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.

 

 

 

 

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 to be an ed tech futurist — from campustechnology.com by Bryan Alexander
While no one can predict the future, these forecasting methods will help you anticipate trends and spur more collaborative thinking.

Excerpts:

Some of the forecasting methods Bryan mentions are:

  • Trend analysis
  • Environmental scanning
  • Scenarios
  • Science fiction

 

 

 

 

From DSC:
I greatly appreciate the work that Bryan does — the topics that he chooses to write about, his analyses, comments, and questions are often thought-provoking. I couldn’t agree more with Bryan’s assertion that forecasting needs to become more realized/practiced within higher education. This is especially true given the exponential rate of change that many societies throughout the globe are now experiencing.

We need to be pulse-checking a variety of landscapes out there, to identify and put significant trends, forces, and emerging technologies on our radars. The strategy of identifying potential scenarios – and then developing responses to those potential scenarios — is very wise.

 

 

 

 

 

 

 

 

 

 

 

 

 

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:

 

 

 

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

 

 

Plan now to attend the 2018 Next Generation Learning Spaces Conference — tour USC’s campus!

From DSC:
I am honored to be currently serving on the 2018 Advisory Council for the Next Generation Learning Spaces Conference with a great group of people. Missing — at least from my perspective — from the image below is Kristen Tadrous, Senior Program Director with the Corporate Learning Network. Kristen has done a great job these last few years planning and running this conference.

 

The Advisory Board for the 2018 Next Generation Learning Spaces Conference

NOTE:
The above graphic reflects a recent change for me. I am still an Adjunct Faculty Member
at Calvin College, but I am no longer a Senior Instructional Designer there.
My brand is centered around being an Instructional Technologist.

 

This national conference will be held in Los Angeles, CA on February 26-28, 2018. It is designed to help institutions of higher education develop highly-innovative cultures — something that’s needed in many institutions of traditional higher education right now.

I have attended the first 3 conferences and I moderated a panel at the most recent conference out in San Diego back in February/March of this year. I just want to say that this is a great conference and I encourage you to bring a group of people to it from your organization! I say a group of people because a group of 5 of us (from a variety of departments) went one year and the result of attending the NGLS Conference was a brand new Sandbox Classroom — an active-learning based, highly-collaborative learning space where faculty members can experiment with new pedagogies as well as with new technologies. The conference helped us discuss things as a diverse group, think out load, come up with some innovative ideas, and then build the momentum to move forward with some of those key ideas.

If you haven’t already attended this conference, I highly recommend that you check it out. You can obtain the agenda/brochure for the conference by providing some basic contact information here.

 

The 2018 Next Generational Learning Spaces Conference- to be held in Los Angeles on Feb 26-28, 2018

 

Tour the campus at UCLA

Per Kristen Tadrous, here’s why you want to check out USC:

  • A true leader in innovation: USC made it to the Top 20 of Reuter’s 100 Most Innovative Universities in 2017!
  • Detailed guided tour of leading spaces led by the Information Technology Services Learning Environments team
  • Benchmark your own learning environments by getting a ‘behind the scenes’ look at their state-of-the-art spaces
  • There are only 30 spots available for the site tour

 



 

Building Spaces to Inspire a Culture of Innovation — a core theme at the 4th Next Generation Learning Spaces summit, taking place this February 26-28 in Los Angeles. An invaluable opportunity to meet and hear from like-minded peers in higher education, and continue your path toward lifelong learning. #ngls2018 http://bit.ly/2yNkMLL

 



 

 

 

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.”

 



 

 

 

 

 

How to improve memory retention in online training — from growthengineering.co.uk by Christopher Pappas

Excerpt:

4. Incorporate A “Moment Of Need” Online Training Repository
That brings us to the next tip, which is to incorporate a “just in time” online training library. This features microlearning online training resources that are easy to digest and remember. Employees can access support tools based on their needs, goals, and skill gaps. Best of all, they can expand their knowledge whenever it’s most convenient, whether that’s on the sales floor, before a client meeting, or during the morning commute. “Moment of need” online training repositories aid in memory retention by breaking the online training content into consumable pieces, instead of barraging your employees with large quantities of information.

 

From DSC:
This idea of an online training repository is tied in with a more recent development of “chatbots.” As artificial intelligence continues to pick up steam, these chatbots could offer internal employees as well as external customers automated responses to questions. People could ask the questions either by typing in their questions and/or by using their voices to ask their questions. So keep your eyes on chatbots — as they will likely bring a whole new method of obtaining information and professional development to us in the near future!

