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.

 

 

 

 

 

 

 

 

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

 

 

 

Ask About AI: The Future of Learning and Work — from gettingsmart.com by Tom Vander Ark

Excerpts:

Code that learns may prove to be the most important invention in human history. But in 2016, there was almost no discussion of the implications of artificial intelligence (AI) in K-12 education—either the immense implications for the employment landscape or the exciting potential to improve learning.

We spent two years studying the implications of AI and concluded that machine intelligence turbocharged by big data and enabling technologies like robotics is the most significant change force facing humanity. Given enormous benefits and challenges we’re just beginning to understand, we believe it is an important time to Ask About AI (#AskAboutAI).

After interviewing experts, hosting a dozen community conversations, and posting more than 50 articles we’re summarizing what we’ve learned in a new paper Ask About AI: The Future of Learning and Work.

The paper explores what’s happening in the automation economy, the civic and social implications, and how to prepare ourselves and our children for exponential change.

With this launch we’re also launching a new microsite on Future of Work.

 

 

 

 

To initiate lifelong learning, secondary schools should encourage students to be reflect on how they learn, and build habits of success. There are an increasing number of organizations interested in being lifelong learning partners for students—college alumni associations, professional schools and private marketplaces among them.

Self-directed learning is most powerfully driven by a sense of purpose. In our study of Millennial employment, Generation Do It Yourself, we learned that it is critical for young people to develop a sense of purpose before attending college to avoid the new worst-case scenario—racking up college debt and dropping out. A sense of purpose can be developed around a talent or issue, or their intersection; both can be cultivated by a robust guidance system.

We’ve been teaching digital literacy for two decades, but what’s new is that we all need to appreciate that algorithms curate every screen we see. As smart machines augment our capabilities, they will increasingly influence our perceptions, opportunities and decisions. That means that to self- and social awareness, we’ll soon need to add AI awareness.

Taken together, these skills and dispositions create a sense of agency—the ability to take ownership of learning, grow through effort and work with other people in order to do the learning you need to do.

 

 

 

 

McKinsey: automation may wipe out 1/3 of America’s workforce by 2030 — from axios.com by Steve LeVine

Excerpt (emphasis DSC):

In a new study that is optimistic about automation yet stark in its appraisal of the challenge ahead, McKinsey says massive government intervention will be required to hold societies together against the ravages of labor disruption over the next 13 years. Up to 800 million people—including a third of the work force in the U.S. and Germany—will be made jobless by 2030, the study says.

The bottom line: The economy of most countries will eventually replace the lost jobs, the study says, but many of the unemployed will need considerable help to shift to new work, and salaries could continue to flatline. “It’s a Marshall Plan size of task,” Michael Chui, lead author of the McKinsey report, tells Axios.

In the eight-month study, the McKinsey Global Institute, the firm’s think tank, found that almost half of those thrown out of work—375 million people, comprising 14% of the global work force—will have to find entirely new occupations, since their old one will either no longer exist or need far fewer workers. Chinese will have the highest such absolute numbers—100 million people changing occupations, or 12% of the country’s 2030 work force.

I asked Chui what surprised him the most of the findings. “The degree of transition that needs to happen over time is a real eye opener,” he said.

 

The transition compares to the U.S. shift from a largely agricultural to an industrial-services economy in the early 1900s forward. But this time, it’s not young people leaving farms, but mid-career workers who need new skills.

 

 

From DSC:
Higher education — and likely (strictly) vocational training outside of higher ed — is simply not ready for this! MAJOR reinvention will be necessary, and as soon as 2018 according to Forrester Research. 

One of the key values that institutions of traditional higher education can bring to the table is to help people through this gut wrenching transition — identifying which jobs are going to last for the next 5-10+ years and which ones won’t, and then be about the work of preparing the necessary programs quickly enough to meet the demands of the new economy.

Students/entrepreneurs out there, they say you should look around to see where the needs are and then develop products and/or services to meet those needs. Well, here you go!

 

 

 

As a member of the International Education Committee, at edX we are extremely aware of the changing nature of work and jobs. It is predicted that 50 percent of current jobs will disappear by 2030.

