analytics

Ten HR trends in the age of artificial intelligence [Meister]

On 01/09/2019, in 21st century, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, change, computer science, corporate / business world, corporate universities / corporate training, education, education technology, emerging technologies, entrepreneurship, ethics, future, game-changing environment, intelligent systems, intelligent tutoring, learning, learning ecosystem, Learning from the Living [Class] Room, morals/values, Natural Language Processing (NLP), personalized/customized learning, platforms, professional development, reinvent, staying relevant, surviving, tools, training / L&D, trends, vendors, voice recognition / voice enabled interfaces, workplace, by Daniel Christian

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 [Newman]

On 01/07/2019, in 21st century, analytics, bots, business, change, changing business models, computer science, corporate / business world, Daniel S. Christian, economics, human-computer interaction (HCI), innovation, intelligent systems, leadership, MBA, robotics, society, strategy, tools, training / L&D, trends, United States, vendors, vision/possibilities, workplace, by Daniel Christian

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…

Kai-Fu Lee at AI Frontiers: The Era of Artificial Intelligence

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:

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 [Prince, Swanson, & King]

On 12/08/2018, in 21st century, adjunct faculty, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, change, colleges, community colleges, data related items, digital learning, education, education technology, emerging technologies, formal learning, future, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, instructional design, intelligent systems, intelligent tutoring, internet, leadership, learning, learning ecosystem, Learning from the Living [Class] Room, learning spaces, mobile learning, multimedia, Natural Language Processing (NLP), online learning, online tutoring, pace of change, parents/guardians, personalized/customized learning, platforms, science, smart classrooms, social learning / networks, social media, society, sociology, student teaching/teacher education, student-related, teachers, teaching & learning, teaching online, technology (general), tools, trends, United States, universities, virtual tutoring, vision/possibilities, web-based collaboration, by Daniel Christian

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]

On 11/09/2018, in 21st century, 24x7x365 access, adult learning, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, business side of he, career development, change, changing business models, cloud-based computing / apps / other cloud-related, collaboration, colleges, communities of practice, community colleges, competency-based learning/education, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, cost of getting a degree, credentialing, dangers of the status quo, Daniel S. Christian, data related items, digital learning, disruption, education technology, elearning, formal learning, future, future of higher education, game-changing environment, global / globalization, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, intelligent systems, intelligent tutoring, internet, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, lifelong learning, marketplaces, microlearning, Microsoft, mobile learning, more voice more choice more control, multimedia, New "Amazon.com" of Higher Education, online learning, online tutoring, pace of change, personalized/customized learning, platforms, professional development, social learning / networks, social media, society, staying relevant, streams of content, student-related, surviving, technologies for your home, training / L&D, trends, United States, universities, using teams, vendors, vision/possibilities, web-based collaboration, workplace, by Daniel Christian

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:

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.

Introducing several new ideas to provide personalized, customized learning experiences for all kinds of learners! [Christian]

On 11/06/2018, in 21st century, 24x7x365 access, accessibility / UDL, adjunct faculty, analytics, Artificial Intelligence/Agents/LLMs/and Related, assistive technologies, attention, blended learning, bots, cloud-based computing / apps / other cloud-related, colleges, community colleges, content development, aggregation, repositories, Daniel S. Christian, digital learning, e-books, e-publishing related items (EPUB and more), e-readers, education, education technology, elearning, engagement / engaging students, face-to-face, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), hybrid learning, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, interaction design, interactivity, interface design, internet, K-12 related, law schools, learner profiles, learning, learning ecosystem, Learning from the Living [Class] Room, learning preferences, library / librarians, memory, more voice more choice more control, neurodivergent/special needs, personalized/customized learning, platforms, productivity / tips and tricks, reading, society, student-related, teachers, teaching & learning, technology (general), tools, traditional / tradition, training / L&D, universities, user experience (UX), user interface design, using teams, vendors, vision/possibilities, visualizing information, writing, youth, by Daniel Christian

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.

