intelligent systems

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.

AI Now Report 2018: 10 Recommendations for AI [AI Now Institute]

On 12/07/2018, in 21st century, Amazon, Apple, Artificial Intelligence/Agents/LLMs/and Related, bots, business, career development, change, colleges, community colleges, computer science, corporate / business world, emerging technologies, ethics, Facebook / Meta Platforms, future, game-changing environment, Google, higher education, human-computer interaction (HCI), IBM, ideas, innovation, intelligent systems, internet, law schools, legislatures / government / legal, machine-to-machine communications, Microsoft, morals/values, pace of change, platforms, programming, society, sociology, surviving, technologies for your home, technology (general), the downsides of how people use tech, tools, trends, United States, universities, vendors, vision/possibilities, workplace, by Daniel Christian

AI Now Report 2018 | December 2018 — from ainowinstitute.org

Meredith Whittaker , AI Now Institute, New York University, Google Open Research
Kate Crawford , AI Now Institute, New York University, Microsoft Research
Roel Dobbe , AI Now Institute, New York University
Genevieve Fried , AI Now Institute, New York University
Elizabeth Kaziunas , AI Now Institute, New York University
Varoon Mathur , AI Now Institute, New York University
Sarah Myers West , AI Now Institute, New York University
Rashida Richardson , AI Now Institute, New York University
Jason Schultz , AI Now Institute, New York University School of Law
Oscar Schwartz , AI Now Institute, New York University

With research assistance from Alex Campolo and Gretchen Krueger (AI Now Institute, New York University)

Excerpt (emphasis DSC):

Building on our 2016 and 2017 reports, the AI Now 2018 Report contends with this central problem, and provides 10 practical recommendations that can help create accountability frameworks capable of governing these powerful technologies.

Governments need to regulate AI by expanding the powers of sector-specific agencies to oversee, audit, and monitor these technologies by domain.
Facial recognition and affect recognition need stringent regulation to protect the public interest.
The AI industry urgently needs new approaches to governance. As this report demonstrates, internal governance structures at most technology companies are failing to ensure accountability for AI systems.
AI companies should waive trade secrecy and other legal claims that stand in the way of accountability in the public sector.
Technology companies should provide protections for conscientious objectors, employee organizing, and ethical whistleblowers.
Consumer protection agencies should apply “truth-in-advertising” laws to AI products and services.
Technology companies must go beyond the “pipeline model” and commit to addressing the practices of exclusion and discrimination in their workplaces.
Fairness, accountability, and transparency in AI require a detailed account of the “full stack supply chain.”
More funding and support are needed for litigation, labor organizing, and community participation on AI accountability issues.
University AI programs should expand beyond computer science and engineering disciplines. AI began as an interdisciplinary field, but over the decades has narrowed to become a technical discipline. With the increasing application of AI systems to social domains, it needs to expand its disciplinary orientation. That means centering forms of expertise from the social and humanistic disciplines. AI efforts that genuinely wish to address social implications cannot stay solely within computer science and engineering departments, where faculty and students are not trained to research the social world. Expanding the disciplinary orientation of AI research will ensure deeper attention to social contexts, and more focus on potential hazards when these systems are applied to human populations.

Also see:

After a Year of Tech Scandals, Our 10 Recommendations for AI — from medium.com by the AI Now Institute
Let’s begin with better regulation, protecting workers, and applying “truth in advertising” rules to AI

Also see:

Excerpt:

As we discussed, this technology brings important and even exciting societal benefits but also the potential for abuse. We noted the need for broader study and discussion of these issues. In the ensuing months, we’ve been pursuing these issues further, talking with technologists, companies, civil society groups, academics and public officials around the world. We’ve learned more and tested new ideas. Based on this work, we believe it’s important to move beyond study and discussion. The time for action has arrived.

We believe it’s important for governments in 2019 to start adopting laws to regulate this technology. The facial recognition genie, so to speak, is just emerging from the bottle. Unless we act, we risk waking up five years from now to find that facial recognition services have spread in ways that exacerbate societal issues. By that time, these challenges will be much more difficult to bottle back up.

