Ten HR trends in the age of artificial intelligence — from fortune.com by Jeanne Meister
The future of HR is both digital and human as HR leaders focus on optimizing the combination of human and automated work. This is driving a new HR priority: requiring leaders and teams to develop fluency in artificial intelligence while they re-imagine HR to be more personal, human, and intuitive.

Excerpt from 21 More Jobs Of the Future (emphasis DSC):

Voice UX Designer: This role will leverage voice as a platform to deliver an “optimal” dialect and sound that is pleasing to each of the seven billion humans on the planet. The Voice UX Designer will do this by creating a set of AI tools and algorithms to help individuals find their “perfect voice” assistant.

Head of Business Behavior: The head of business behavior will analyze employee behavioral data such as performance data along with data gathered through personal, environmental and spatial sensors to create strategies to improve employee experience, cross company collaboration, productivity and employee well-being.

The question for HR leaders is: What are new job roles in HR that are on the horizon as A.I. becomes integrated into the workplace?

Chief Ethical and Humane Use Officer: This job role is already being filled by Salesforce announcing its first Chief Ethical and Humane Officer this month. This new role will focus on developing strategies to use technology in an ethical and humane way. As practical uses of AI have exploded in recent years, we look for more companies to establish new jobs focusing on ethical uses of AI to ensure AI’s trustworthiness, while also helping to diffuse fears about it.

A.I. Trainer: This role allows the existing knowledge you have about a job to be ready for A.I. to use.  Creating knowledge for an A.I. supported workplace requires individuals to tag or “annotate” discrete knowledge nuggets so the correct data is served up in a conversational interface. This role is increasingly important as the role of a recruiter is augmented by AI.

 

 

Also see:

  • Experts Weigh in on Merits of AI in Education — from by Dian Schaffhauser
    Excerpt:
    Will artificial intelligence make most people better off over the next decade, or will it redefine what free will means or what a human being is? A new report by the Pew Research Center has weighed in on the topic by conferring with some 979 experts, who have, in summary, predicted that networked AI “will amplify human effectiveness but also threaten human autonomy, agency and capabilities.”

    These same experts also weighed in on the expected changes in formal and informal education systems. Many mentioned seeing “more options for affordable adaptive and individualized learning solutions,” such as the use of AI assistants to enhance learning activities and their effectiveness.

 

 

Top six AI and automation trends for 2019 — from forbes.com by Daniel Newman

Excerpt:

If your company hasn’t yet created a plan for AI and automation throughout your enterprise, you have some work to do. Experts believe AI will add nearly $16 trillion to the global economy by 2030, and 20 % of companies surveyed are already planning to incorporate AI throughout their companies next year. As 2018 winds down, now is the time to take a look at some trends and predictions for AI and automation that I believe will dominate the headlines in 2019—and to think about how you may incorporate them into your own company.

 

Also see — and an insert here from DSC:

Kai-Fu has a rosier picture than I do in regards to how humanity will be impacted by AI. One simply needs to check out today’s news to see that humans have a very hard time creating unity, thinking about why businesses exist in the first place, and being kind to one another…

 

 

 

How AI can save our humanity 

 

 

 

Guide to how artificial intelligence can change the world – Part 3 — from intelligenthq.com by Maria Fonseca and Paula Newton
This is part 3 of a Guide in 4 parts about Artificial Intelligence. The guide covers some of its basic concepts, history and present applications, possible developments in the future, and also its challenges as opportunities.

Excerpt:

Artificial intelligence is considered to be anything that gives machines intelligence which allows them to reason in the way that humans can. Machine learning is an element of artificial intelligence which is when machines are programmed to learn. This is brought about through the development of algorithms that work to find patterns, trends and insights from data that is input into them to help with decision making. Deep learning is in turn an element of machine learning. This is a particularly innovative and advanced area of artificial intelligence which seeks to try and get machines to both learn and think like people.

 

Also see:

 

Also see:

LinkedIn’s 2018 U.S. emerging jobs report — from economicgraph.linkedin.com

Excerpt (emphasis DSC):

Our biggest takeaways from this year’s Emerging Jobs Report:

  • Artificial Intelligence (AI) is here to stay. No, this doesn’t mean robots are coming for your job, but we are likely to see continued growth in fields and functions related to AI. This year, six out of the 15 emerging jobs are related in some way to AI, and our research shows that skills related to AI are starting to infiltrate every industry, not just tech. In fact, AI skills are among the fastest-growing skills on LinkedIn, and globally saw a 190% increase from 2015 to 2017.

