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)

 

 

 

The woman who thinks time has rendered Western education obsolete — from unlimited.world 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.

Other:

  • 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!

 

 

 

 

 

 

 

 

 

 

The number of VR companies grew 40% in 2016 — from venturebeat.com by Dean Takahashi

Excerpt:

The Venture Reality Fund reported that the landscape of companies it tracks in the virtual reality market grew more than 40 percent in 2016. The largest area of growth was in content companies that create apps for head-mounted VR displays, said Marco DeMiroz, cofounder of The Venture Reality Fund with Tipatat Chennavasin. The fund invests in VR and augmented reality startups. Gaming and entertainment nearly doubled in size, with major players as well as well-funded new companies in both the U.S. and Asia, he said.

 

Also see:

 

Also see:

 

 

Also see:

  • Millions pour into China’s virtual reality industry –from scmp.com by He Huifeng
    Excerpt:
    More than a dozen Chinese virtual-reality (VR) start-ups raised fresh funding of at least 10 million yuan each last month as venture capitalists continue to flock to this nascent market. The Nanfang Daily also reported on Monday that 60 listed domestic companies have entered the VR industry since July last year through investments in content developers and device makers. The VR consumer market will explode within a year in China, according to a white paper released by the Ministry of Industry and Information Technology (MIIT) last week. The market size of China’s VR industry will triple this year to 5.66 billion yuan from 1.54 billion yuan last year, according to the white paper. It also estimates the industry revenue is on track to cross 55 billion yuan by 2020.

 

 

From DSC:
Vinay Narayan, from HTC Vive, described 2016 as “ground zero” for VR (i.e., it’s just getting started).

So while there certainly is hype going on (and there often is when we’re talking about potentially-promising emerging technologies), so are the investment dollars. It may take a few years to get there, but I don’t see these new forms of Human Computer Interaction (HCI) going away (here’s another reason why).

 

 

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!

 

 

What educators can learn about effective teaching from a Harvard prof — from ecampusnews.com by Alan November

Excerpt:

Harvard professor David Malan has managed to pull off a neat trick: His Computer Science 50 course is the most popular course at both Harvard and Yale. By examining his success, we can learn some important lessons about effective teaching.

CS50 assumes no prior knowledge or skill in computer programming, yet it’s extremely demanding. Despite its rigor, CS50 regularly attracts thousands of students each year. While some aspire to become software engineers, others enroll just to experience the course.

Why is Professor Malan’s course so popular, even with students who don’t plan a career in computer science—and even though it requires a lot of work? Here are three keys to Malan’s effective teaching that I think all schools everywhere should apply, from K-12 schools to colleges and universities.

  • Strengthen the social side of learning.
  • Teach students to self-assess.
  • Provide a public audience to inspire students to invent.
 

HarvardX rolls out new adaptive learning feature in online course — from edscoop.com by Corinne Lestch
Students in MOOC adaptive learning experiment scored nearly 20 percent better than students using more traditional learning approaches.

Excerpt:

Online courses at Harvard University are adapting on the fly to students’ needs.

Officials at the Cambridge, Massachusetts, institution announced a new adaptive learning technology that was recently rolled out in a HarvardX online course. The feature offers tailored course material that directly correlates with student performance while the student is taking the class, as well as tailored assessment algorithms.

HarvardX is an independent university initiative that was launched in parallel with edX, the online learning platform that was created by Harvard and Massachusetts Institute of Technology. Both HarvardX and edX run massive open online courses. The new feature has never before been used in a HarvardX course, and has only been deployed in a small number of edX courses, according to officials.

 

 

From DSC:
Given the growth of AI, this is certainly radar worthy — something that’s definitely worth pulse-checking to see where opportunities exist to leverage these types of technologies.  What we now know of as adaptive learning will likely take an enormous step forward in the next decade.

IBM’s assertion rings in my mind:

 

 

I’m cautiously hopeful that these types of technologies can extend beyond K-12 and help us deal with the current need to be lifelong learners, and the need to constantly reinvent ourselves — while providing us with more choice, more control over our learning. I’m hopeful that learners will be able to pursue their passions, and enlist the help of other learners and/or the (human) subject matter experts as needed.

I don’t see these types of technologies replacing any teachers, professors, or trainers. That said, these types of technologies should be able to help do some of the heavy teaching and learning lifting in order to help someone learn about a new topic.

Again, this is one piece of the Learning from the Living [Class] Room that we see developing.

 

 

 

 
 

“In a decade, Hymnary.org has become the most complete database of North American hymnody on the planet, a rich resource now visited by more than 5 million people each year!”

 

 

Hymnary.org was founded by Calvin College Computer Science Professor Harry Plantinga and Calvin Institute of Christian Worship Music Associate Greg Scheer.

 

 
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