Artificial Intelligence/Agents/LLMs/and Related

I’m not sure I like these Applicant Tracking Systems (ATS); on your next job search, you might not either. [Christian]

On 08/21/2017, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, business, career development, competency-based learning/education, Daniel S. Christian, data related items, ethics, Google, ideas, morals/values, society, student-related, the downsides of how people use tech, workplace, by Daniel Christian

From DSC:
I’ve been thinking about Applicant Tracking Systems (ATSs) for a while now, but the article below made me revisit my reflections on them. (By the way, my thoughts below are not meant to be a slam on Google. I like Google and I use their tools daily.) I’ve included a few items below, but there were some other articles/vendors’ products that I had seen on this topic that focused specifically on ATSs, but I couldn’t locate them all.

How Google’s AI-Powered Job Search Will Impact Companies And Job Seekers — from forbes.com by Forbes Coaches Council

Excerpt:

In mid-June, Google announced the implementation of an AI-powered search function aimed at connecting job seekers with jobs by sorting through posted recruitment information. The system allows users to search for basic phrases, such as “jobs near me,” or perform searches for industry-specific keywords. The search results can include reviews from Glassdoor or other companies, along with the details of what skills the hiring company is looking to acquire.

As this is a relatively new development, what the system will mean is still an open question. To help, members from the Forbes Coaches Council offer their analysis on how the search system will impact candidates or companies. Here’s what they said…

5. Expect competition to increase.
Google jumping into the job search market may make it easier than ever to apply for a role online. For companies, this could likely tax the already strained-ATS system, and unless fixed, could mean many more resumes falling into that “black hole.” For candidates, competition might be steeper than ever, which means networking will be even more important to job search success. – Virginia Franco

10. Understanding keywords and trending topics will be essential.
Since Google’s AI is based on crowd-gathered metrics, the importance of keywords and understanding trending topics is essential for both employers and candidates. Standing out from the crowd or getting relevant results will be determined by how well you speak the expected language of the AI. Optimizing for the search engine’s results pages will make or break your search for a job or candidate. – Maurice Evans, IGROWyourBiz, Inc

Also see:

In Unilever’s radical hiring experiment, resumes are out, algorithms are in — from foxbusiness.com by Kelsey Gee Pu

Excerpt:

Before then, 21-year-old Ms. Jaffer had filled out a job application, played a set of online games and submitted videos of herself responding to questions about how she’d tackle challenges of the job. The reason she found herself in front of a hiring manager? A series of algorithms recommended her.

The Future of HR: Is it Dying? — from hrtechnologist.com by Rhucha Kulkarni

Excerpt (emphasis DSC):

The debate is on, whether man or machine will win the race, as they are pitted against each other in every walk of life. Experts are already worried about the social disruption that is inevitable, as artificial intelligence (AI)-led robots take over the jobs of human beings, leaving them without livelihoods. The same is believed to happen to the HR profession, says a report by Career Builder. HR jobs are at threat, like all other jobs out there, as we can expect certain roles in talent acquisition, talent management, and mainstream business being automated over the next 10 years. To delve deeper into the imminent problem, Career Builder carried out a study of 719 HR professionals in the private sector, specifically looking for the rate of adoption of emerging technologies in HR and what HR professionals perceived about it.

The change is happening for real, though different companies are adopting technologies at varied paces. Most companies are turning to the new-age technologies to help carry out talent acquisition and management tasks that are time-consuming and labor-intensive.

From DSC:
Are you aware that if you apply for a job at many organizations nowadays, your resume has a significant chance of not ever making it in front of a human’s eyeballs for their review? Were you aware that an Applicant Tracking System (an ATS) will likely syphon off and filter out your resume unless you have the exact right keywords in your resume and unless you mentioned those keywords the optimal number of times?

