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

Excerpt:

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.

 

 

 

From DSC:
First of all, let me say again that I’m not suggesting that we replace professors with artificial intelligence, algorithms, and such.

However, given a variety of trends, we need to greatly lower the price of obtaining a degree and these types of technologies will help us do just that — while at the same time significantly increasing the productivity of each professor and/or team of specialists offering an online-based course (something institutions of higher education are currently attempting to do…big time). Not only will these types of technologies find their place in the higher education landscape, I predict that they will usher in a “New Amazon.com of Higher Education” — a new organization that will cause major disruption for traditional institutions of higher education. AI-powered MOOCs will find their place on the higher ed landscape; just how big they become remains to be seen, but this area of the landscape should be on our radars from here on out.

This type of development again points the need for team-based
approaches; s
uch approaches will likely dominate the future.

 

 


 

California State University East Bay partners with Cognii to offer artificial intelligence powered online learning — from prnewswire.com
Cognii’s Virtual Learning Assistant technology will provide intelligent tutoring and assessments to students in a chatbot-style conversation

Excerpt:

HAYWARD, Calif., April 14, 2017 /PRNewswire/ — Cal State East Bay, a top-tier public university, and Cognii Inc., a leading provider of artificial intelligence-based educational technologies, today announced a partnership. Cognii will work with Cal State East Bay to develop a new learning and assessment experience, powered by Cognii’s Virtual Learning Assistant technology.

Winner of the 2016 EdTech Innovation of the Year Award from Mass Technology Leadership Council for its unique use of conversational AI and Natural Language Processing technologies in education, Cognii VLA provides automatic grading to students’ open-response answers along with qualitative feedback that guides them towards conceptual mastery. Compared to the multiple choice tests, open-response questions are considered pedagogically superior for measuring students’ critical thinking and problem solving skills, essential for 21st century jobs.

Students at Cal State East Bay will use the Cognii-powered interactive tutorials starting in summer as part of the online transfer orientation course. The interactive questions and tutorials will be developed collaboratively by Cognii team and the eLearning specialists from the university’s office of the Online Campus. Students will interact with the questions in a chatbot-style natural language conversation during the formative assessment stage. As students practice the tutorials, Cognii will generate rich learning analytics and proficiency measurements for the course leaders.

 

 

 

 

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.

 



 

 

 

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

Excerpt:

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

 


 

 

 

 

Tech giants grapple with the ethical concerns raised by the AI boom — from technologyreview.com by Tom Simonite
As machines take over more decisions from humans, new questions about fairness, ethics, and morality arise.

Excerpt:

With great power comes great responsibility—and artificial-intelligence technology is getting much more powerful. Companies in the vanguard of developing and deploying machine learning and AI are now starting to talk openly about ethical challenges raised by their increasingly smart creations.

“We’re here at an inflection point for AI,” said Eric Horvitz, managing director of Microsoft Research, at MIT Technology Review’s EmTech conference this week. “We have an ethical imperative to harness AI to protect and preserve over time.”

Horvitz spoke alongside researchers from IBM and Google pondering similar issues. One shared concern was that recent advances are leading companies to put software in positions with very direct control over humans—for example in health care.

 

 

21 bot experts make their predictions for 2017 — from venturebeat.com by Adelyn Zhou

Excerpt:

2016 was a huge year for bots, with major platforms like Facebook launching bots for Messenger, and Amazon and Google heavily pushing their digital assistants. Looking forward to 2017, we asked 21 bot experts, entrepreneurs, and executives to share their predictions for how bots will continue to evolve in the coming year.

From Jordi Torras, founder and CEO, Inbenta:
“Chatbots will get increasingly smarter, thanks to the adoption of sophisticated AI algorithms and machine learning. But also they will specialize more in specific tasks, like online purchases, customer support, or online advice. First attempts of chatbot interoperability will start to appear, with generalist chatbots, like Siri or Alexa, connecting to specialized enterprise chatbots to accomplish specific tasks. Functions traditionally performed by search engines will be increasingly performed by chatbots.”

 

 

 

 

 


From DSC:
For those of us working within higher education, chatbots need to be on our radars. Here are 2 slides from my NGLS 2017 presentation.

 

 

 

 

59 impressive things artificial intelligence can do today — from businessinsider.com by Ed Newton-Rex

Excerpt:

But what can AI do today? How close are we to that all-powerful machine intelligence? I wanted to know, but couldn’t find a list of AI’s achievements to date. So I decided to write one. What follows is an attempt at that list. It’s not comprehensive, but it contains links to some of the most impressive feats of machine intelligence around. Here’s what AI can do…

 

 

 


Recorded Saturday, February 25th, 2017 and published on Mar 16, 2017


Description:

Will progress in Artificial Intelligence provide humanity with a boost of unprecedented strength to realize a better future, or could it present a threat to the very basis of human civilization? The future of artificial intelligence is up for debate, and the Origins Project is bringing together a distinguished panel of experts, intellectuals and public figures to discuss who’s in control. Eric Horvitz, Jaan Tallinn, Kathleen Fisher and Subbarao Kambhampati join Origins Project director Lawrence Krauss.

 

 

 

 

Description:
Elon Musk, Stuart Russell, Ray Kurzweil, Demis Hassabis, Sam Harris, Nick Bostrom, David Chalmers, Bart Selman, and Jaan Tallinn discuss with Max Tegmark (moderator) what likely outcomes might be if we succeed in building human-level AGI, and also what we would like to happen. The Beneficial AI 2017 Conference: In our sequel to the 2015 Puerto Rico AI conference, we brought together an amazing group of AI researchers from academia and industry, and thought leaders in economics, law, ethics, and philosophy for five days dedicated to beneficial AI. We hosted a two-day workshop for our grant recipients and followed that with a 2.5-day conference, in which people from various AI-related fields hashed out opportunities and challenges related to the future of AI and steps we can take to ensure that the technology is beneficial.

