LinkedIn’s Open Candidate feature.
  • Give a great testimonial.

 

 

Former interns tell how they landed a first job — from nytimes.com by Jeff Selingo

Excerpt:

In recent years, internships have gone from nice-to-have-on-a-résumé to absolutely critical. Employers today go on to hire about 50 percent of their interns as full-time workers, according to the Collegiate Employment Research Institute at Michigan State University. And the share is growing every year in industries like construction, consulting, accounting and scientific services.

This new emphasis has upended the traditional recruiting calendar on campuses nationwide. With more companies drawing from their intern pools, recruiters have shifted their attention from hiring soon-to-graduate seniors to scoping out juniors, even as early as the fall term, for summer internships. Postings for internships now make up a significant proportion of the overall entry-level job openings in engineering, graphic design, communications, marketing and information technology, according to Burning Glass Technologies, a data analytics company that studies the job market.

“There was a time when 50 employers came to recruit for interns,” said Patricia Rose, director of career services at the University of Pennsylvania. “Now we have 180. They want to wrap up talent before anyone else.”

 

 

Want to effectively raise your LinkedIn profile? Follow these tips! — from medium.com by Larry Kim

Excerpt:

A killer LinkedIn profile is mandatory if you want to grow your personal brand and company. Even though you’re busy, LinkedIn is one place you can’t forget. The more you put in, the more you’ll get out of it. Here are 22 top tips to effectively boost your LinkedIn profile.

 

 

 

 

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?
 

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.

 



 

 

A Guide to Internships: Finding Hands-On Experience Locally & Abroad — from learnhowtobecome.org

Excerpt:

A good internship may be the deciding factor for employers looking to hire recent graduates. The professional experience acquired in an internship could mean the candidate is more likely to provide value from day one. Find out the ways an internship can boost a career, what type of internship is the right fit and tips for getting your dream internship locally and abroad.
How Internships Benefit Careers

From hands-on experience to networking, internships offer students experiences they often will not find in the classroom. The following list includes some of the reasons why internships are beneficial to students, and a great way to get a head start on a career path.

Searching for and starting an internship can be intimidating. The list below offers students advice on how to find the right internship and be successful once they start.

 

Professional networking: Since most job positions are not advertised, professional networking plays a huge role in any successful job search. As an intern, students meet people who can become part of their professional network, which may help them find a job after graduation. Even if there isn’t a position available in the organization they interned for, the contacts students make can lead to a job somewhere else.

 

 

 

 

Perfect marriage between universities and K12 public schools — from huffingtonpost.com by Dr. Rod Berger

 

Excerpt:

I sat down with Dr. Jeanice Kerr Swift at this year’s AASA conference in New Orleans to learn about the unique advantage of running a public school district that resides alongside one of our nation’s most prominent universities. The University of Michigan provides the district of Ann Arbor with rich partnerships that lift the learning experiences of the children in the community. Kerr Swift is delighted to have the enthusiasm of not only the University but the business community in reaching out to the students of Ann Arbor.

The implementation of real world projects matches University of Michigan scientists with teachers and students to enrich school learning environments. One example is the Woven Wind program that provides real life wind turbine applications. Students learn, and teachers have their classes bolstered by the input of advanced experimentation. Project Lead the Way is another example that is providing modules for classroom learning.

According to Jeanice Kerr Swift, technology should support and strengthen learning, not stand in the place of person-to-person engagement. Devices are there to serve and enhance, not replace teacher-student collaboration and critical thinking. Kerr Swift believes there is a balance of the “Cs” to consider: collaboration, connection, and community. If all the “Cs” are listening and working together, then a school district can thrive.

Jeanice Kerr Swift certainly makes the balance look easy and enviable in Ann Arbor Michigan.

 

 

 

 

 

The Blockchain Revolution and Higher Education — from er.educause.edu by Don Tapscott and Alex Tapscott
The blockchain provides a rich, secure, and transparent platform on which to create a global network for higher learning. This Internet of value can help to reinvent higher education in a way the Internet of information alone could not.

Excerpt:

What will be the most important technology to change higher education? In our view, it’s not big data, the social web, MOOCs, virtual reality, or even artificial intelligence. We see these as components of something new, all enabled and transformed by an emerging technology called the blockchain.

OK, it’s not the most sonorous word ever, sounding more like a college football strategy than a transformative technology. Yet, sonorous or not, the blockchain represents nothing less than the second generation of the Internet, and it holds the potential to disrupt money, business, government, and yes, higher education.

The opportunities for innovators in higher education fall into four categories:

  • Identity and Student Records: How we identify students; protect their privacy; measure, record, and credential their accomplishments; and keep these records secure
  • New Pedagogy: How we customize teaching to each student and create new models of learning
  • Costs (Student Debt): How we value and fund education and reward students for the quality of their work
  • The Meta-University: How we design entirely new models of higher education so that former MIT President Chuck Vest’s dream can become a reality1

The blockchain may help us change the relationships among colleges and universities and, in turn, their relationship to society.

Let us explain.

 

What if there was an Internet of value — a global, distributed, highly secure platform, ledger, or database where we could store and exchange things of value and where we could trust each other without powerful intermediaries? That is the blockchain.

 

 

From DSC:
The quote…

In 2006, MIT President Emeritus Vest offered a tantalizing vision of what he called the meta-university. In the open-access movement, he saw “a transcendent, accessible, empowering, dynamic, communally constructed framework of open materials and platforms on which much of higher education worldwide can be constructed or enhanced.”

…made me wonder if this is where a vision that I’m tracking called Learning from the Living [Class] Room is heading. Also, along these lines, futurist Thomas Frey believes

“I’ve been predicting that by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet,” Frey, the senior futurist at the DaVinci Institute think tank, tells Business Insider. (source)

Blockchain could be a key piece of this vision.

 

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

 

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)

 

 

 

Blockchain: Letting students own their credentials — from campustechnology.com by Dian Schaffhauser
Very soon this nascent technology could securely enable registrars to help students verify credentials without the hassle of ordering copies of transcripts.

Excerpt:

While truth may seem evasive on many fronts, a joint academic and industry effort is underway to codify it for credentialing. At the core of the effort is blockchain, a trust technology developed for bitcoin and used in solving other forms of validation between individuals and organizations. Still in its nascent stage, the technology could, within just a year or two, provide the core services that would enable schools to stop acting as if they own proof of learning and help students verify their credentials as needed — without waiting on a records office to do it for them.

 

From DSC:
This article reminded me of two of the slides from my NGLS 2017 presentation back from February:

 

 

 

Also see:

 

 
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