And were you aware that many advisors assert that you should use a 1 page resume — a 2 page resume at most? Well…assuming that you have to edit big time to get to a 1-2 page resume, how does that editing help you get past the ATSs out there? When you significantly reduce your resume’s size/information, you hack out numerous words that the ATS may be scanning for. (BTW, advisors recommend creating a Wordle from the job description to ascertain the likely keywords; but still, you don’t know which exact keywords the ATS will be looking for in your specific case/job application and how many times to use those keywords. Numerous words can be of similar size in the resulting Wordle graphic…so is that 1-2 page resume helping you or hurting you when you can only submit 1 resume for a position/organization?)

Vendors are hailing these ATS systems as being major productivity boosters for their HR departments…and that might be true in some cases. But my question is, at what cost?

At this point in time, I still believe that humans are better than software/algorithms at making judgement calls. Perhaps I’m giving hiring managers too much credit, but I’d rather have a human being make the call at this point. I want a pair of human eyeballs to scan my resume, not a (potentially) narrowly defined algorithm. A human being might see transferable skills better than a piece of code at this point.

Just so you know…in light of these keyword-based means of passing through the first layer of filtering, people are now playing games with their resumes and are often stretching the truth — if not outright lying:

85 Percent of Job Applicants Lie on Resumes. Here’s How to Spot a Dishonest Candidate — from inc.com by J.T. O’Donnell

A new study shows huge increase in lies on job applications.

Excerpt (emphasis DSC):

Employer Applicant Tracking Systems Expect an Exact Match
Most companies use some form of applicant tracking system (ATS) to take in résumés, sort through them, and narrow down the applicant pool. With the average job posting getting more than 100 applicants, recruiters don’t want to go bleary-eyed sorting through them. Instead, they let the ATS do the dirty work by telling it to pass along only the résumés that match their specific requirements for things like college degrees, years of experience, and salary expectations. The result? Job seekers have gotten wise to the finicky nature of the technology and are lying on their résumés and applications in hopes of making the cut.

From DSC:
I don’t see this as being very helpful. But perhaps that’s because I don’t like playing games with people and/or with other organizations. I’m not a game player. What you see is what you get. I’ll be honest and transparent about what I can — and can’t — deliver.

But students, you should know that these ATS systems are in place. Those of us in higher education should know about these ATS systems, as many of us are being negatively impacted by the current landscape within higher education.

Also see:

Why Your Approach To Job Searching Is Failing — from forbes.com by Jeanna McGinnis

Excerpt:

Is Your Resume ATS Friendly?
Did you know that an ATS (applicant tracking system) will play a major role in whether or not your resume is selected for further review when you’re applying to opportunities through online job boards?

It’s true. When you apply to a position a company has posted online, a human usually isn’t the first to review your resume, a computer program is. Scouring your resume for keywords, terminology and phrases the hiring manager is targeting, the program will toss your resume if it can’t understand the content it’s reading. Basically, your resume doesn’t stand a chance of making it to the next level if it isn’t optimized for ATS.

To ensure your resume makes it past the evil eye of ATS, format your resume correctly for applicant tracking programs, target it to the opportunity and check for spelling errors. If you don’t, you’re wasting your time applying online.

Why Natural Language Processing is the Future of Business Intelligence — from dzone.com by Gur Tirosh
Until now, we have been interacting with computers in a way that they understand, rather than us. We have learned their language. But now, they’re learning ours.

Excerpt:

Every time you ask Siri for directions, a complex chain of cutting-edge code is activated. It allows “her” to understand your question, find the information you’re looking for, and respond to you in a language that you understand. This has only become possible in the last few years. Until now, we have been interacting with computers in a way that they understand, rather than us. We have learned their language.

But now, they’re learning ours.

The technology underpinning this revolution in human-computer relations is Natural Language Processing (NLP). And it’s already transforming BI, in ways that go far beyond simply making the interface easier. Before long, business transforming, life changing information will be discovered merely by talking with a chatbot.

This future is not far away. In some ways, it’s already here.

What Is Natural Language Processing?
NLP, otherwise known as computational linguistics, is the combination of Machine Learning, AI, and linguistics that allows us to talk to machines as if they were human.