Anant Agarwal, CEO and Founder of edX, and Professor of
Electrical Engineering and Computer Science at MIT
(source)

 

 

 

Addendum:

Automation threatens 800 million jobs, but technology could still save us, says report — from theverge.com by James Vincent
New analysis says governments need to act now to help a labor force in flux

Excerpt:

A new report predicts that by 2030, as many as 800 million jobs could be lost worldwide to automation. The study, compiled by the McKinsey Global Institute, says that advances in AI and robotics will have a drastic effect on everyday working lives, comparable to the shift away from agricultural societies during the Industrial Revolution. In the US alone, between 39 and 73 million jobs stand to be automated — making up around a third of the total workforce.

 

If a computer can do one-third of your job, what happens next? Do you get trained to take on new tasks, or does your boss fire you, or some of your colleagues? What if you just get a pay cut instead? Do you have the money to retrain, or will you be forced to take the hit in living standards?

 

 

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.

 

 

 

 

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 Ivory Tower Can’t Keep Ignoring Tech — from nytimes.com by Cathy O’Neil

Excerpt:

We need academia to step up to fill in the gaps in our collective understanding about the new role of technology in shaping our lives. We need robust research on hiring algorithms that seem to filter out people with mental health disorders, sentencing algorithms that fail twice as often for black defendants as for white defendants, statistically flawed public teacher assessments or oppressive scheduling algorithms. And we need research to ensure that the same mistakes aren’t made again and again. It’s absolutely within the abilities of academic research to study such examples and to push against the most obvious statistical, ethical or constitutional failures and dedicate serious intellectual energy to finding solutions. And whereas professional technologists working at private companies are not in a position to critique their own work, academics theoretically enjoy much more freedom of inquiry.

 

 

There is essentially no distinct field of academic study that takes seriously the responsibility of understanding and critiquing the role of technology — and specifically, the algorithms that are responsible for so many decisions — in our lives.

 

 

There’s one solution for the short term. We urgently need an academic institute focused on algorithmic accountability. First, it should provide a comprehensive ethical training for future engineers and data scientists at the undergraduate and graduate levels, with case studies taken from real-world algorithms that are choosing the winners from the losers. Lecturers from humanities, social sciences and philosophy departments should weigh in.

 

 

 

Somewhat related:

 

 

 

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

 

 

2018 Tech Trends for Journalism & Media Report + the 2017 Tech Trends Annual Report that I missed from the Future Today Institute

 

2018 Tech Trends For Journalism Report — from the Future Today Institute

Key Takeaways

  • 2018 marks the beginning of the end of smartphones in the world’s largest economies. What’s coming next are conversational interfaces with zero-UIs. This will radically change the media landscape, and now is the best time to start thinking through future scenarios.
  • In 2018, a critical mass of emerging technologies will converge finding advanced uses beyond initial testing and applied research. That’s a signal worth paying attention to. News organizations should devote attention to emerging trends in voice interfaces, the decentralization of content, mixed reality, new types of search, and hardware (such as CubeSats and smart cameras).
  • Journalists need to understand what artificial intelligence is, what it is not, and what it means for the future of news. AI research has advanced enough that it is now a core component of our work at FTI. You will see the AI ecosystem represented in many of the trends in this report, and it is vitally important that all decision-makers within news organizations familiarize themselves with the current and emerging AI landscapes. We have included an AI Primer For Journalists in our Trend Report this year to aid in that effort.
  • Decentralization emerged as a key theme for 2018. Among the companies and organizations FTI covers, we discovered a new emphasis on restricted peer-to-peer networks to detect harassment, share resources and connect with sources. There is also a push by some democratic governments around the world to divide internet access and to restrict certain content, effectively creating dozens of “splinternets.”
  • Consolidation is also a key theme for 2018. News brands, broadcast spectrum, and artificial intelligence startups will continue to be merged with and acquired by relatively few corporations. Pending legislation and policy in the U.S., E.U. and in parts of Asia could further concentrate the power among a small cadre of information and technology organizations in the year ahead.
  • To understand the future of news, you must pay attention to the future of many industries and research areas in the coming year. When journalists think about the future, they should broaden the usual scope to consider developments from myriad other fields also participating in the knowledge economy. Technology begets technology. We are witnessing an explosion in slow motion.