In particular, we don’t believe that the world will be best served by a commercial race to the bottom, with tech companies forced to choose between social responsibility and market success. We believe that the only way to protect against this race to the bottom is to build a floor of responsibility that supports healthy market competition. And a solid floor requires that we ensure that this technology, and the organizations that develop and use it, are governed by the rule of law.

From DSC:
This is a major heads up to the American Bar Association (ABA), law schools, governments, legislatures around the country, the courts, the corporate world, as well as for colleges, universities, and community colleges. The pace of emerging technologies is much faster than society’s ability to deal with them!

The ABA and law schools need to majorly pick up their pace — for the benefit of all within our society.

This type of functionality from Chegg will likely be a piece of a next gen learning platform

On 12/06/2018, in 21st century, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, community colleges, education technology, emerging technologies, faculty, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learner profiles, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning preferences, mathematics, online learning, personalized/customized learning, platforms, productivity / tips and tricks, smart/connected TV, student teaching/teacher education, student-related, teachers, teaching & learning, teaching online, technologies for your home, tools, universities, usability, user experience (UX), vendors, by Daniel Christian

The information below is from Heather Campbell at Chegg
(emphasis DSC)

Chegg Math Solver is an AI-driven tool to help the student understand math. It is more than just a calculator – it explains the approach to solving the problem. So, students won’t just copy the answer but understand and can solve similar problems at the same time. Most importantly,students can dig deeper into a problem and see why it’s solved that way. Chegg Math Solver.

In every subject, there are many key concepts and terms that are crucial for students to know and understand. Often it can be hard to determine what the most important concepts and terms are for a given subject, and even once you’ve identified them you still need to understand what they mean. To help you learn and understand these terms and concepts, we’ve provided thousands of definitions, written and compiled by Chegg experts. Chegg Definition.

From DSC:
I see this type of functionality as a piece of a next generation learning platform — a piece of the Living from the Living [Class] Room type of vision. Great work here by Chegg!

Likely, students will also be able to take pictures of their homework, submit it online, and have that image/problem analyzed for correctness and/or where things went wrong with it.

From Dimitri Hommel’s posting on Twitter

Also see:

Amazon is beefing up Amazon Web Services’ IoT — from businessinsider.com by Peter Newman
As Digital Technology Pervades The Utility Industry So Too Does The Risk Of Cyber Attacks — from which-50.com by Joseph Brookes

10 predictions for tech in 2019 — from enterprisersproject.com by Carla Rudder
IT leaders look at the road ahead and predict what’s next for containers, security, blockchain, and more

Excerpts:

We asked IT leaders and tech experts what they see on the horizon for the future of technology. We intentionally left the question open-ended, and as a result, the answers represent a broad range of what IT professionals may expect to face in the new year. Let’s dig in…

3. Security becomes must-have developer skill.
Developers who have job interviews next year will see a new question added to the usual list.

5. Ethics take center stage with tech talent
Robert Reeves, CTO and co-founder, Datical: “More companies (prompted by their employees) will become increasingly concerned about the ethics of their technology. Microsoft is raising concerns of the dangers of facial recognition technology; Google employees are very concerned about their AI products being used by the Department of Defense. The economy is good for tech right now and the job market is becoming tighter. Thus, I expect those companies to take their employees’ concerns very seriously. Of course, all bets are off when (not if) we dip into a recession. But, for 2019, be prepared for more employees of tech giants to raise ethical concerns and for those concerns to be taken seriously and addressed.”’

7. Customers expect instant satisfaction
“All customers will be the customer of ‘now,’ with expectations of immediate and personalized service; single-click approval for loans, sales quotes on the spot, and deliveries in hours instead of days. The window of opportunity for customer satisfaction will keep closing and technology will evolve to keep pace. Real-time analytics will become faster and smarter as data that is external to the organization, such as social, news and weather, will be included for more insights. The move to the cloud will accelerate with the growing adoption of open-source vendors.”

From DSC:
Regarding #7 above…as the years progress, how do you suppose this type of environment where people expect instant satisfaction and personalized service will impact education/training?