But NLP aims to eventually render GUIs — even UIs — obsolete, so that interacting with a machine is as easy as talking to a human.

Chatbot “Bobbot” has driven 1000’s of potential leads, 10% increase in converting visitors to students

On 08/08/2017, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, business side of he, cloud-based computing / apps / other cloud-related, colleges, community colleges, emerging technologies, experimentation, Facebook / Meta Platforms, higher education, IBM, Natural Language Processing (NLP), student-related, tools, universities, vendors, by Daniel Christian

Codify Academy Taps IBM Cloud with Watson to Design Cognitive Chatbot — from finance.yahoo.com
Chatbot “Bobbot” has driven thousands of potential leads, 10 percent increase in converting visitors to students

Excerpt:

ARMONK, N.Y., Aug. 4, 2017 /PRNewswire/ — IBM (NYSE: IBM) today announced that Codify Academy, a San Francisco-based developer education startup, tapped into IBM Cloud’s cognitive services to create an interactive cognitive chatbot, Bobbot, that is improving student experiences and increasing enrollment.

Using the IBM Watson Conversation Service, Bobbot fields questions from prospective and current students in natural language via the company’s website. Since implementing the chatbot, Codify Academy has engaged thousands of potential leads through live conversation between the bot and site visitors, leading to a 10 percent increase in converting these visitors into students.

Bobbot can answer more than 200 common questions about enrollment, course and program details, tuition, and prerequisites, in turn enabling Codify Academy staff to focus on deeper, more meaningful exchanges.

Also see:

Chatbots — The Beginners Guide — from chatbotsmagazine.com

Excerpt:

If you search for chatbots on Google, you’ll probably come across hundreds of pages starting from what is a chatbot to how to build one. This is because we’re in 2017, the year of the chatbots revolution.

I’ve been introduced to many people who are new to this space, and who are very interested and motivated in entering it, rather they’re software developers, entrepreneurs, or just tech hobbyists. Entering this space for the first time, has become overwhelming in just a few months, particularly after Facebook announced the release of the messenger API at F8 developer conference. Due to this matter, I’ve decided to simplify the basic steps of entering this fascinating world.

Reflections on “Digital Ivy: Harvard Business School’s Next Online Program” [Corcoran]

On 08/08/2017, in Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, Daniel S. Christian, higher education, innovation, leadership, MBA, online learning, platforms, strategy, United States, universities, vendors, vision/possibilities, by Daniel Christian

Digital Ivy: Harvard Business School’s Next Online Program — from edsurge.com by Betsy Corcoran

Excerpts:

A triad of Harvard institutions—its business School, the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), and the department of statistics—are teaming up with Maryland-based digital education company, 2U, to offer an online executive education certificate in business analytics.
…
Orchestrating a cross-disciplinary program is no small feat, particularly at Harvard. “This was really hard [for Harvard] to pull off,” Paucek says. “It’s an intense, cross-disciplinary new offering from a school founded in 1636. The field is new, the offering of a complex blended certificate is new, and it’s being done with HBS, SEAS and the faculty, all blessed by the central administration. And it’s powered by an outside company that’s only 10 years old.”

The bottom line: HBS, Harvard SEAS and FAS faculty all want to put their imprint on the topic that is mesmerizing nearly every type of organization.

Also see:

Andrew Ng spreads the gospel of AI with a new online school — from wired.com by Tom Simonite

Excerpt:

Andrew Ng a soft-spoken AI researcher whose online postings talk loudly.

A March blog post in which the Stanford professor announced he was leaving Chinese search engine Baidu temporarily wiped more than a billion dollars off the company’s value. A June tweet about a new Ng website, Deeplearning.ai, triggered a wave of industry and media speculation about his next project.

Today that speculation is over. Deeplearning.ai is home to a series of online courses Ng says will help spread the benefits of recent advances in machine learning far beyond big tech companies such as Google and Baidu. The courses offers coders without an AI background training in how to use deep learning, the technique behind the current frenzy of investment in AI.

