WE ARE NOT READY FOR THIS! Per Forrester Research: In US, a net loss of 7% of jobs to automation — *in 2018*!

Forrester predicts that AI-enabled automation will eliminate 9% of US jobs in 2018 — from forbes.com by Gil Press

Excerpt (emphasis DSC):

A new Forrester Research report, Predictions 2018: Automation Alters The Global Workforce, outlines 10 predictions about the impact of AI and automation on jobs, work processes and tasks, business success and failure, and software development, cybersecurity, and regulatory compliance.

We will see a surge in white-collar automation, half a million new digital workers (bots) in the US, and a shift from manual to automated IT and data management. “Companies that master automation will dominate their industries,” Forrester says. Here’s my summary of what Forrester predicts will be the impact of automation in 2018:

Automation will eliminate 9% of US jobs but will create 2% more.
In 2018, 9% of US jobs will be lost to automation, partly offset by a 2% growth in jobs supporting the “automation economy.” Specifically impacted will be back-office and administrative, sales, and call center employees. A wide range of technologies, from robotic process automation and AI to customer self-service and physical robots will impact hiring and staffing strategies as well as create a need for new skills.

 

Your next entry-level compliance staffer will be a robot.

 

From DSC:

Are we ready for a net loss of 7% of jobs in our workforce due to automation — *next year*? Last I checked, it was November 2017, and 2018 will be here before we know it.

 

***Are we ready for this?! ***

 

AS OF TODAY, can we reinvent ourselves fast enough given our current educational systems, offerings, infrastructures, and methods of learning?

 

My answer: No, we can’t. But we need to be able to — and very soon!

 

 

There are all kinds of major issues and ramifications when people lose their jobs — especially this many people and jobs! The ripple effects will be enormous and very negative unless we introduce new ways for how people can learn new things — and quickly!

That’s why I’m big on trying to establish a next generation learning platform, such as the one that I’ve been tracking and proposing out at Learning from the Living [Class] Room. It’s meant to provide societies around the globe with a powerful, next generation learning platform — one that can help people reinvent themselves quickly, cost-effectively, conveniently, & consistently! It involves providing, relevant, up-to-date streams of content that people can subscribe to — and drop at any time. It involves working in conjunction with subject matter experts who work with teams of specialists, backed up by suites of powerful technologies. It involves learning with others, at any time, from any place, at any pace. It involves more choice, more control. It involves blockchain-based technologies to feed cloud-based learner profiles and more.

But likely, bringing such a vision to fruition will require a significant amount of collaboration. In my mind, some of the organizations that should be at the table here include:

  • Some of the largest players in the tech world, such as Amazon, Google, Apple, IBM, Microsoft, and/or Facebook
  • Some of the vendors that already operate within the higher ed space — such as Salesforce.com, Ellucian, and/or Blackboard
  • Some of the most innovative institutions of higher education — including their faculty members, instructional technologists, instructional designers, members of administration, librarians, A/V specialists, and more
  • The U.S. Federal Government — for additional funding and the development of policies to make this vision a reality

 

 

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

 

 

Artificial Intelligence in Education: Where It’s At, Where It’s Headed — from gettingsmart.com by Cameron Paterson

Excerpt:

Artificial intelligence is predicted to fundamentally alter the nature of society by 2040. Investment in AI start-ups was estimated at $6-$9 billion in 2016, up from US$415 million four years earlier. While futurist Ray Kurzweil argues that AI will help us to address the grand challenges facing humanity, Elon Musk warns us that artificial intelligence will be our “biggest existential threat.” Others argue that artificial intelligence is the future of growth. Everything depends on how we manage the transition to this AI-era.

In 2016 the Obama administration released a national strategic plan for artificial intelligence and, while we do not all suddenly now need a plan for artificial intelligence, we do need to stay up to date on how AI is being implemented. Much of AI’s potential is yet to be realized, but AI is already running our lives, from Siri to Netflix recommendations to automated air traffic control. We all need to become more aware of how we are algorithmically shaped by our tools.