Mama Mia It’s Sophia: A Show Robot Or Dangerous Platform To Mislead? — from forbes.com by Noel Sharkey

Excerpts:

A collective eyebrow was raised by the AI and robotics community when the robot Sophia was given Saudia citizenship in 2017 The AI sharks were already circling as Sophia’s fame spread with worldwide media attention. Were they just jealous buzz-kills or is something deeper going on? Sophia has gripped the public imagination with its interesting and fun appearances on TV and on high-profile conference platforms.

Sophia is not the first show robot to attain celebrity status. Yet accusations of hype and deception have proliferated about the misrepresentation of AI to public and policymakers alike. In an AI-hungry world where decisions about the application of the technologies will impact significantly on our lives, Sophia’s creators may have crossed a line. What might the negative consequences be? To get answers, we need to place Sophia in the context of earlier show robots.

A dangerous path for our rights and security
For me, the biggest problem with the hype surrounding Sophia is that we have entered a critical moment in the history of AI where informed decisions need to be made. AI is sweeping through the business world and being delegated decisions that impact significantly on peoples lives from mortgage and loan applications to job interviews, to prison sentences and bail guidance, to transport and delivery services to medicine and care.

It is vitally important that our governments and policymakers are strongly grounded in the reality of AI at this time and are not misled by hype, speculation, and fantasy. It is not clear how much the Hanson Robotics team are aware of the dangers that they are creating by appearing on international platforms with government ministers and policymakers in the audience.

Frey: “…by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet.”

On 11/14/2018, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, bots, colleges, community colleges, cost of getting a degree, Daniel S. Christian, digital learning, education, education reform, education technology, emerging technologies, face-to-face, future, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, intelligent systems, intelligent tutoring, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, MOOCs -- Massive Open Online Courses, more voice more choice more control, online learning, online tutoring, personalized/customized learning, platforms, universities, by Daniel Christian

From DSC:
I agree with futurist Thomas Frey:

“I’ve been predicting that by 2030 the largest company on the internet is going to be an education-based company that we haven’t heard of yet.”

(source)

Along these lines, see what Arizona State University is up to:

We think of this as a transformation away from a mass-production model to a mass-personalization model. For us, that’s the big win in this whole process. When we move away from the large lectures in that mass-production model that we’ve used for the last 170 years and get into something that reflects each of the individual learners’ needs and can personalize their learning path through the instructional resources, we will have successfully moved the education industry to the new frontier in the learning process. We think that mass personalization has already permeated every aspect of our lives, from navigation to entertainment; and education is really the next big frontier.

(source)

From DSC:
Each year the vision I outlined here gets closer and closer and closer and closer. With the advancements in Artificial Intelligence (AI), change is on the horizon…big time. Mass personalization. More choice. More control.

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.

“The global companies that failed to adapt to change.” [Rao] | DC: Higher ed likely has something to learn here.

On 11/05/2018, in 21st century, 24x7x365 access, active learning, Artificial Intelligence/Agents/LLMs/and Related, bots, business side of he, colleges, community colleges, corporate / business world, cost of getting a degree, dangers of the status quo, Daniel S. Christian, future, future of higher education, game-changing environment, global / globalization, ideas, innovation, intelligent systems, internet, law schools, leadership, learning, learning ecosystem, Learning from the Living [Class] Room, MBA, New "Amazon.com" of Higher Education, new business models, organizational change, pace of change, reinvent, society, staying relevant, strategy, student-related, surviving, training / L&D, universities, vendors, vision/possibilities, workplace, by Daniel Christian

The global companies that failed to adapt to change. — from trainingmag.com by Professor M.S. Rao, Ph.D.

Excerpt:

Eastman Kodak, a leader for many years, filed for bankruptcy in 2012. Blockbuster Video became defunct in 2013. Similarly, Borders — one of the largest book retailers in the U.S. — went out of business in 2011. Why did these companies, which once had great brands, ultimately fail? It is because they failed to adapt to change. Additionally, they failed to unlearn and relearn.
…
Former GE CEO Jack Welch once remarked, “If the rate of change on the outside exceeds the rate of change on the inside, the end is near.” Thus, accept change before the change is thrust on you.
…
Leaders must adopt tools and techniques to adapt to change. Here is a blueprint to embrace change effectively:

Keep the vision right and straight, and articulate it effectively.
Create organizational culture conducive to bring about change.
Communicate clearly about the need to change.
Enlighten people about the implications of the status quo.
Show them benefits once the change is implemented.
Coordinate all stakeholders effectively.
Remove the roadblocks by allaying their apprehensions.
Show them small gains to ensure that entire change takes place smoothly without any resistance.