From DSC:
For those of you who shun online learning and think such programs will dilute your face-to-face based brands — whether individual colleges, universities, faculty members, provosts, deans, IT-based personnel, administrators, members of the board of trustees, and/or other leaders and strategists within higher education — you might want to intentionally consider what kind of future you have without a strong, solid online presence. Because if one of the top — arguably thee top — universities in the United States is moving forward forcefully with online learning, what’s your story/excuse?

And if one of the top thinkers in artificial intelligence backs online learning, again…what’s your story/excuse?

If Amazon.com dominates and Sears (and related retail stores who were powerhouses just years ago) are now closing…you are likely heading for major trouble as the world continues down the digital/virtual tracks — and you aren’t sending any (or very few) cars down those tracks. You won’t have any credibility in the future — at least not in the digital/virtual/online-based realms. Oh, and by the way, you might want to set some more funding aside for the mental and physical health of your admissions/enrollment teams in such situations…as their jobs are going to be increasingly stressful and difficult in order to meet their target numbers.

Also see:

Could Georgia Tech Use Online to Shave Time Off Bachelor’s Degrees? — from insidehighered.com by Mark Lieberman
University uses model from closely observed master’s in computer science on undergraduates for first time, finds notable success and sees path to shaving a year or more off in-person instruction.

Overall, tech-related skills accounted for nearly two-thirds of Upwork’s list of the 20 fastest-growing skills. [Gottlieb]

On 08/04/2017, in 21st century, A/V -- audio/visual, Adobe, Artificial Intelligence/Agents/LLMs/and Related, career development, CMS/LMS, computer science, economics, emerging technologies, Facebook / Meta Platforms, marketing/social marketing, Natural Language Processing (NLP), platforms, programming, tools, trends, Virtual Reality (VR) / worlds / learning, workplace, by Daniel Christian

VR Is the Fastest-Growing Skill for Online Freelancers — from bloomberg.com by Isabel Gottlieb
Workers who specialize in artificial intelligence also saw big jumps in demand for their expertise.

Excerpt:

Overall, tech-related skills accounted for nearly two-thirds of Upwork’s list of the 20 fastest-growing skills.

Also see:

How to Prepare Preschoolers for an Automated Economy — from nytimes.com by Claire Miller and Jess Bidgood

Excerpt

MEDFORD, Mass. — Amory Kahan, 7, wanted to know when it would be snack time. Harvey Borisy, 5, complained about a scrape on his elbow. And Declan Lewis, 8, was wondering why the two-wheeled wooden robot he was programming to do the Hokey Pokey wasn’t working. He sighed, “Forward, backward, and it stops.”

Declan tried it again, and this time the robot shook back and forth on the gray rug. “It did it!” he cried. Amanda Sullivan, a camp coordinator and a postdoctoral researcher in early childhood technology, smiled. “They’ve been debugging their Hokey Pokeys,” she said.

The children, at a summer camp last month run by the Developmental Technologies Research Group at Tufts University, were learning typical kid skills: building with blocks, taking turns, persevering through frustration. They were also, researchers say, learning the skills necessary to succeed in an automated economy.

Technological advances have rendered an increasing number of jobs obsolete in the last decade, and researchers say parts of most jobs will eventually be automated. What the labor market will look like when today’s young children are old enough to work is perhaps harder to predict than at any time in recent history. Jobs are likely to be very different, but we don’t know which will still exist, which will be done by machines and which new ones will be created.

155 chatbots in this brand new landscape. Where does your bot fit? [Chan]

On 08/03/2017, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, bots, business, corporate / business world, marketing/social marketing, tools, trends, vendors, workplace, by Daniel Christian

155 chatbots in this brand new landscape. Where does your bot fit? — from venturebeat.com by Carylyne Chan

Excerpt:

Since we started building bots at KeyReply more than two years ago, the industry has seen massive interest and change. This makes it hard for companies and customers to figure out what’s really happening — so we hope to throw some light on this industry by creating a landscape of chatbot-related businesses. There’s no way to put everyone into this landscape, so we have selected examples that give readers an overview of the industry, such as notable or dominant providers and tools widely used to develop bots.