 

 

Forecast 5.0 – The Future of Learning: Navigating the Future of Learning  — from knowledgeworks.org by Katherine Prince, Jason Swanson, and Katie King
Discover how current trends could impact learning ten years from now and consider ways to shape a future where all students can thrive.

 

 

 

LinkedIn Learning Opens Its Platform (Slightly) [Young]

LinkedIn Learning Opens Its Platform (Slightly) — from edsurge by Jeff Young

Excerpt (emphasis DSC):

A few years ago, in a move toward professional learning, LinkedIn bought Lynda.com for $1.5 billion, adding the well-known library of video-based courses to its professional social network. Today LinkedIn officials announced that they plan to open up their platform to let in educational videos from other providers as well—but with a catch or two.

The plan, announced Friday, is to let companies or colleges who already subscribe to LinkedIn Learning add content from a select group of other providers. The company or college will still have to subscribe to those other services separately, so it’s essentially an integration—but it does mark a change in approach.

For LinkedIn, the goal is to become the front door for employees as they look for micro-courses for professional development.

 

LinkedIn also announced another service for its LinkedIn Learning platform called Q&A, which will give subscribers the ability to pose a question they have about the video lessons they’re taking. The question will first be sent to bots, but if that doesn’t yield an answer the query will be sent on to other learners, and in some cases the instructor who created the videos.

 

 

Also see:

LinkedIn becomes a serious open learning experience platform — from clomedia.com by Josh Bersin
LinkedIn is becoming a dominant learning solution with some pretty interesting competitive advantages, according to one learning analyst.

Excerpt:

LinkedIn has become quite a juggernaut in the corporate learning market. Last time I checked the company had more than 17 million users, 14,000 corporate customers, more than 3,000 courses and was growing at high double-digit rates. And all this in only about two years.

And the company just threw down the gauntlet; it’s now announcing it has completely opened up its learning platform to external content partners. This is the company’s formal announcement that LinkedIn Learning is not just an amazing array of content, it is a corporate learning platform. The company wants to become a single place for all organizational learning content.

 

LinkedIn now offers skills-based learning recommendations to any user through its machine learning algorithms. 

 

 



Is there demand for staying relevant? For learning new skills? For reinventing oneself?

Well…let’s see.

 

 

 

 

 

 



From DSC:
So…look out higher ed and traditional forms of accreditation — your window of opportunity may be starting to close. Alternatives to traditional higher ed continue to appear on the scene and gain momentum. LinkedIn — and/or similar organizations in the future — along with blockchain and big data backed efforts may gain traction in the future and start taking away some major market share. If employers get solid performance from their employees who have gone this route…higher ed better look out. 

Microsoft/LinkedIn/Lynda.com are nicely positioned to be a major player who can offer society a next generation learning platform at an incredible price — offering up-to-date, microlearning along with new forms of credentialing. It’s what I’ve been calling the Amazon.com of higher ed (previously the Walmart of Education) for ~10 years. It will take place in a strategy/platform similar to this one.

 



Also, this is what a guerilla on the back looks like:

 

This is what a guerilla on the back looks like!

 



Also see:

  • Meet the 83-Year-Old App Developer Who Says Edtech Should Better Support Seniors — from edsurge.com by Sydney Johnson
    Excerpt (emphasis DSC):
    Now at age 83, Wakamiya beams with excitement when she recounts her journey, which has been featured in news outlets and even at Apple’s developer conference last year. But through learning how to code, she believes that experience offers an even more important lesson to today’s education and technology companies: don’t forget about senior citizens.Today’s education technology products overwhelmingly target young people. And while there’s a growing industry around serving adult learners in higher education, companies largely neglect to consider the needs of the elderly.

 

 

From DSC:
I have often reflected on differentiation or what some call personalized learning and/or customized learning. How does a busy teacher, instructor, professor, or trainer achieve this, realistically?

It’s very difficult and time-consuming to do for sure. But it also requires a team of specialists to achieve such a holy grail of learning — as one person can’t know it all. That is, one educator doesn’t have the necessary time, skills, or knowledge to address so many different learning needs and levels!

  • Think of different cognitive capabilities — from students that have special learning needs and challenges to gifted students
  • Or learners that have different physical capabilities or restrictions
  • Or learners that have different backgrounds and/or levels of prior knowledge
  • Etc., etc., etc.