This Australian discussion paper on the implications of AI, automation and 21st-century skills, shows how AI will not just affect blue-collar truck drivers and cleaners, it will also affect white-collar lawyers and doctors. Automated pharmacy systems with robots dispensing medication exist, Domino’s pizza delivery by drone has already occurred, and a fully automated farm is opening in Japan.

 

Education reformers need to plan for our AI-driven future and its implications for education, both in schools and beyond. The never-ending debate about the sorts of skills needed in the future and the role of schools in teaching and assessing them is becoming a whole lot more urgent and intense.

 

 

 

AI Experts Want to End ‘Black Box’ Algorithms in Government — from wired.com by Tom Simonite

Excerpt:

The right to due process was inscribed into the US constitution with a pen. A new report from leading researchers in artificial intelligence cautions it is now being undermined by computer code.

Public agencies responsible for areas such as criminal justice, health, and welfare increasingly use scoring systems and software to steer or make decisions on life-changing events like granting bail, sentencing, enforcement, and prioritizing services. The report from AI Now, a research institute at NYU that studies the social implications of artificial intelligence, says too many of those systems are opaque to the citizens they hold power over.

The AI Now report calls for agencies to refrain from what it calls “black box” systems opaque to outside scrutiny. Kate Crawford, a researcher at Microsoft and cofounder of AI Now, says citizens should be able to know how systems making decisions about them operate and have been tested or validated. Such systems are expected to get more complex as technologies such as machine learning used by tech companies become more widely available.

“We should have equivalent due-process protections for algorithmic decisions as for human decisions,” Crawford says. She says it can be possible to disclose information about systems and their performance without disclosing their code, which is sometimes protected intellectual property.

 

 

UAE appoints first-ever Minister for Artificial Intelligence — from tribune.com.pk

 

“We announce the appointment of a minister for artificial intelligence. The next global wave is artificial intelligence and we want the UAE to be more prepared for it.”

 

 

Tech Giants Are Paying Huge Salaries for Scarce A.I. Talent — from nytimes.com by Cade Metz
Nearly all big tech companies have an artificial intelligence project, and they are willing to pay experts millions of dollars to help get it done.

Excerpt:

Tech’s biggest companies are placing huge bets on artificial intelligence, banking on things ranging from face-scanning smartphones and conversational coffee-table gadgets to computerized health care and autonomous vehicles. As they chase this future, they are doling out salaries that are startling even in an industry that has never been shy about lavishing a fortune on its top talent.

Typical A.I. specialists, including both Ph.D.s fresh out of school and people with less education and just a few years of experience, can be paid from $300,000 to $500,000 a year or more in salary and company stock, according to nine people who work for major tech companies or have entertained job offers from them. All of them requested anonymity because they did not want to damage their professional prospects.

With so few A.I. specialists available, big tech companies are also hiring the best and brightest of academia. In the process, they are limiting the number of professors who can teach the technology.

 

 

 

Where will AI play? By Mike Quindazzi.

 

 

 

 

100 Data and Analytics Predictions Through 2021 — from Gartner

From DSC:
I just wanted to include some excerpts (see below) from Gartner’s 100 Data and Analytics Predictions Through 2021 report. I do so to illustrate how technology’s impact continues to expand/grow in influence throughout many societies around the globe, as well as to say that if you want a sure thing job in the next 1-15 years, I would go into studying data science and/or artificial intelligence!