 



 

Also from Christopher Pappas (@cpappas) see:

 

 



 

 

Cameras are Watching and Machines are Learning: The Beginning — from medium.com by Brian Brackeen
You better believe their eyes

This is a new series about cameras and their relationship to face recognition, machine learning, and how, in the future, the ways in which we interact with technology will be radically different.

Excerpt (emphasis DSC):

First, the data.
LDV Capital, a venture capital firm focussed on Visual Technologies, recently published a 19 page report thick with some pretty eye opening data around cameras.

Specifically, how many cameras we can expect to have watching us, what they are watching us for, and how those insights will be used.

According to their study, by 2022 there will be more than 44,354,881,622 (that’s 44 BILLION) cameras in use globally, collecting even more billions of images for visual collateral. This is incredible — but what’s interesting — is that most of these images will never be seen by human eyes.

 

 

 

From DSC:
Though the author asserts there will be great business opportunities surrounding this trend, I’m not sure that I’m comfortable with it. Embedded cameras everywhere…hmmm…what he calls a privilege (in the quote below), I see as an overstepping of boundaries.

We have the privilege of experiencing the actual evolution of a device that we have come to know as one thing, for all of our lives to this point, into something completely different, to the extent that the word “camera”, itself, is becoming outdated.

How do you feel about this trend?

 

 

 

AI and Internet of Things will drive digital transformation through 2020 — from zdnet.com by Courtney Sato
Research study reveals IoT, AI and synchronous ledger tech (blockchain) priorities.

Excerpt:

Businesses are investing heavily in the Internet of Things (IoT) while remaining cautious about investments in artificial intelligence (AI), reveals the Constellation Research 2017 Digital Transformation Study. However, Constellation expects AI to emerge in 2018 as the predominant area of technological experimentation due to the increasing availability of AI development kits and frameworks.

Nearly half of respondents of the Constellation 2017 Digital Transformation Survey said their organization either had an established IoT strategy with applications in production (19 percent) or have pilot projects underway (28 percent). In contrast, just 25 percent of executives said they were investing in AI.

 

Investmet in AI Digital Transformation
 

 

Highlights:

  • Charging ahead with IoT
  • Cautious about AI for now
  • Blockchain remains enigmatic
  • Appetite for cloud and big data grow to support digital transformation
  • Digital transformation goes mainstream
  • Digital transformation focuses on digital business
  • The war for talent intensifies

 

 

 

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.

 

 

 

 

10 really hard decisions coming our way — from gettingsmart.com by Tom Vander Ark

Excerpt (emphasis DSC):

Things are about to get interesting. You’ve likely heard that Google’s DeepMind recently beat the world’s best Go player. But in far more practical and pervasive ways, artificial intelligence (AI) is creeping into every aspect of life–every screen you view, every search, every purchase, and every customer service contact.

What’s happening? It’s the confluence of several technologies–Moore’s law made storage, computing, and access devices almost free.

This Venn diagram illustrates how deep learning is a subset of AI and how, when combined with big data, can inform enabling technologies in many sectors. For examples, to AI and big data add:

  • Robotics, and you have industry 4.0.
  • Cameras and sensor package, and you have self-driving cars.
  • Sensors and bioinformatic maps, and you have precision medicine.

While there is lots of good news here–diseases will be eradicated and clean energy will be produced–we have a problem: this stuff is moving faster than civic infrastructure can handle. Innovation is outpacing public policy on all fronts. The following are 10 examples of issues coming at us fast that we (in the US in particular) are not ready to deal with.

  1. Unemployment.
  2. Income inequality.
  3. Privacy
  4. Algorithmic bias.
  5. Access.
  6. Machine ethics. 
  7. Weaponization. 
  8. Humanity. 
  9. Genome editing.
  10. Bad AI.

 


From DSC:
Readers of this blog will know that I’m big on pulse-checking the pace of technological change — because it has enormous ramifications for societies throughout the globe, as well as for individuals, workforces, corporations, jobs, education, training, higher education and more. Readers of this blog will again hear me say that the pace of change has changed. We’re now on an exponential pace/trajectory (vs. a slow, steady, linear path).

“Innovation is outpacing public policy on all fronts.”

How true this is. Our society doesn’t know how to deal with this new pace of change. How shall we tackle this thorny issue?

 


 

 

 

 
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