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:

 

 

VR resumes are catching the eyes of industry recruiters — from vrscout.com by Kyle Melnick

 

 

Excerpt:

A brand new market requires a brand new kind of CV.

Getting creative with a resume or job application is a common tactic among job-seekers looking to stand out from the pack. A simple Google search reveals incredible examples of resumes iced into cakes, programmed into video games, hidden inside QR codes, the list goes on. In most cases however, the most engaging CV is always the most successful, which is why many developers looking to get into the VR industry are using the immersive technology to build some of the coolest resumes you’ve ever seen.

Through a variety of methods, from VR art programs to 360-degree videos, amateur hopefuls have designed incredible works of art that creatively display their information while simultaneously showcasing their skills in the medium. One art community in particular, Sketchfab, has been a popular platform for distributing VR resumes and applications. Here are some of the best examples of brilliant self-advertising on the web (Click and hold to change angles, zoom in/out and move around the pieces):

 

 
 

Report: Overtime, Low Wages Causing Educator Stress — from thejournal.com by Sri Ravipati

 

Excerpt:

As the role of the educator continues to evolve, it is necessary to take a look at some of the challenges they face day-to-day: What contributes to educators’ stress? Have the recent changes in the federal government added to their stress at all? How can technology help? To find out the answers to these questions, online learning company Course Hero polled educators about their economic satisfaction, work-related stress, classroom technology and even how the new Trump administration impacts them.

The company recently released its inaugural “State of the Educator Survey” report, which includes findings from a 68-question survey conducted in January. Course Hero polled 412 higher ed professors and 117 high school Advanced Placement (AP) teachers who work full-time and part-time in a variety of disciplines. As it turns out, all of the aforementioned topics have contributed to increased stress felt by nearly half of the survey participants. In fact, five times as many educators reported increased rather than decreased stress, with 42 percent responding that their job became more stressful in the last year (compared to 8 percent who reported a decrease). Exactly half of respondents said their stress level stayed the same.

 

 

 

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

 

 

 

From DSC:
In the future, will Microsoft — via data supplied by LinkedIn and Lynda.com — use artificial intelligence, big data, and blockchain-related technologies to match employers with employees/freelancers?  If so, how would this impact higher education? Badging? Credentialing?

It’s something to put on our radars.

 

 

 

 

 

Excerpt:

A sneak peak on Recruitment in AI era
With global talent war at its peak, organisations are now looking at harnessing Artificial Intelligence (AI) capabilities, to use search optimisation tools, data analytics, and talent mapping to reach out to the right talent for crucial job roles. Technology has been revolutionising the way recruitment works with the entire process being now automated with ATS and other talent management softwares. This saves time and costs involved with recruiting for HR managers, whilst allowing them to do away with third-party service providers for talent sourcing such as employment bureaus and traditional recruitment agencies. With modern talent acquisition technology empowered by AI, the time taken for recruitment is halved and search narrowed to reach out to only the best talent that matches job requirements. There is no need for human intervention and manual personality matching to choose the best candidates for suitable job roles.

Talent mapping, with the help of big data, is definitely the next step in recruitment technology. With talent mapping, recruiters can determine their candidate needs well in advance and develop a strategic plan for hiring long-term. This includes filling any skill gaps, bolstering the team for sudden changes in the workplace, or just simply having suitable talent in mind for the future. All of these, when prepared ahead of time, can save companies the trouble and time in future. Recruiters who are able to understand how AI works, harness the technology to save on time and costs will be rewarded with improved quality of hires, enhanced efficiency, more productive workforce and less turnover.

 

Summer 2017 Human++ — fromcambridge.nuvustudio.com
Human-Machine Intelligence, Hacking Drones, Bio Fashion, Augmented Video Games, Aerial Filmmaking, Smart Tools, Soft Robotics and more!

Excerpt:

NuVu is a place where young students grow their spirit of innovation. They use their curiosity and creativity to explore new ideas, and make their concepts come to life through our design process. Our model is based on the architecture studio model, and every Summer we use imaginative themes to frame two-week long Studios in which students dive into hands-on design, engineering, science, technology, art and more!

 

 

From DSC:
At the recent
Next Generation Learning Spaces Conference, in my introductory piece for our panel discussion, I relayed several ideas/areas that should be on our institutions’ radars. That is, at least someone at each of our institutions of higher education should be aware of these things and be pulse-checking them as time goes by.

 

 

 

 

 

 

 

 

 

 

 

One of these ideas/areas involved the use of blockchain technologies:

 

 

If #blockchain technologies are successful within the financial/banking world, then it’s highly likely that other use cases will be developed as well (i.e., the trust in blockchain-enabled applications will be there already).

Along those lines, if that occurs, then colleges and universities are likely to become only 1 of the feeds into someone’s cloud-based, lifelong learning profile. I’ve listed several more sources of credentials below:

 

 

Given the trend towards more competency-based education (CBE) and the increased experimentation with badges, blockchain could increasingly move onto the scene.

In fact, I could see a day when an individual learner will be able to establish who can and can’t access their learner profile, and who can and can’t feed information and updates into it.

Artificial intelligence and big data also come to mind here…and I put Microsoft on my radar a while back in this regard; as Microsoft (via LinkedIn and Lynda.com) could easily create online-based marketplaces matching employers with employees/freelancers.

 

 

 


Along these lines, see:


 

  • The Mainstreaming of Alternative Credentials in Postsecondary Education — from by Deborah Keyek-Franssen
    Excerpt:

    • The Context of Alternative Credentials
      The past few years have seen a proliferation of new learning credentials ranging from badges and bootcamp certifications to micro-degrees and MOOC certificates. Although alternative credentials have been part of the fabric of postsecondary education and professional development for decades—think prior learning assessments like Advanced Placement or International Baccalaureate exams, or industry certifications—postsecondary institutions are increasingly unbundling their degrees and validating smaller chunks of skills and learning to provide workplace value to traditional and non-traditional students alike.
      Many are experimenting with alternative credentials to counter the typical binary nature of a degree. Certifications of learning or skills are conferred after the completion of a course or a few short courses in a related field. Students do not have to wait until all requirements for a degree are met before receiving a certificate of learning, but instead can receive one after a much shorter period of study. “Stackable” credentials are combined to be the equivalent of an undergraduate or graduate certificate (a micro-degree), or even a degree.
    • The National Discussion of Alternative Credentials
      Discussions of alternative credentials are often responses to a persistent and growing critique of traditional higher educational institutions’ ability to meet workforce needs, especially because the cost to students for a four-year degree has grown dramatically over the past several decades. The increasing attention paid to alternative credentials brings to the fore questions such as what constitutes a postsecondary education, what role universities in particular should play vis-à-vis workforce development, and how we can assess learning and mastery.

 

 


Addendums added on 3/4/17, that show that this topic isn’t just for higher education, but could involve K-12 as well:


 

 

 

 

 
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