 

 


(Below emphasis via DSC)

IBM and Ricoh have partnered for a cognitive-enabled interactive whiteboard which uses IBM’s Watson intelligence and voice technologies to support voice commands, taking notes and actions and even translating into other languages.

 

The Intelligent Workplace Solution leverages IBM Watson and Ricoh’s interactive whiteboards to allow to access features via using voice. It makes sure that Watson doesn’t just listen, but is an active meeting participant, using real-time analytics to help guide discussions.

Features of the new cognitive-enabled whiteboard solution include:

  • Global voice control of meetings: Once a meeting begins, any employee, whether in-person or located remotely in another country, can easily control what’s on the screen, including advancing slides, all through simple voice commands using Watson’s Natural Language API.
  • Translation of the meeting into another language: The Intelligent Workplace Solution can translate speakers’ words into several other languages and display them on screen or in transcript.
  • Easy-to-join meetings: With the swipe of a badge the Intelligent Workplace Solution can log attendance and track key agenda items to ensure all key topics are discussed.
  • Ability to capture side discussions: During a meeting, team members can also hold side conversations that are displayed on the same whiteboard.

 


From DSC:

Holy smokes!

If you combine the technologies that Ricoh and IBM are using with their new cognitive-enabled interactive whiteboard with what Bluescape is doing — by providing 160 acres of digital workspace that’s used to foster collaboration (and to do so whether you are working remoting or working with others in the same physical space) — and you have one incredibly powerful platform! 

#NLP  |  #AI  |  #CognitiveComputing  | #SmartClassrooms
#LearningSpaces  |#Collaboration |  #Meetings 

 

 


 

 

 


 

AI Market to Grow 47.5% Over Next Four Years — from campustechnology.com by Richard Chang

Excerpt:

The artificial intelligence (AI) market in the United States education sector is expected to grow at a compound annual growth rate of 47.5 percent during the period 2017-2021, according to a new report by market research firm Research and Markets.

 

 

Amazon deepens university ties in artificial intelligence race — from by Jeffrey Dastin

Excerpt:

Amazon.com Inc has launched a new program to help students build capabilities into its voice-controlled assistant Alexa, the company told Reuters, the latest move by a technology firm to nurture ideas and talent in artificial intelligence research.

Amazon, Alphabet Inc’s Google and others are locked in a race to develop and monetize artificial intelligence. Unlike some rivals, Amazon has made it easy for third-party developers to create skills for Alexa so it can get better faster – a tactic it now is extending to the classroom.

 

 

The WebMD skill for Amazon’s Alexa can answer all your medical questions — from digitaltrends.com by Kyle Wiggers
WebMD is bringing its wealth of medical knowledge to a new form factor: Amazon’s Alexa voice assistant.

Excerpt:

Alexa, Amazon’s brilliant voice-activated smart assistant, is a capable little companion. It can order a pizza, summon a car, dictate a text message, and flick on your downstairs living room’s smart bulb. But what it couldn’t do until today was tell you whether that throbbing lump on your forearm was something that required medical attention. Fortunately, that changed on Tuesday with the introduction of a WebMD skill that puts the service’s medical knowledge at your fingertips.

 

 


Addendum:

  • How artificial intelligence is taking Asia by storm — from techwireasia.com by Samantha Cheh
    Excerpt:
    Lately it seems as if everyone is jumping onto the artificial intelligence bandwagon. Everyone, from ride-sharing service Uber to Amazon’s logistics branch, is banking on AI being the next frontier in technological innovation, and are investing heavily in the industry.

    That’s likely truest in Asia, where the manufacturing engine which drove China’s growth is now turning its focus to plumbing the AI mine for gold.

    Despite Asia’s relatively low overall investment in AI, the industry is set to grow. Fifty percent of respondents in KPMG’s AI report said their companies had plans to invest in AI or robotic technology.

    Investment in AI is set to drive venture capital investment in China in 2017. Tak Lo, of Hong Kong’s Zeroth, notes there are more mentions of AI in Chinese research papers than there are in the US.

    China, Korea and Japan collectively account for nearly half the planet’s shipments of articulated robots in the world.

     

 

Artificial Intelligence – Research Areas

 

 

 

 

 

 

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)

 

 

 

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:
Chatbots were another one of the topics I mentioned at the Next Generation Learning Spaces Conference last week. For those of us working within higher education, chatbots need to be on our radars!

 

 

An article from today on this:

  • Using AI Chatbots to Freeze ‘Summer Melt’ in Higher Ed — from campustechnology.com by Sri Ravipati
    Excerpt:
    Students who accept offers of admission into a college or university don’t always show up for fall enrollment — a phenomenon known as “summer melt.” It’s a problem that Georgia State University (GSU) is all too familiar with: The institution’s summer melt rates have increased from 12 percent to nearly 19 percent in recent years. With traditional methods of reaching students (i.e. snail mail, e-mail and phone calls) producing feeble results, GSU decided to try another approach: smart text messaging.

    According to a recent case study, GSU was well aware of the advantages of communicating with students via text messages, but was concerned about the additional workload that text messaging students would place on existing staff. So, the university partnered with AdmitHub, a Boston-based ed tech startup, to test out text-based intervention. AdmitHub works with higher ed institutions to create a virtual “campus coach” that embodies the collective knowledge and unique spirit of a school’s community. It integrates conversational artificial intelligence (AI) with human expertise to guide students to and through college.

 

One of the slides from my presentation on this:

 

 

 
© 2016 Learning Ecosystems