To put everything into a coherent structure, we arranged companies along the axes according to the functions of their bots and how they built them.

On the horizontal axis, the “marketing” function refers to a bot’s ability to drive exposure, reach, and interaction with the brand or product for potential and current customers. The “support” function refers to a bot’s ability to assist current customers with problems and to resolve those problems for them.

On the vertical axis, “managed” refers to companies outsourcing the development of bots to external vendors, whereas “self-serve” refers to them building their bots in-house or with an off-the-shelf tool.

Report: AI will be in nearly all new software by 2020 [Bolkan]

On 08/02/2017, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, career development, change, computer science, emerging technologies, future, game-changing environment, pace of change, platforms, programming, strategy, user experience (UX), vendors, by Daniel Christian

Report: AI will be in nearly all new software by 2020 — from thejournal.com by Joshua Bolkan

Excerpt:

Artificial intelligence will be in nearly all new software products by 2020 and a top five investment priority for more than 30 percent of chief information officers, according to a new report from Gartner.
…
The company lists three keys to successfully exploiting AI technologies over the next few years:

Many vendors are “AI washing” their products, or applying the term artificial intelligence to tools that don’t really merit it. Vendors should use the term wisely and be clear about what differentiates their AI products and what problems they solve;
Forego more complicated or cutting-edge AI techniques in favor of simpler, proven approaches; and
Organizations do not have the skills to evaluate, build or deploy AI and are looking for embedded or packaged AI rather than custom building their own.

How SLAM technology is redrawing augmented reality’s battle lines [Tabatabaie]

On 08/01/2017, in 21st century, A/V -- audio/visual, Apple, Artificial Intelligence/Agents/LLMs/and Related, Augmented Reality (AR), education technology, emerging technologies, Facebook / Meta Platforms, Google, interaction design, interactivity, tools, trends, user experience (UX), by Daniel Christian

How SLAM technology is redrawing augmented reality’s battle lines — from venturebeat.com by Mojtaba Tabatabaie

Excerpt (emphasis DSC):

In early June, Apple introduced its first attempt to enter AR/VR space with ARKit. What makes ARKit stand out for Apple is a technology called SLAM (Simultaneous Localization And Mapping). Every tech giant — especially Apple, Google, and Facebook — is investing heavily in SLAM technology and whichever takes best advantage of SLAM tech will likely end up on top.

SLAM is a technology used in computer vision technologies which gets the visual data from the physical world in shape of points to make an understanding for the machine. SLAM makes it possible for machines to “have an eye and understand” what’s around them through visual input. What the machine sees with SLAM technology from a simple scene looks like the photo above, for example.

Using these points machines can have an understanding of their surroundings. Using this data also helps AR developers like myself to create much more interactive and realistic experiences. This understanding can be used in different scenarios like robotics, self-driving cars, AI and of course augmented reality.

The simplest form of understanding from this technology is recognizing walls and barriers and also floors. Right now most AR SLAM technologies like ARKit only use floor recognition and position tracking to place AR objects around you, so they don’t actually know what’s going on in your environment to correctly react to it. More advanced SLAM technologies like Google Tango, can create a mesh of our environment so not only the machine can tell you where the floor is, but it can also identify walls and objects in your environment allowing everything around you to be an element to interact with.

The company with the most complete SLAM database will likely be the winner. This database will allow these giants to have an eye on the world metaphorically, so, for example Facebook can tag and know the location of your photo by just analyzing the image or Google can place ads and virtual billboards around you by analyzing the camera feed from your smart glasses. Your self-driving car can navigate itself with nothing more than visual data.