Those in the news ecosystem should factor the trends in this report into their strategic thinking for the coming year, and adjust their planning, operations and business models accordingly.

 



 

 

2017 Tech Trends Annual Report — from the Future Today Institute; this is the first I’ve seen this solid report

Excerpts:

This year’s report has 159 trends.
This is mostly due to the fact that 2016 was the year that many areas of science and technology finally started to converge. As a result we’re seeing a sort of slow-motion explosion––we will undoubtedly look back on the last part of this decade as a pivotal moment in our history on this planet.

Our 2017 Trend Report reveals strategic opportunities and challenges for your organization in the coming year. The Future Today Institute’s annual Trend Report prepares leaders and organizations for the year ahead, so that you are better positioned to see emerging technology and adjust your strategy accordingly. Use our report to identify near-future business disruption and competitive threats while simultaneously finding new collaborators and partners. Most importantly, use our report as a jumping off point for deeper strategic planning.

 

 



 

Also see:

Emerging eLearning Tools and Platforms Improve Results — from learningsolutionsmag.com

  • Augmented and virtual reality offer ways to immerse learners in experiences that can aid training in processes and procedures, provide realistic simulations to deepen empathy and build communication skills, or provide in-the-workflow support for skilled technicians performing complex procedures.
  • Badges and other digital credentials provide new ways to assess and validate employees’ skills and mark their eLearning achievements, even if their learning takes place informally or outside of the corporate framework.
  • Chatbots are proving an excellent tool for spaced learning, review of course materials, guiding new hires through onboarding, and supporting new managers with coaching and tips.
  • Content curation enables L&D professionals to provide information and educational materials from trusted sources that can deepen learners’ knowledge and help them build skills.
  • eBooks, a relative newcomer to the eLearning arena, offer rich features for portable on-demand content that learners can explore, review, and revisit as needed.
  • Interactive videos provide branching scenarios, quiz learners on newly introduced concepts and terms, offer prompts for small-group discussions, and do much more to engage learners.
  • Podcasts can turn drive time into productive time, allowing learners to enjoy a story built around eLearning content.
  • Smartphone apps, available wherever learners take their phones or tablets, can be designed to offer product support, info for sales personnel, up-to-date information for repair technicians, and games and drills for teaching and reviewing content; the possibilities are limited only by designers’ imagination.
  • Social platforms like Slack, Yammer, or Instagram facilitate collaboration, sharing of ideas, networking, and social learning. Adopting social learning platforms encourages learners to develop their skills and contribute to their communities of practice, whether inside their companies or more broadly.
  • xAPI turns any experience into a learning experience. Adding xAPI capability to any suitable tool or platform means you can record learner activity and progress in a learning record store (LRS) and track it.

 



 

DevLearn Attendees Learn How to ‘Think Like a Futurist’ — from learningsolutionsmag.com

Excerpt:

How does all of this relate to eLearning? Again, Webb anticipated the question. Her response gave hope to some—and terrified others. She presented three possible future scenarios:

  • Everyone in the learning arena learns to recognize weak signals; they work with technologists to refine artificial intelligence to instill values. Future machines learn not only to identify correct and incorrect answers; they also learn right and wrong. Webb said that she gives this optimistic scenario a 25 percent chance of occurring.
  • Everyone present is inspired by her talk but they, and the rest of the learning world, do nothing. Artificial intelligence continues to develop as it has in the past, learning to identify correct answers but lacking values. Webb’s prediction is that this pragmatic optimistic scenario has a 50 percent chance of occurring.
  • Learning and artificial intelligence continue to develop on separate tracks. Future artificial intelligence and machine learning projects incorporate real biases that affect what and how people learn and how knowledge is transferred. Webb said that she gives this catastrophic scenario a 25 percent chance of occurring.

In an attempt to end on a strong positive note, Webb said that “the future hasn’t happened yet—we think” and encouraged attendees to take action. “To build the future of learning that you want, listen to weak signals now.”

 



 

 

 

 

 

Looking for something?

Use the form below to search the site:

Still not finding what you're looking for? Drop a comment on a post or contact us so we can take care of it!

© 2017 | Daniel Christian