2 items re: AI’s potential impact/place within education

On 11/03/2018, in 21st century, 24x7x365 access, adult learning, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, business side of he, career development, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, cost of getting a degree, Daniel S. Christian, data related items, digital learning, distance education, education, education technology, elearning, future, game-changing environment, global / globalization, higher education, human-computer interaction (HCI), innovation, intelligent systems, intelligent tutoring, internet, IT in HE, languages and translation, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, microlearning, mobile learning, more voice more choice more control, Natural Language Processing (NLP), New "Amazon.com" of Higher Education, online learning, online media, organizational change, pace of change, personalized/customized learning, platforms, professional development, reinvent, universities, user experience (UX), using teams, vendors, by Daniel Christian

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 [Pisani]

On 11/03/2018, in Amazon, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, computer science, programming, society, student-related, youth, by Daniel Christian

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 [Ekstein]

On 11/03/2018, in analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, computer science, data related items, emerging technologies, future, geography / geology, Google, innovation, society, by Daniel Christian

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 (& Algorithms) Rule [Young]

On 10/26/2018, in 21st century, analytics, Artificial Intelligence/Agents/LLMs/and Related, Blockchain, business side of he, change, changing business models, colleges, community colleges, education technology, emerging technologies, face-to-face, faculty, future, future of higher education, game-changing environment, innovation, Learning from the Living [Class] Room, lifelong learning, microlearning, New "Amazon.com" of Higher Education, online learning, personalized/customized learning, platforms, reinvent, staying relevant, streams of content, surviving, tools, ubiquitous learning, UK, universities, user experience (UX), vision/possibilities, by Daniel Christian

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. “

Gartner: Immersive experiences among top tech trends for 2019 [Schaffhauser]

On 10/23/2018, in 21st century, A/V -- audio/visual, analytics, Artificial Intelligence/Agents/LLMs/and Related, Augmented Reality (AR), Blockchain, bots, business, career development, change, cloud-based computing / apps / other cloud-related, computer science, corporate / business world, data related items, emerging technologies, ethics, future, human-computer interaction (HCI), ideas, immersion, innovation, intelligent systems, interaction design, machine-to-machine communications, Mixed Reality (MR), morals/values, Natural Language Processing (NLP), platforms, programming, smart classrooms, society, strategy, technology (general), tools, trends, usability, user experience (UX), vendors, Virtual Reality (VR) / worlds / learning, voice recognition / voice enabled interfaces, workplace, XR - extended reality, by Daniel Christian

Gartner: Immersive experiences among top tech trends for 2019 — from campustechnology.com by Dian Schaffhauser

Excerpt:

IT analyst firm Gartner has named its top 10 trends for 2019, and the “immersive user experience” is on the list, alongside blockchain, quantum computing and seven other drivers influencing how we interact with the world. The annual trend list covers breakout tech with broad impact and tech that could reach a tipping point in the near future.

Reflections on “Inside Amazon’s artificial intelligence flywheel” [Levy]

On 10/19/2018, in 21st century, 24x7x365 access, A/V -- audio/visual, Amazon, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, colleges, communities of practice, community colleges, competency-based learning/education, computer science, content development, aggregation, repositories, corporate / business world, cost of getting a degree, dangers of the status quo, Daniel S. Christian, data related items, digital learning, disruption, distance education, e-books, e-publishing related items (EPUB and more), e-readers, education, education reform, education technology, educational games / serious games, elearning, emerging technologies, engagement / engaging students, entrepreneurship, experimentation, future, future of higher education, game-changing environment, generational differences, global / globalization, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, interactivity, internet, K-12 related, law schools, learner profiles, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, library / librarians, lifelong learning, microlearning, mobile learning, MOOCs -- Massive Open Online Courses, more voice more choice more control, multimedia, Natural Language Processing (NLP), New "Amazon.com" of Higher Education, new business models, online learning, online media, online tutoring, personalized/customized learning, platforms, reinvent, second screen apps, social learning / networks, society, staying relevant, streams of content, student-related, surviving, teaching online, technologies for your home, tools, training / L&D, trends, United States, universities, usability, user experience (UX), vision/possibilities, voice recognition / voice enabled interfaces, workplace, by Daniel Christian

Inside Amazon’s artificial intelligence flywheel — from wired.com by Steven Levy
How deep learning came to power Alexa, Amazon Web Services, and nearly every other division of the company.

Excerpt (emphasis DSC):

Amazon loves to use the word flywheel to describe how various parts of its massive business work as a single perpetual motion machine. It now has a powerful AI flywheel, where machine-learning innovations in one part of the company fuel the efforts of other teams, who in turn can build products or offer services to affect other groups, or even the company at large. Offering its machine-learning platforms to outsiders as a paid service makes the effort itself profitable—and in certain cases scoops up yet more data to level up the technology even more.