 



Excerpts:

As evidenced by its pervasiveness within our vast array of recently published Predicts 2017 research, it is clear that data and analytics are increasingly critical elements across most industries, business functions and IT disciplines. Most significantly, data and analytics are key to a successful digital business. This collection of more than 100 data-and-analytics-related Strategic Planning Assumptions (SPAs) or predictions through 2021, heralds several transformations and challenges ahead that CIOs and data and analytics leaders should embrace and include in their planning for successful strategies. Common themes across the discipline in general, and within particular business functions and industries, include:

  • Artificial intelligence (AI) is emerging as a core business and analytic competency. Beyond yesteryear’s hard-coded algorithms and manual data science activities, machine learning (ML) promises to transform business processes, reconfigure workforces, optimize infrastructure behavior and blend industries through rapidly improved decision making and process optimization.
  • Natural language is beginning to play a dual role in many organizations and applications as a source of input for analytic and other applications, and a variety of output, in addition to traditional analytic visualizations.
  • Information itself is being recognized as a corporate asset (albeit not yet a balance sheet asset), prompting organizations to become more disciplined about monetizing, managing and measuring it as they do with other assets. This includes “spending” it like cash, selling/licensing it to others, participating in emerging data marketplaces, applying asset management principles to improve its quality and availability, and quantifying its value and risks in a variety of ways.
  • Smart devices that both produce and consume Internet of Things (IoT) data will also move intelligent computing to the edge of business functions, enabling devices in almost every industry to operate and interact with humans and each other without a centralized command and control. The resulting opportunities for innovation are unbounded.
  • Trust becomes the watchword for businesses, devices and information, leading to the creation of digital ethics frameworks, accreditation and assessments. Most attempts at leveraging blockchain as a trust mechanism fail until technical limitations, particularly performance, are solved.

Education
Significant changes to the global education landscape have taken shape in 2016, and spotlight new and interesting trends for 2017 and beyond. “Predicts 2017: Education Gets Personal” is focused on several SPAs, each uniquely contributing to the foundation needed to create the digitalized education environments of the future. Organizations and institutions will require new strategies to leverage existing and new technologies to maximize benefits to the organization in fresh and
innovative ways.

  • By 2021, more than 30% of institutions will be forced to execute on a personalization strategy to maintain student enrollment.
  • By 2021, the top 100 higher education institutions will have to adopt AI technologies to stay competitive in research.

Artificial Intelligence
Business and IT leaders are stepping up to a broad range of opportunities enabled by AI, including autonomous vehicles, smart vision systems, virtual customer assistants, smart (personal) agents and natural-language processing. Gartner believes that this new general-purpose technology is just beginning a 75-year technology cycle that will have far-reaching implications for every industry. In “Predicts 2017: Artificial Intelligence,” we reflect on the near-term opportunities, and the potential burdens and risks that organizations face in exploiting AI. AI is changing the way in which organizations innovate and communicate their processes, products and services.

Practical strategies for employing AI and choosing the right vendors are available to data and analytics leaders right now.

  • By 2019, more than 10% of IT hires in customer service will mostly write scripts for bot interactions.
  • Through 2020, organizations using cognitive ergonomics and system design in new AI projects will achieve long-term success four times more often than others.
  • By 2020, 20% of companies will dedicate workers to monitor and guide neural networks.
  • By 2019, startups will overtake Amazon, Google, IBM and Microsoft in driving the AI economy with disruptive business solutions.
  • By 2019, AI platform services will cannibalize revenues for 30% of market-leading companies. “Predicts 2017: Drones”
  • By 2020, the top seven commercial drone manufacturers will all offer analytical software packages.
    “Predicts 2017: The Reinvention of Buying Behavior in Vertical-Industry Markets”
  • By 2021, 30% of net new revenue growth from industry-specific solutions will include AI technology.

Advanced Analytics and Data Science
Advanced analytics and data science are fast becoming mainstream solutions and competencies in most organizations, even supplanting traditional BI and analytics resources and budgets. They allow more types of knowledge and insights to be extracted from data. To become and remain competitive, enterprises must seek to adopt advanced analytics, and adapt their business models, establish specialist data science teams and rethink their overall strategies to keep pace with the competition. “Predicts 2017: Analytics Strategy and Technology” offers advice on overall strategy, approach and operational transformation to algorithmic business that leadership needs to build to reap the benefits.

