New Google Earth has exciting features for teachers — from by Richard Chang


Google has recently released a brand new version of Google Earth for both Chrome and Android. This new version has come with a slew of nifty features teachers can use for educational purposes with students in class. Following is a quick overview of the most fascinating features…







The Dark Secret at the Heart of AI — from by Will Knight
No one really knows how the most advanced algorithms do what they do. That could be a problem.


The mysterious mind of this vehicle points to a looming issue with artificial intelligence. The car’s underlying AI technology, known as deep learning, has proved very powerful at solving problems in recent years, and it has been widely deployed for tasks like image captioning, voice recognition, and language translation. There is now hope that the same techniques will be able to diagnose deadly diseases, make million-dollar trading decisions, and do countless other things to transform whole industries.

But this won’t happen—or shouldn’t happen—unless we find ways of making techniques like deep learning more understandable to their creators and accountable to their users. Otherwise it will be hard to predict when failures might occur—and it’s inevitable they will. That’s one reason Nvidia’s car is still experimental.


“Whether it’s an investment decision, a medical decision, or maybe a military decision, you don’t want to just rely on a ‘black box’ method.”


This raises mind-boggling questions. As the technology advances, we might soon cross some threshold beyond which using AI requires a leap of faith. Sure, we humans can’t always truly explain our thought processes either—but we find ways to intuitively trust and gauge people. Will that also be possible with machines that think and make decisions differently from the way a human would? We’ve never before built machines that operate in ways their creators don’t understand. How well can we expect to communicate—and get along with—intelligent machines that could be unpredictable and inscrutable? These questions took me on a journey to the bleeding edge of research on AI algorithms, from Google to Apple and many places in between, including a meeting with one of the great philosophers of our time.
 Archaeology Virtual Reality Content for Tourism, Education and Entertainment




An excerpt from their website:

Head mounted virtual reality devices have an enormous potential to provide non-destructive immersive experiences for visitors to archaeological sites and museums as well as for researchers and educators. By creating a model that suggests an anastylosis of a building, the user can simply put on a headset and view the streetscape and its suggested reconstruction.

VR simulations are a much cheaper and more flexible solution than on-site physical reconstruction. Of course, necessary checks and measures are important to signify what is certain and what is guesswork, and as such, Lithodomos adheres to section 2.4 of the ICOMOS Charter for the Interpretation and Presentation of Cultural Heritage Sites.

By using photogrammetry, texturing and mesh modelling, Lithodomos VR creates immersive experiences of the Greek and Roman worlds for viewing on Virtual Reality Head Mounted devices, for example: the Oculus Rift, Samsung Gear VR, Google Cardboard and many others. Unlike many VR content creators, our point of difference is that we specialse in VR content for the Greek and Roman worlds. Our reconstructions stem from years of research and firsthand knowledge, and they reflect the best academic practices to ensure that the end product is both as accurate as can be possible and informative for the viewer.






NMC Horizon Report > 2017 Library Edition — from


What is on the five-year horizon for academic and research libraries? Which trends and technology developments will drive transformation? What are the critical challenges and how can we strategize solutions? These questions regarding technology adoption and educational change steered the discussions of 77 experts to produce the NMC Horizon Report: 2017 Library Edition, in partnership with the University of Applied Sciences (HTW) Chur, Technische Informationsbibliothek (TIB), ETH Library, and the Association of College & Research Libraries (ACRL). Six key trends, six significant challenges, and six developments in technology profiled in this report are poised to impact library strategies, operations, and services with regards to learning, creative inquiry, research, and information management. The three sections of this report constitute a reference and technology planning guide for librarians, library leaders, library staff, policymakers, and technologists.






The 82 Hottest EdTech Tools of 2017 According to Education Experts — from by Giorgio Cassella


If you work in education, you’ll know there’s a HUGE array of applications, services, products and tools created to serve a multitude of functions in education.

Tools for teaching and learning, parent-teacher communication apps, lesson planning software, home-tutoring websites, revision blogs, SEN education information, professional development qualifications and more.

There are so many companies creating new products for education, though, that it can be difficult to keep up – especially with the massive volumes of planning and marking teachers have to do, never mind finding the time to actually teach!

So how do you know which ones are the best?

Well, as a team of people passionate about education and learning, we decided to do a bit of research to help you out.

We’ve asked some of the best and brightest in education for their opinions on the hottest EdTech of 2017. These guys are the real deal – experts in education, teaching and new tech from all over the world from England to India, to New York and San Francisco.

They’ve given us a list of 82 amazing, tried and tested tools…

From DSC:
The ones that I mentioned that Giorgio included in his excellent article were:

  • AdmitHub – Free, Expert College Admissions Advice
  • Labster – Empowering the Next Generation of Scientists to Change the World
  • Unimersiv – Virtual Reality Educational Experiences
  • Lifeliqe – Interactive 3D Models to Augment Classroom Learning






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


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.




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)




The woman who thinks time has rendered Western education obsolete — from with thanks to Maree Conway for her tweet on this

Excerpt (emphasis DSC):

For years, Finland has loitered in the upper echelons of global literacy and numeracy tables, leading politicians from other Western nations to see its education system as a model of inspiration. Why, then, is the Finnish government submitting it to a radical overhaul?

Dr. Marjo Kyllonen is the Education Manager for Helsinki. Having devised the blueprint for the future of Finland’s school system, she is playing a pivotal role in driving these changes through. She is doing so because she sees the structure and aims of current education systems in the West as increasingly irrelevant and obsolete, relics of an Industrial Age that we started to leave behind a long time ago. She argues that we need to rethink our entire relationship to education to equip future generations with the tools they need to face the challenges to come –challenges such as climate collapse, automated workforces, urbanisation and social division. The key to her blueprint is an emphasis on collaborative, holistic, “phenomenon” teaching – a routine that is less beholden to traditional subject-based learning and instead teaches pupils to work together to deal with problems they will face in their everyday lives, including those they encounter online and in the digital world.


  • If schools were invented today, what would they be like?
  • Instead of studying different subjects in isolation, learning should be anchored to real-life phenomena, things that kids see around them, so they see the connection between what they’re learning and real life. The traditional way of teaching isolated subjects with a teacher as the sole oracle of knowledge is widening the gap between the lives kids are living today and what they do at school.
  • So we have to think, what skills will people need in 60 years? Life is not split into subjects, so why is learning? What is more crucial for future society is cross-disciplinary thinking; all the experts say that the big problems of tomorrow won’t be solved if you only have one approach.


From DSC:
Whether one agrees with Marjo or not, her assertions are very thought provoking.  I really enjoyed reading this piece.



From DSC:
Can you imagine this as a virtual reality or a mixed reality-based app!?! Very cool.

This resource is incredible on multiple levels:

  • For their interface/interaction design
  • For their insights and ideas
  • For their creativity
  • For their graphics
  • …and more!











From DSC:
Given the exponential pace of technological change that many societies throughout the globe are now on, we need some tools to help us pulse-check what’s going on in the relevant landscapes that we are trying to scan.











Below, I would like to suggest 2 methods/tools to do this.  I have used both methods for years, and I have found them to be immensely helpful in pulse-checking the landscapes. Perhaps these tools will be helpful to you — or to your students or employees — as well.  I vote for these 2 tools to be a part of all of our learning ecosystems. (And besides, they also encourage micro-learning while helping us spot emerging trends.)


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