It took a lot of six-pagers to transform Amazon from a deep-learning wannabe into a formidable power. The results of this transformation can be seen throughout the company—including in a recommendations system that now runs on a totally new machine-learning infrastructure. Amazon is smarter in suggesting what you should read next, what items you should add to your shopping list, and what movie you might want to watch tonight. And this year Thirumalai started a new job, heading Amazon search, where he intends to use deep learning in every aspect of the service.

“If you asked me seven or eight years ago how big a force Amazon was in AI, I would have said, ‘They aren’t,’” says Pedro Domingos, a top computer science professor at the University of Washington. “But they have really come on aggressively. Now they are becoming a force.”

Maybe the force.

From DSC:
When will we begin to see more mainstream recommendation engines for learning-based materials? With the demand for people to reinvent themselves, such a next generation learning platform can’t come soon enough!

Turning over control to learners to create/enhance their own web-based learner profiles; and allowing people to say who can access their learning profiles.
AI-based recommendation engines to help people identify curated, effective digital playlists for what they want to learn about.
Voice-driven interfaces.
Matching employees to employers.
Matching one’s learning preferences (not styles) with the content being presented as one piece of a personalized learning experience.
From cradle to grave. Lifelong learning.
Multimedia-based, interactive content.
Asynchronously and synchronously connecting with others learning about the same content.
Online-based tutoring/assistance; remote assistance.
Reinvent. Staying relevant. Surviving.
Competency-based learning.

We’re about to embark on a period in American history where career reinvention will be critical, perhaps more so than it’s ever been before. In the next decade, as many as 50 million American workers—a third of the total—will need to change careers, according to McKinsey Global Institute. Automation, in the form of AI (artificial intelligence) and RPA (robotic process automation), is the primary driver. McKinsey observes: “There are few precedents in which societies have successfully retrained such large numbers of people.”

Bill Triant and Ryan Craig

Also relevant/see:

Online education’s expansion continues in higher ed with a focus on tech skills — from educationdive.com by James Paterson

Dive Brief:

Online learning continues to expand in higher ed with the addition of several online master’s degrees and a new for-profit college that offers a hybrid of vocational training and liberal arts curriculum online.
Inside Higher Ed reported the nonprofit learning provider edX is offering nine master’s degrees through five U.S. universities — the Georgia Institute of Technology, the University of Texas at Austin, Indiana University, Arizona State University and the University of California, San Diego. The programs include cybersecurity, data science, analytics, computer science and marketing, and they cost from around $10,000 to $22,000. Most offer stackable certificates, helping students who change their educational trajectory.
Former Harvard University Dean of Social Science Stephen Kosslyn, meanwhile, will open Foundry College in January. The for-profit, two-year program targets adult learners who want to upskill, and it includes training in soft skills such as critical thinking and problem solving. Students will pay about $1,000 per course, though the college is waiving tuition for its first cohort.

AI Forces Shaping Work & Learning in 2030 [IFTF and Lumina Foundation]

On 10/18/2018, in 21st century, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, career development, change, changing business models, colleges, community colleges, competency-based learning/education, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, future, future of higher education, game-changing environment, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, K-12 related, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, lifelong learning, New "Amazon.com" of Higher Education, personalized/customized learning, platforms, programming, society, staying relevant, student-related, technologies for your home, technology (general), tools, training / L&D, trends, United States, universities, vendors, vision/possibilities, by Daniel Christian

In the 2030 and beyond world, employers will no longer be a separate entity from the education establishment. Pressures from both the supply and demand side are so large that employers and learners will end up, by default, co-designing new learning experiences, where all learning counts.

OBJECTIVES FOR CONVENINGS

Identify the skills everyone will need to navigate the changing relationship between machine intelligence and people over the next 10-12 years.
Develop implications for work, workers, students, working learners, employers, and policymakers.
Identify a preliminary set of actions that need to be taken now to best prepare for the changing work + learn ecosystem.

Three key questions guided the discussions:

What are the LEAST and MOST essential skills needed for the future?
Where and how will tomorrow’s workers and learners acquire the skills they really need?
Who is accountable for making sure individuals can thrive in this new economy?

This report summarizes the experts’ views on what skills will likely be needed to navigate the work + learn ecosystem over the next 10–15 years—and their suggested steps for better serving the nation’s future needs.

In a new world of work, driven especially by AI, institutionally-sanctioned curricula could give way to AI-personalized learning. This would drastically change the nature of existing social contracts between employers and employees, teachers and students, and governments and citizens. Traditional social contracts would need to be renegotiated or revamped entirely. In the process, institutional assessment and evaluation could well shift from top-down to new bottom-up tools and processes for developing capacities, valuing skills, and managing performance through new kinds of reputation or accomplishment scores.