2017 Ed Tech Trends: The Halfway Point [Aldridge, Christian, Kelly, Powell, & Ventimiglia]

On 07/31/2017, in 21st century, analytics, Artificial Intelligence/Agents/LLMs/and Related, Augmented Reality (AR), bots, change, Daniel S. Christian, data related items, digital learning, education technology, emerging technologies, future, future of higher education, game-changing environment, Google, higher education, human-computer interaction (HCI), ideas, innovation, intelligent systems, intelligent tutoring, leadership, learning, learning ecosystem, Learning from the Living [Class] Room, maker movement, robotics, society, student-related, tools, trends, universities, vendors, Virtual Reality (VR) / worlds / learning, vision/possibilities, by Daniel Christian

2017 Ed Tech Trends: The Halfway Point — from campustechnology.com by Rhea Kelly
Four higher ed IT leaders weigh in on the current state of education technology and what’s ahead.

This article includes some perspectives shared from the following 4 IT leaders:

Susan Aldridge, Senior Vice President for Online Learning, Drexel University (PA); President, Drexel University Online
Daniel Christian, Adjunct Faculty Member, Calvin College
Marci Powell, CEO/President, Marci Powell & Associates; Chair Emerita and Past President, United States Distance Learning Association
Phil Ventimiglia, Chief Innovation Officer, Georgia State University

Also see:

Higher ed forges ahead on immersive tech integration – from educationdive.com by Pat Donachie

From DSC:
Reviewing the article below made me think of 2 potential additions to the Learning & Development Groups/Departments out there:

Help people build their own learning ecosystems
Design, develop, and implement workbots for self-service

Chatbots Poised to Revolutionize HR — from by Pratibha Nanduri

Excerpt:

Self-service is becoming an increasingly popular trend where people want to perform their tasks without needing help or input from anyone else. The increasing popularity of this trend is mainly attributed to the increasing use of computers and mobile devices to electronically manage all kinds of tasks.

As employee tolerance for downtime reduces and preferences for mobility increases, the bureaucracy which exists in managing everyday HR related tasks in the workplace will also have to be replaced. A large number of companies have still not automated even their basic HR services such as handling inquiries about holidays and leaves. Employees in such organizations still have to send their query and then wait for HR to respond.

As the number of employees goes up in an organization, the time taken by HR managers to respond to mundane admin tasks also increases. This leaves very little time for the HR manager to focus on strategic HR initiatives.

Chatbots that are powered by AI and machine learning are increasingly being used to automate mundane and repetitive tasks. They can also be leveraged in HR to simulate intelligent SMS-based conversations between employees and HR team members to automate basic HR tasks.

Trying to develop a general AI illustrates that some serious glory & honor is due (again)

On 07/22/2017, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, bots, computer science, Daniel S. Christian, faith, Google, human-computer interaction (HCI), programming, by Daniel Christian

Google’s AI Guru Says That Great Artificial Intelligence Must Build on Neuroscience — from technologyreview.com by Jamie Condliffe
Inquisitiveness and imagination will be hard to create any other way.

Excerpt:

Demis Hassabis knows a thing or two about artificial intelligence: he founded the London-based AI startup DeepMind, which was purchased by Google for $650 million back in 2014. Since then, his company has wiped the floor with humans at the complex game of Go and begun making steps towards crafting more general AIs.

But now he’s come out and said that be believes the only way for artificial intelligence to realize its true potential is with a dose of inspiration from human intellect.

Currently, most AI systems are based on layers of mathematics that are only loosely inspired by the way the human brain works. But different types of machine learning, such as speech recognition or identifying objects in an image, require different mathematical structures, and the resulting algorithms are only able to perform very specific tasks.

Building AI that can perform general tasks, rather than niche ones, is a long-held desire in the world of machine learning. But the truth is that expanding those specialized algorithms to something more versatile remains an incredibly difficult problem, in part because human traits like inquisitiveness, imagination, and memory don’t exist or are only in their infancy in the world of AI.

First, they say, better understanding of how the brain works will allow us to create new structures and algorithms for electronic intelligence.