From DSC:
Though I’m not on board with all of the perspectives in that article, institutions of traditional higher education likely have something to learn from the failures of these companies….while there’s still time to change and to innovate.

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.

“Affordable and at-scale” [Schroeder] + “Trends for the future of education with Jeff Selingo” [Steelcase]

On 10/31/2018, in 21st century, 24x7x365 access, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assistive technologies, business side of he, career development, change, colleges, communities of practice, community colleges, computer science, cost of getting a degree, dangers of the status quo, digital learning, disruption, distance education, education, education reform, education technology, emerging technologies, face-to-face, future, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, intelligent systems, intelligent tutoring, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning spaces, lifelong learning, MOOCs -- Massive Open Online Courses, New "Amazon.com" of Higher Education, new business models, online learning, United States, universities, vendors, vision/possibilities, web-based collaboration, by Daniel Christian

Affordable and at-scale — from insidehighered.com by Ray Schroeder
Affordable degrees at scale have arrived. The momentum behind this movement is undeniable, and its impact will be significant, Ray Schroeder writes.

Excerpt (emphasis DSC):

How many times have we been told that major change in our field is on the near horizon? Too many times, indeed.

The promises of technologies and practices have fallen short more often than not. Just seven years ago, I was part of the early MOOC movement and felt the pulsating potential of teaching thousands of students around the world in a single class. The “year of the MOOC” was declared in 2012. Three years later, skeptics declared that the MOOC had died an ignominious death with high “failure” rates and relatively little recognition by employers.

However, the skeptics were too impatient, misunderstood the nature of MOOCs and lacked the vision of those at Georgia Tech, the University of Illinois, Arizona State University, Coursera, edX and scores of other institutions that have persevered in building upon MOOCs’ premises to develop high-quality, affordable courses, certificates and now, degrees at scale.

No, these degrees are not free, but they are less than half the cost of on-campus versions. No, they are not massive in the hundreds of thousands, but they are certainly at large scale with many thousands enrolled. In computer science, the success is felt across the country.

Georgia Tech alone has enrolled 10,000 students over all in its online master’s program and is adding thousands of new students each semester in a top 10-ranked degree program costing less than $7,000. Georgia Tech broke the new ground through building collaborations among several partners. Yet, that was just the beginning, and many leading universities have followed.

Also see:

Trends for the future of education with Jeff Selingo — from steelcase.com
How the future of work and new technology will make place more important than ever.

Excerpt:

Selingo sees artificial intelligence and big data as game changers for higher education. He says AI can free up professors and advisors to spend more time with students by answering some more frequently-asked questions and handling some of the grading. He also says data can help us track and predict student performance to help them create better outcomes. “When they come in as a first-year student, we can say ‘People who came in like you that had similar high school grades and took similar classes ended up here. So, if you want to get out of here in four years and have a successful career, here are the different pathways you should follow.’”

Should self-driving cars have ethics? [Wamsley]

On 10/31/2018, in Artificial Intelligence/Agents/LLMs/and Related, bots, data related items, emerging technologies, ethics, innovation, intelligent systems, morals/values, pace of change, platforms, society, by Daniel Christian

Should self-driving cars have ethics? — from npr.org by Laurel Wamsley

Excerpt:

In the not-too-distant future, fully autonomous vehicles will drive our streets. These cars will need to make split-second decisions to avoid endangering human lives — both inside and outside of the vehicles.

To determine attitudes toward these decisions a group of researchers created a variation on the classic philosophical exercise known as “the Trolley problem.” They posed a series of moral dilemmas involving a self-driving car with brakes that suddenly give out…

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.

Learning Ecosystems

Infographic on the Internet of Things (IoT); Amazon is beefing up Amazon Web Services’ IoT

Categories

Tags