5 technologies disrupting the app development industry — from cio.com by Kevin Rands
Developers who want to be at the top of their game will need to roll with the times and constantly innovate, whether they’re playing around with new form factors or whether they’re learning to code in a new language.

Excerpts:

But with so much disruption on the horizon, what does this mean for app developers? Let’s find out.

  1. AI and machine Learning
  2. The Internet of Things
  3. Blockchain
  4. Self-driving tech
  5. AR and VR

 

 

 

Amazon Intros Alexa for Business — from campustechnology.com by Rhea Kelly

Excerpt:

Amazon Web Services today announced Alexa for Business, a new service that provides voice control for office tasks. The Alexa intelligent assistant can help start conference calls, control conference room equipment, schedule meetings, keep track of tasks, notify IT of an equipment issue or reorder supplies, the company noted in a news announcement. The service can also be customized to voice-enable an organization’s specific IT applications and office systems.

 

Also see:

 

Shared devices

 

 

EDUCAUSE 2017: Microsoft VP Praises the Power of Artificial Intelligence — from edtechmagazine.com
Artificial intelligence and connected systems advancements are creating a foundation where higher education can use insights and data to drive more efficient campus management, Microsoft’s Anthony Salcito explains.

 

 

 

Analysts and AI: A winning combination — from information-age.com
Artificial intelligence is crucial in helping analysts achieve more in day-to-day operations, and drive innovation

Excerpt:

A Capgemini and LinkedIn study of 1,000 companies with revenue of $500 million+ reported that 2 in 3 jobs being created as a result of AI were at management level, and of those that have implemented the technology at scale, 89% believe complex jobs will be made easier, and 88% say humans and machines will co-exist within their business.

 

 

 

 

 

 

 

 

 

From DSC:
In this video, I look at how the pace of change has changed and I also provide some examples that back up this assertion. I end with a series of relevant questions, especially for those of us working within higher education.

What are we doing to get ready for the massive change that’s heading our way?

 

 

How AI-powered enterprise chatbot platforms are transforming the future of work — from chatbotsmagazine.com by Gina Shaw

Excerpts:

WHAT IS AN ENTERPRISE CHATBOT PLATFORM?
To sum it up in a few words, a chatbot platform is a toolset which is used to build and deploy chatbots. Every organization has its own set of unique challenges that can be overcome by convenient automation provided by chatbots. After establishing a clear-cut chatbot strategy, enterprises can use a bot builder platform to build, train and manage customized bots. Before the advent of chatbot platforms, building a bot was a strenuous task and required sophisticated toolsets and advanced coding knowledge. However with time, several bot building platforms flooded the chatbot market and led to the creation of safe AI bots which need minimum deployment time and almost zero coding knowledge. Enterprise chatbot platforms also allow IT departments to have complete control and access to monitoring bots.

 

From DSC:
It is with some hesitation that I post this article. Why? Because:

  1. I started out my career in a customer service related position at Baxter Healthcare, and it was one of the most important jobs that I’ve had because it taught me the value of a customer. Ever since then, I have treated everyone as my customer — whether they be internal or external to the organization that I was working for.
  2. Then, there’s the idea of calling a Voice Response Unit (VRU) — which sometimes works well and sometimes I can’t stand it. There are times when I/we simply want to speak to a fellow human being.

So it is with some hesitation that I post this article. But I do so because it is yet another example of:

  • The increased usage of algorithms, software, bots, personal assistants, AI, etc. to obtain answers and information
  • The changing skillset employees will need and job seekers may want to develop (if such things are interesting to them)
  • The massive changes heading our way

 

 

 

Google, Amazon Find Not Everyone Is Ready for AI — from wired.com by Tom Simonite

Excerpt:

Yet as Amazon and Google seek greater riches by infusing the world with artificial intelligence, they’ve started their own consulting operations, lending out some of their prized AI talent to customers. The reason: Those other businesses lack the expertise to take advantage of techniques such as machine learning.

The expertise shortage upsets the usual dynamic of the cloud market, where Amazon, Google, and others mostly compete on price and technical features. “If you’re a random manufacturing company in the midwest you may have money, but it’s hard to attract a $250,000-a-year Stanford PhD to work for you,” says Diego Oppenheimer, whose Google-backed startup provides tools that help companies deploy machine-learning software. Companies in that situation may be more swayed by an offer of help building AI, than pricing and performance, he says.

 

 

 

 

AI: Embracing the promises and realities — from the Allegis Group

Excerpts:

What will that future be? When it comes to jobs, the tea leaves are indecipherable as analysts grapple with emerging technologies, new fields of work, and skills that have yet to be conceived. The only certainty is
that jobs will change. Consider the conflicting predictions put forth by the analyst community:

  • According to the Organization of Economic Cooperation and Development, only 5-10% of labor would be displaced by intelligent automation, and new job creation will offset losses.  (Inserted comment from DSC: Hmmm. ONLY 5-10%!? What?! That’s huge! And don’t count on the majority of those people becoming experts in robotics, algorithms, big data, AI, etc.)
  • The World Economic Forum27 said in 2016 that 60% of children entering school today will work in jobs that do not yet exist.
  • 47% of all American job functions could be automated within 20 years, according to the Oxford Martin School on Economics in a 2013 report.
  • In 2016, a KPMG study estimated that 100 million global knowledge workers could be affected by robotic process automation by 2025.