…

In October 2017, Chris Wanstrath, CEO of Github, the foremost code-sharing and social networking resource for programmers today, made a bold statement: “The future of coding is no coding at all.” He believes that the writing of code will be automated in the near future, leaving humans to focus on “higher-level strategy and design of software.” Many of the experts at the convenings agreed. Even creating the AI systems of tomorrow, they asserted, will likely require less human coding than is needed today, with graphic interfaces turning AI programming into a drag-and-drop operation.

Digital fluency does not mean knowing coding languages. Experts at both convenings contended that effectively “befriending the machine” will be less about teaching people to code and more about being able to empathize with AIs and machines, understanding how they “see the world” and “think” and “make decisions.” Machines will create languages to talk to one another.

…

Here’s a list of many skills the experts do not expect to see much of—if at all—in the future:

Coding. Systems will be self-programming.
Building AI systems. Graphic interfaces will turn AI programming into drag-and-drop operations.
Calendaring, scheduling, and organizing. There won’t be need for email triage.
Planning and even decision-making. AI assistants will pick this up.
Creating more personalized curricula. Learners may design more of their own personalized learning adventure.
Writing and reviewing resumes. Digital portfolios, personal branding, and performance reputation will replace resumes.
Language translation and localization. This will happen in real time using translator apps.
Legal research and writing. Many of our legal systems will be automated.
Validation skills. Machines will check people’s work to validate their skills.
Driving. Driverless vehicles will replace the need to learn how to drive.

Here’s a list of the most essential skills needed for the future:

Quantitative and algorithmic thinking.
Managing reputation.
Storytelling and interpretive skills.
First principles thinking.
Communicating with machines as machines.
Augmenting high-skilled physical tasks with AI.
Optimization and debugging frame of mind.
Creativity and growth mindset.
Adaptability.
Emotional intelligence.
Truth seeking.
Cybersecurity.

The rise of machine intelligence is just one of the many powerful social, technological, economic, environmental, and political forces that are rapidly and disruptively changing the way everyone will work and learn in the future. Because this largely tech-driven force is so interconnected with other drivers of change, it is nearly impossible to understand the impact of intelligent agents on how we will work and learn without also imagining the ways in which these new tools will reshape how we live.

AI Now Law and Policy Reading List [AI Now Institute]

On 10/17/2018, in 21st century, analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, data related items, emerging technologies, law schools, legislatures / government / legal, policy, by Daniel Christian

AI Now Law and Policy Reading List — from medium.com by the AI Now Institute

Excerpt:

Data-driven technologies are widely used in society to make decisions that affect many critical aspects of our lives, from health, education, employment, and criminal justice to economic, social and political norms. Their varied applications, uses, and consequences raise a number of unique and complex legal and policy concerns. As a result, it can be hard to figure out not only how these systems work but what to do about them.

As a starting point, AI Now offers this Law and Policy Reading List tailored for those interested in learning about key concepts, debates, and leading analysis on law and policy issues related to artificial intelligence and other emerging data-driven technologies.

New game lets players train AI to spot legal issues [Tashea]

On 10/17/2018, in analytics, Artificial Intelligence/Agents/LLMs/and Related, bots, computer science, design, ideas, innovation, law schools, legislatures / government / legal, by Daniel Christian

New game lets players train AI to spot legal issues — from abajournal.com by Jason Tashea

Excerpt:

Got a free minute? There’s a new game that will help train an artificial intelligence model to spot legal issues and help close the access-to-justice gap.

Called Learned Hands—yes, it’s a pun—the game takes 75,000 legal questions posted on Reddit dealing with family, consumer, criminal and other legal issues and asks the user to determine what the issue is.

While conjuring up nightmares of the first-year in law school for many lawyers, David Colarusso says it’s for a good cause.

“It’s an opportunity for attorneys to take their downtime to train machine learning algorithms to help access-to-justice issues,” says Colarusso, director of Suffolk University Law School’s Legal Innovation and Technology (LIT) Lab and partner on this project with the Stanford Legal Design Lab.

From learnedhands.law.stanford.edu/legalIssues

When you play the game, you’ll be spotting if different legal issues are present in people’s stories. Some of these issues will be high level categories, and others will be more specific issues.

Here are the high level categories:

Learning Ecosystems

Top six AI and automation trends for 2019 [Newman]

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