  • By 2018, deep learning (deep neural networks [DNNs]) will be a standard component in 80% of data scientists’ tool boxes.
  • By 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.
  • By 2019, natural-language generation will be a standard feature of 90% of modern BI and analytics platforms.
  • By 2019, 50% of analytics queries will be generated using search, natural-language query or voice, or will be autogenerated.
  • By 2019, citizen data scientists will surpass data scientists in the amount of advanced analysis
    produced.

 

 

By 2020, 95% of video/image content will never be viewed by humans; instead, it will be vetted by machines that provide some degree of automated analysis.

 

 

Through 2020, lack of data science professionals will inhibit 75% of organizations from achieving the full potential of IoT.

 

 

 

 

Ginni Rometty on the End of Programming — from bloomberg.com by Megan Murphy
The IBM chief dares to imagine what Watson will be when it grows up, and reaffirms her pledge to hire 25,000 people over the next four years.

Excerpt (emphasis DSC):

Do you feel we’re going to get to a point where AI will displace more jobs than it creates and we’re not doing enough to push forward with the jobs of the future?

I do believe that when it comes to complete job replacement, it will be a very small percentage. When it comes to changing a job and what you do, it will be 100 percent. “Whoa, different skills. Everybody is going to have to have a different skill because it’s going to be a threat in all our jobs.” Let me just park that thought. I want to come back to something I think that’s far more important and is related. The issue of skills is front and center in this country and many countries in the world right now without AI. We already have a world that’s bifurcating between haves and have-nots, and a lot of that is based on education and skills. This country has 5 million to 6 million jobs open. That’s about skill. This is not being caused by AI. We’ve got to revamp education for this era of man and machine. And that means you cannot insist that every person needs to be a university or a Ph.D. graduate to be productive in society. You cannot. It’s not true by the way. We’ve proven that.

You started a six-year high school program. This is a program where they take people through four years of high school, two years of a college equivalent, and then hopefully give them preference in getting into the workforce, again to work with IBM.

In the U.S., in 2015, half of our young people didn’t have an associate’s degree or a college degree. That’s the problem today: the number of people that need to be retrained. I’m far more optimistic that public-private partnerships can solve this dilemma. There will be a hundred pathways to technology becoming viral, driven by governors and states. I always remember when President Obama came to the first one, he goes, “Where are all the computers?” We’re like, “That’s not what we teach these kids.” We’re teaching them a skill about math and problem-solving that’s going to transcend any technology they deal with. The first part is a very simple formula: a curriculum of math, science. The second, give the kids a mentor and then you give them a chance at a job. We will be up to 50,000 kids, and 300 other companies have volunteered. I have a whole bunch of these kids over in Silicon Alley where we have our Watson headquarters.

 

 

I do believe that when it comes to complete job replacement, it will be a very small percentage. When it comes to changing a job and what you do, it will be 100 percent.

 

 

 

The new Autonomous SmartDesk 3 has a built-in touchscreen and AI software — from imore.com by Tory Foulk 

Excerpt:

Can your desk encourage you to stand, remind you to drink water and order you a pizza? No? Well SmartDesk 3 can.

Autonomous announced the launch of the newest iteration of its SmartDesk in a press release today, and is claiming it’s “the world’s most powerful AI-powered standing desk.”

The embedded tablet has a 7″ display and is powered by Autonomous’ own OS platform, and has both Bluetooth and WiFi capabilities so it can interact with the apps on your phone. It features many of its own shortcuts, too – you can make coffee, order food, check the weather, play Spotify playlists, and even request a ride from Uber. Because the tablet syncs with Google Calendar, it will remind you of any meetings you might have throughout the day. And in addition to all of that, SmartDesk 3 monitors how long you sit or stand and reminds you to either stretch your legs or take a break to relax when it feels you need it. After using the AI for a week or so, it will learn your habits – say, when you usually start getting hungry – and begin to anticipate your needs.