Educators  and trainers have so many things on their plates that it’s very difficult to come up with _X_ lesson plans/agendas/personalized approaches, etc.  On the other side of the table, how do students from a vast array of backgrounds and cognitive skill levels get the main points of a chapter or piece of text? How can they self-select the level of difficulty and/or start at a “basics” level and work one’s way up to harder/more detailed levels if they can cognitively handle that level of detail/complexity? Conversely, how do I as a learner get the boiled down version of a piece of text?

Well… just as with the flipped classroom approach, I’d like to suggest that we flip things a bit and enlist teams of specialists at the publishers to fulfill this need. Move things to the content creation end — not so much at the delivery end of things. Publishers’ teams could play a significant, hugely helpful role in providing customized learning to learners.

Some of the ways that this could happen:

Use an HTML like language when writing a textbook, such as:

<MainPoint> The text for the main point here. </MainPoint>

<SubPoint1>The text for the subpoint 1 here.</SubPoint1>

<DetailsSubPoint1>More detailed information for subpoint 1 here.</DetailsSubPoint1>

<SubPoint2>The text for the subpoint 2 here.</SubPoint2>

<DetailsSubPoint2>More detailed information for subpoint 2 here.</DetailsSubPoint2>

<SubPoint3>The text for the subpoint 3 here.</SubPoint3>

<DetailsSubPoint3>More detailed information for subpoint 3 here.</DetailsSubPoint1>

<SummaryOfMainPoints>A list of the main points that a learner should walk away with.</SummaryOfMainPoints>

<BasicsOfMainPoints>Here is a listing of the main points, but put in alternative words and more basic ways of expressing those main points. </BasicsOfMainPoints>

<Conclusion> The text for the concluding comments here.</Conclusion>

 

<BasicsOfMainPoints> could be called <AlternativeExplanations>
Bottom line: This tag would be to put things forth using very straightforward terms.

Another tag would be to address how this topic/chapter is relevant:
<RealWorldApplication>This short paragraph should illustrate real world examples

of this particular topic. Why does this topic matter? How is it relevant?</RealWorldApplication>

 

On the students’ end, they could use an app that works with such tags to allow a learner to quickly see/review the different layers. That is:

  • Show me just the main points
  • Then add on the sub points
  • Then fill in the details
    OR
  • Just give me the basics via an alternative ways of expressing these things. I won’t remember all the details. Put things using easy-to-understand wording/ideas.

 

It’s like the layers of a Microsoft HoloLens app of the human anatomy:

 

Or it’s like different layers of a chapter of a “textbook” — so a learner could quickly collapse/expand the text as needed:

 

This approach could be helpful at all kinds of learning levels. For example, it could be very helpful for law school students to obtain outlines for cases or for chapters of information. Similarly, it could be helpful for dental or medical school students to get the main points as well as detailed information.

Also, as Artificial Intelligence (AI) grows, the system could check a learner’s cloud-based learner profile to see their reading level or prior knowledge, any IEP’s on file, their learning preferences (audio, video, animations, etc.), etc. to further provide a personalized/customized learning experience. 

To recap:

  • “Textbooks” continue to be created by teams of specialists, but add specialists with knowledge of students with special needs as well as for gifted students. For example, a team could have experts within the field of Special Education to help create one of the overlays/or filters/lenses — i.e., to reword things. If the text was talking about how to hit a backhand or a forehand, the alternative text layer could be summed up to say that tennis is a sport…and that a sport is something people play. On the other end of the spectrum, the text could dive deeply into the various grips a person could use to hit a forehand or backhand.
  • This puts the power of offering differentiation at the point of content creation/development (differentiation could also be provided for at the delivery end, but again, time and expertise are likely not going to be there)
  • Publishers create “overlays” or various layers that can be turned on or off by the learners
  • Can see whole chapters or can see main ideas, topic sentences, and/or details. Like HTML tags for web pages.
  • Can instantly collapse chapters to main ideas/outlines.

 

 

Robots won’t replace instructors, 2 Penn State educators argue. Instead, they’ll help them be ‘more human.’ — from edsurge.com by Tina Nazerian

Excerpt:

Specifically, it will help them prepare for and teach their courses through several phases—ideation, design, assessment, facilitation, reflection and research. The two described a few prototypes they’ve built to show what that might look like.