Despite the conflicting views, most analysts agree on one thing: big change is coming. Venture Capitalist David Vandergrift has some words of advice: “Anyone not planning to retire in the next 20 years should be paying pretty close attention to what’s going on in the realm of AI. The supplanting (of jobs) will not happen overnight: the trend over the next couple of decades is going to be towards more and more automation.”30

While analysts may not agree on the timing of AI’s development in the economy, many companies are already seeing its impact on key areas of talent and business strategy. AI is replacing jobs, changing traditional roles, applying pressure on knowledge workers, creating new fields of work, and raising the demand for certain skills.

 

 

 

 

 

The emphasis on learning is a key change from previous decades and rounds of automation. Advanced AI is, or will soon be, capable of displacing a very wide range of labor, far beyond the repetitive, low-skill functions traditionally thought to be at risk from automation. In many cases, the pressure on knowledge workers has already begun.

 

 

 

 

Regardless of industry, however, AI is a real challenge to today’s way of thinking about work, value, and talent scarcity. AI will expand and eventually force many human knowledge workers to reinvent their roles to address issues that machines cannot process. At the same time, AI will create a new demand for skills to guide its growth and development. These emerging areas of expertise will likely be technical or knowledge-intensive fields. In the near term, the competition for workers in these areas may change how companies focus their talent strategies.

 

 

 

 

The Impact of Alexa and Google Home on Consumer Behavior — from chatbotsmagazine.com by Arte Merritt

Excerpt (emphasis DSC):

2017 has turned out to be the year of voice. Amazon Alexa passed over 10 million unit sales earlier in the year and there are over 24,000 Skills in the store. With the addition of new devices like the Echo Show, Echo Plus, improved Echo Dot, and a new form factor for the Echo, there’s an option for everyone’s budget. Google is right there as well with the addition of the Google Mini to go along with the original Google Home. Apple’s efforts with Siri and HomePod, Samsung’s Bixby, and Microsoft’s Cortana round out the major tech firms efforts in this space.

 

 

Also see:

 

Amazon Alexa Store -- has over 24,000 skills as of November 29, 2017

 

 

 

How artificial intelligence could transform government — from Deloitte University Press
Cognitive technologies have the potential to revolutionize the public sector—and save billions of dollars

Excerpt:

The rise of more sophisticated cognitive technologies is, of course, critical to that third era, aiding advances in several categories:

  • Rules-based systems capture and use experts’ knowledge to provide answers to tricky but routine problems. As this decades-old form of AI grows more sophisticated, users may forget they aren’t conversing with a real person.
  • Speech recognition transcribes human speech automatically and accurately. The technology is improving as machines collect more examples of conversation. This has obvious value for dictation, phone assistance, and much more.
  • Machine translation, as the name indicates, translates text or speech from one language to another. Significant advances have been made in this field in only the past year.8 Machine translation has obvious implications for international relations, defense, and intelligence as well as, in our multilingual society, numerous domestic applications.
  • Computer vision is the ability to identify objects, scenes, and activities in naturally occurring images. It’s how Facebook sorts millions of users’ photos, but it can also scan medical images for indications of disease and identify criminals from surveillance footage. Soon it will allow law enforcement to quickly scan license plate numbers of vehicles stopped at red lights, identifying suspects’ cars in real time.
  • Machine learning takes place without explicit programming. By trial and error, computers learn how to learn, mining information to discover patterns in data that can help predict future events. The larger the datasets, the easier it is to accurately gauge normal or abnormal behavior. When your email program flags a message as spam, or your credit card company warns you of a potentially fraudulent use of your card, machine learning may be involved. Deep learning is a branch of machine learning involving artificial neural networks inspired by the brain’s structure and function.9
  • Robotics is the creation and use of machines to perform automated physical functions. The integration of cognitive technologies such as computer vision with sensors and other sophisticated hardware has given rise to a new generation of robots that can work alongside people and perform many tasks in unpredictable environments. Examples include drones, robots used for disaster response, and robot assistants in home health care.
  • Natural language processing refers to the complex and difficult task of organizing and understanding language in a human way. This goes far beyond interpreting search queries, or translating between Mandarin and English text. Combined with machine learning, a system can scan websites for discussions of specific topics even if the user didn’t input precise search terms. Computers can identify all the people and places mentioned in a document or extract terms and conditions from contracts. As with all AI-enabled technology, these become smarter as they consume more accurate data—and as developers integrate complementary technologies such as machine translation and natural language processing.

We’ve developed a framework that can help government agencies assess their own opportunities for deploying these technologies. It involves examining business processes, services, and programs to find where cognitive technologies may be viable, valuable, or even vital. Figure 8 summarizes this “Three Vs” framework. Government agencies can use it to screen the best opportunities for automation or cognitive technologies.

 

 

 

 

The future of work: How artificial intelligence will transform the employee experience — from forbes.com by Jeanne Meister

Excerpt:

Artificial Intelligence is on the verge of penetrating every major industry from healthcare to advertising, transportation, finance, legal, education, and now inside the workplace. Many of us may have already interacted with a chatbot (defined as an automated, yet personalized, conversation between software and human users) whether it’s on Facebook Messenger to book a hotel room or ordering flowers through 1-800 flowers. According to Facebook Vice President, David Marcus, there are now more than 100,000 chatbots on the Facebook Messenger platform, up from 33,000 in 2016.

As we increase the usage of chatbots in our personal lives, we will expect to use them in the workplace to assist us with things like finding new jobs, answering frequently asked HR related questions or even receiving coaching and mentoring.  Chatbots digitize HR processes and enable employees to access HR solutions from anywhere. Using artificial intelligence in HR will create a more seamless employee experience, one that is nimbler and more user driven.

 

 

 

 

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

 

 

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