 

Autonomous' SmartDesk 3 in white

 

 

 

 

 

Unity Technologies unveils AI toolkit for training machine learning ‘agents’ — from therobotreport.com by Alex Beall

Excerpt:

Unity Technologies released the open beta version of its Unity Machine Learning Agents, an artificial intelligence toolkit developers and researchers can use to virtually train agents —whether video game characters, autonomous vehicles or robots.

“Machine learning is a disruptive technology that is important to all types of developers and researchers to make their games or systems smarter, but complexities and technical barriers make it out of reach for most,” vice president of AI and machine learning Danny Lange said in a press release. “This is an exciting new chapter in AI’s history as we are making an end-to-end machine learning environment widely accessible, and providing the critical tools needed to make more intelligent, beautiful games and applications. Complete with Unity’s physics engine and a 3D photorealistic rendering environment, our AI toolkit also offers a game-changing AI research platform to a rapidly growing community of AI enthusiasts exploring the frontiers of Deep Learning.”

 

 

 

 

How Chatbot Tech Takes Customer Service to the Next Level — from nojitter.com by Yaniv Reznik
A chatbot’s combination of personalized service and quick, efficient answers perfectly fits the needs of today’s digital consumers.

Excerpts:

Rather, today’s connected consumers want a seamless online experience that immediately allows them to self-serve when they have a quick question or choose a hybrid approach when they need that personal touch from a live representative.

Chatbots empower consumers to take charge of their own brand experience and efficiently get the answers they need. Consumers demand accuracy and convenience, and chatbots provide the perfect balance of speed, personalization, and human touch necessary for improved customer experiences.

The key to implementing chatbots that go beyond scripted responses is Natural Language Processing (NLP). Chatbots equipped with this advanced technology can understand situational context and can therefore get to the root of customer questions without putting customers on hold or redirecting them.

 

 

 

 



 

Addendum on 9/25/17:

One year later, Microsoft AI and Research grows to 8k people in massive bet on artificial intelligence — from geekwire.com by Todd Bishop

Excerpt:

One way to measure Microsoft’s AI bet: In its first year of operation, the AI and Research group has grown by 60 percent — from 5,000 people originally to nearly 8,000 people today — through hiring and acquisitions, and by bringing aboard additional teams from other parts of the company.

The creation of Microsoft AI and Research also underscores the intense competition in artificial intelligence. Microsoft is gearing up to compete against the likes of Google, Amazon, Salesforce, Apple, and countless AI startups and research groups, all of them looking to lead the tech industry in this new era of artificial intelligence.

 



 

 

 

 

 

Teachers can now use IBM’s Watson to search for free lesson plans — from edsurge.com by Stephen Noonoo

Excerpt:

IBM’s famous Watson computing system—which defeated Jeopardy champ Ken Jennings in 2011—is coming to education, if not quite the classroom. As part of a new IBM philanthropic initiative, the supercomputer is helping to power a searchable database of open educational math resources designed for teachers in grades K-5.

Today marks the first time the new tool, called Teacher Advisor With Watson 1.0, is open to the public after a lengthy beta testing period that sought input from state education commissioners, teachers unions, school board associations and more than 1,000 teachers.

“We wanted to build and design something for teachers by teachers, with the best information and the best technology available,” says Stan Litow, the President Emeritus of the IBM Foundation and a former deputy chancellor for New York City Department of Education.

The IBM Foundation has been flirting with ideas to apply Watson technology in education for a while, without knowing exactly what it wanted to do with it. The tech giant began last year by pulling in more than 100 top-level education leaders for a daylong event demoing the tech. From that focus group they narrowed the list of potential applications to professional development tools and, eventually, settled on a searchable database exclusively for elementary school math.