 

Also see:

The future of education: Online, free, and with AI teachers? — from fool.com by Simon Erickson
Duolingo is using artificial intelligence to teach 300 million people a foreign language for free. Will this be the future of education?

Excerpts:

While it might not get a lot of investor attention, education is actually one of America’s largest markets.

The U.S. has 20 million undergraduates enrolled in colleges and universities right now and another 3 million enrolled in graduate programs. Those undergrads paid an average of $17,237 for tuition, room, and board at public institutions in the 2016-17 school year and $44,551 for private institutions. Graduate education varies widely by area of focus, but the average amount paid for tuition alone was $24,812 last year.

Add all of those up, and America’s students are paying more than half a trillion dollars each year for their education! And that doesn’t even include the interest amassed for student loans, the college-branded merchandise, or all the money spent on beer and coffee.

Keeping the costs down
Several companies are trying to find ways to make college more affordable and accessible.

 

But after we launched, we have so many users that nowadays if the system wants to figure out whether it should teach plurals before adjectives or adjectives before plurals, it just runs a test with about 50,000 people. So for the next 50,000 people that sign up, which takes about six hours for 50,000 new users to come to Duolingo, to half of them it teaches plurals before adjectives. To the other half it teaches adjectives before plurals. And then it measures which ones learn better. And so once and for all it can figure out, ah it turns out for this particular language to teach plurals before adjectives for example.

So every week the system is improving. It’s making itself better at teaching by learning from our learners. So it’s doing that just based on huge amounts of data. And this is why it’s become so successful I think at teaching and why we have so many users.

 

 

From DSC:
I see AI helping learners, instructors, teachers, and trainers. I see AI being a tool to help do some of the heavy lifting, but people still like to learn with other people…with actual human beings. That said, a next generation learning platform could be far more responsive than what today’s traditional institutions of higher education are delivering.

 

 

Amazon’s new goal: Teach 10 million kids a year to code — from businessinsider.com by Joseph Pisani

Excerpt:

NEW YORK (AP) — Amazon wants to get more kids thinking about becoming computer engineers.

The company launched a program Thursday that aims to teach more than 10 million students a year how to code. Amazon said it will pay for summer camps, teacher training and other initiatives to benefit kids and young adults from low-income families who might not have learned to code otherwise. It hopes the programs spur more black, Hispanic and female students to study computer science.

 

From DSC:
It will be interesting to see how artificial intelligence impacts the demand for programmers as the years progress. 

 

 

Google already knows what you did next summer — from bloomberg.com by Nikki Ekstein
The company’s new travel tools put the focus on artificial intelligence, helping to best predict what you’re going to love—no matter where you go.

Excerpt:

But it’s not a hotel or travel agency that’s cracking the golden acorn. It’s Google. The tech titan is leveraging its immense artificial intelligence and machine-learning capabilities to boost its travel offerings, which currently cover everything from flight and hotel search to activity recommendations, destination guides, and mapping services

The proof is in the pudding. Over the past few months, Google has quietly launched an array of travel-focused features and updates that highlight just how intuitive its AI technology has become. Put them all together and you’ll have enough reason to believe your next travel agent might just be a Google-powered bot.

 

Academics Propose a ‘Blockchain University,’ Where Faculty (and Algorithms) Rule — from edsurge.com by Jeff Young

Excerpt:

A group of academics affiliated with Oxford University have proposed a new model of higher education that replaces traditional administrators with “smart contracts” on the blockchain, the same technology that drives Bitcoin and other cryptocurrencies.

“Our aim is to create a university in which the bulk of administrative tasks are either eliminated or progressively automated,” said the effort’s founders in a white paper released earlier this year. Those proposing the idea added the university would be “a decentralised, non-profit, democratic community in which the use of blockchain technology will provide the contractual stability needed to pursue a full course of study.”

Experiments with blockchain in higher education are underway at multiple campuses around the country, and many of researchers are looking into how to use the technology to verify and deliver credentials. Massachusetts Institute for Technology, for example, began issuing diplomas via blockchain last year.

The plan by Oxford researchers goes beyond digital diplomas—and beyond many typical proposals to disrupt education in general. It argues for a completely new framework for how college is organized, how professors are paid, and how students connect with learning. In other words, it’s a long shot.

But even if the proposed platform never emerges, it is likely to spur debates about whether blockchain technology could one day allow professors to reclaim greater control of how higher education operates through digital contracts.

 

The platform would essentially allow professors to organize their own colleges, and teach and take payments from students directly. “

 

 

 

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