 

Populating the search engine is a collection of more than 1,000 OERs—from sources such as Achieve, UnboundED and statewide orgs like EngageNY—hand-selected by math experts assisting the program.

 

Also see:

 


 

 

A survey of 3,000 executives reveals how businesses succeed with AI — from hbr.org by Jacques Bughin, Brian McCarthy, Michael Chui

Excerpt:

The buzz over artificial intelligence (AI) has grown loud enough to penetrate the C-suites of organizations around the world, and for good reason. Investment in AI is growing and is increasingly coming from organizations outside the tech space. And AI success stories are becoming more numerous and diverse, from Amazon reaping operational efficiencies using its AI-powered Kiva warehouse robots, to GE keeping its industrial equipment running by leveraging AI for predictive maintenance.

While it’s clear that CEOs need to consider AI’s business implications, the technology’s nascence in business settings makes it less clear how to profitably employ it. Through a study of AI that included a survey of 3,073 executives and 160 case studies across 14 sectors and 10 countries, and through a separate digital research program, we have identified 10 key insights CEOs need to know to embark on a successful AI journey.

 

 

Make no mistake: The next digital frontier is here, and it’s AI. While some firms are still reeling from previous digital disruptions, a new one is taking shape. But it’s early days. There’s still time to make AI a competitive advantage.

 

 

 

IBM and MIT to Pursue Joint Research in Artificial Intelligence, Establish New MIT-IBM Watson AI Lab — from  by
IBM plans to make a 10-Year, $240 Million Investment in new lab with MIT to advance AI hardware and software and algorithms

Excerpt:

CAMBRIDGE, Mass., Sept. 7, 2017 /PRNewswire/ — IBM and MIT today announced that IBM plans to make a 10-year, $240 million investment to create the MIT–IBM Watson AI Lab in partnership with MIT. The lab will carry out fundamental artificial intelligence (AI) research and seek to propel scientific breakthroughs that unlock the potential of AI. The collaboration aims to advance AI hardware, software and algorithms related to deep learning and other areas, increase AI’s impact on industries, such as health care and cybersecurity, and explore the economic and ethical implications of AI on society. IBM’s $240 million investment in the lab will support research by IBM and MIT scientists.

 

The new lab will be one of the largest long-term university-industry AI collaborations to date, mobilizing the talent of more than 100 AI scientists, professors, and students to pursue joint research…

 

 

 

Codify Academy Taps IBM Cloud with Watson to Design Cognitive Chatbot — from finance.yahoo.com
Chatbot “Bobbot” has driven thousands of potential leads, 10 percent increase in converting visitors to students

Excerpt:

ARMONK, N.Y., Aug. 4, 2017 /PRNewswire/ — IBM (NYSE: IBM) today announced that Codify Academy, a San Francisco-based developer education startup, tapped into IBM Cloud’s cognitive services to create an interactive cognitive chatbot, Bobbot, that is improving student experiences and increasing enrollment.

Using the IBM Watson Conversation Service, Bobbot fields questions from prospective and current students in natural language via the company’s website. Since implementing the chatbot, Codify Academy has engaged thousands of potential leads through live conversation between the bot and site visitors, leading to a 10 percent increase in converting these visitors into students.

 

 

Bobbot can answer more than 200 common questions about enrollment, course and program details, tuition, and prerequisites, in turn enabling Codify Academy staff to focus on deeper, more meaningful exchanges.

 

 

 


Also see:

Chatbots — The Beginners Guide
 — from chatbotsmagazine.com

Excerpt:

If you search for chatbots on Google, you’ll probably come across hundreds of pages starting from what is a chatbot to how to build one. This is because we’re in 2017, the year of the chatbots revolution.

I’ve been introduced to many people who are new to this space, and who are very interested and motivated in entering it, rather they’re software developers, entrepreneurs, or just tech hobbyists. Entering this space for the first time, has become overwhelming in just a few months, particularly after Facebook announced the release of the messenger API at F8 developer conference. Due to this matter, I’ve decided to simplify the basic steps of entering this fascinating world.

 


 

 

 

 

 

The Business of Artificial Intelligence — from hbr.org by Erik Brynjolfsson & Andrew McAfee

Excerpts (emphasis DSC):

The most important general-purpose technology of our era is artificial intelligence, particularly machine learning (ML) — that is, the machine’s ability to keep improving its performance without humans having to explain exactly how to accomplish all the tasks it’s given. Within just the past few years machine learning has become far more effective and widely available. We can now build systems that learn how to perform tasks on their own.

Why is this such a big deal? Two reasons. First, we humans know more than we can tell: We can’t explain exactly how we’re able to do a lot of things — from recognizing a face to making a smart move in the ancient Asian strategy game of Go. Prior to ML, this inability to articulate our own knowledge meant that we couldn’t automate many tasks. Now we can.

Second, ML systems are often excellent learners. They can achieve superhuman performance in a wide range of activities, including detecting fraud and diagnosing disease. Excellent digital learners are being deployed across the economy, and their impact will be profound.

In the sphere of business, AI is poised have a transformational impact, on the scale of earlier general-purpose technologies. Although it is already in use in thousands of companies around the world, most big opportunities have not yet been tapped. The effects of AI will be magnified in the coming decade, as manufacturing, retailing, transportation, finance, health care, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning. The bottleneck now is in management, implementation, and business imagination.

The machine learns from examples, rather than being explicitly programmed for a particular outcome.

 

Let’s start by exploring what AI is already doing and how quickly it is improving. The biggest advances have been in two broad areas: perception and cognition. …For instance, Aptonomy and Sanbot, makers respectively of drones and robots, are using improved vision systems to automate much of the work of security guards. 

 

 

Machine learning is driving changes at three levels: tasks and occupations, business processes, and business models. 

 

 

You may have noticed that Facebook and other apps now recognize many of your friends’ faces in posted photos and prompt you to tag them with their names.

 

 

 

McKinsey’s State Of Machine Learning & AI, 2017 — from forbes.com by Louis Columbus

Excerpts:

These and other findings are from the McKinsey Global Institute Study, and discussion paper, Artificial Intelligence, The Next Digital Frontier (80 pp., PDF, free, no opt-in) published last month. McKinsey Global Institute published an article summarizing the findings titled   How Artificial Intelligence Can Deliver Real Value To Companies. McKinsey interviewed more than 3,000 senior executives on the use of AI technologies, their companies’ prospects for further deployment, and AI’s impact on markets, governments, and individuals.  McKinsey Analytics was also utilized in the development of this study and discussion paper.

 

Video: 4 FAQs about Watson as tutor — from er.educause.edu by Satya Nitta

Excerpt:

How is IBM using Watson’s intelligent tutoring system? So we are attempting to mimic the best practices of human tutoring. The gold standard will always remain one on one human to human tutoring. The whole idea here is an intelligent tutoring system as a computing system that works autonomously with learners, so there is no human intervention. It’s basically pretending to be the teacher itself and it’s working with the learner. What we’re attempting to do is we’re attempting to basically put conversational systems, systems that understand human conversation and dialogue, and we’re trying to build a system that, in a very natural way, interacts with people through conversation. The system basically has the ability to ask questions, to answer questions, to know who you are and where you are in your learning journey, what you’re struggling with, what you’re strong on and it will personalize its pedagogy to you.

There’s a natural language understanding system and a machine learning system that’s trying to figure out where you are in your learning journey and what the appropriate intervention is for you. The natural language system enables this interaction that’s very rich and conversation-based, where you can basically have a human-like conversation with it and, to a large extent, it will try to understand and to retrieve the right things for you. Again the most important thing is that we will set the expectations appropriately and we have appropriate exit criteria for when the system doesn’t actually understand what you’re trying to do.

 

 

 

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