From DSC:
Glory to God! I find it very interesting to see how people and organizations — via very significant costs/investments — keep trying to mimic the most amazing thing — the human mind. Turns out, that’s not so easy:

But the truth is that expanding those specialized algorithms to something more versatile remains an incredibly difficult problem…

Therefore, some scripture comes to my own mind here:

Psalm 139:14 New International Version (NIV)

¹⁴I praise you because I am fearfully and wonderfully made;
your works are wonderful,
I know that full well.

Job 12:13 (NIV)

¹³“To God belong wisdom and power;
counsel and understanding are his.

Psalm 104:24 (NIV)

²⁴How many are your works, Lord!
In wisdom you made them all;
the earth is full of your creatures.

Revelation 4:11 (NIV)

¹¹“You are worthy, our Lord and God,
    to receive glory and honor and power,
for you created all things,
    and by your will they were created
    and have their being.”

Yes, the LORD designed the human mind by His unfathomable and deep wisdom and understanding.

Glory to God!

Thanks be to God!

The Business of Artificial Intelligence — from hbr.org by Erik Brynjolfsson & Andrew McAfee

Excerpts (emphasis DSC):

The most important general-purpose technology of our era is artificial intelligence, particularly machine learning (ML) — that is, the machine’s ability to keep improving its performance without humans having to explain exactly how to accomplish all the tasks it’s given. Within just the past few years machine learning has become far more effective and widely available. We can now build systems that learn how to perform tasks on their own.

Why is this such a big deal? Two reasons. First, we humans know more than we can tell: We can’t explain exactly how we’re able to do a lot of things — from recognizing a face to making a smart move in the ancient Asian strategy game of Go. Prior to ML, this inability to articulate our own knowledge meant that we couldn’t automate many tasks. Now we can.

Second, ML systems are often excellent learners. They can achieve superhuman performance in a wide range of activities, including detecting fraud and diagnosing disease. Excellent digital learners are being deployed across the economy, and their impact will be profound.

In the sphere of business, AI is poised have a transformational impact, on the scale of earlier general-purpose technologies. Although it is already in use in thousands of companies around the world, most big opportunities have not yet been tapped. The effects of AI will be magnified in the coming decade, as manufacturing, retailing, transportation, finance, health care, law, advertising, insurance, entertainment, education, and virtually every other industry transform their core processes and business models to take advantage of machine learning. The bottleneck now is in management, implementation, and business imagination.

…

The machine learns from examples, rather than being explicitly programmed for a particular outcome.

Let’s start by exploring what AI is already doing and how quickly it is improving. The biggest advances have been in two broad areas: perception and cognition. …For instance, Aptonomy and Sanbot, makers respectively of drones and robots, are using improved vision systems to automate much of the work of security guards.

Machine learning is driving changes at three levels: tasks and occupations, business processes, and business models.

You may have noticed that Facebook and other apps now recognize many of your friends’ faces in posted photos and prompt you to tag them with their names.

Amazon’s Alexa passes 15,000 skills, up from 10,000 in February [Perez]

On 07/21/2017, in 24x7x365 access, Amazon, Artificial Intelligence/Agents/LLMs/and Related, Daniel S. Christian, human-computer interaction (HCI), ideas, learning, learning agents, learning ecosystem, learning preferences, lifelong learning, Natural Language Processing (NLP), online media, online tutoring, personalized/customized learning, platforms, voice recognition / voice enabled interfaces, by Daniel Christian

Amazon’s Alexa passes 15,000 skills, up from 10,000 in February — from techcrunch.com by Sarah Perez

Excerpt:

Amazon’s Alexa voice platform has now passed 15,000 skills — the voice-powered apps that run on devices like the Echo speaker, Echo Dot, newer Echo Show and others. The figure is up from the 10,000 skills Amazon officially announced back in February, which had then represented a 3x increase from September.

The new 15,000 figure was first reported via third-party analysis from Voicebot, and Amazon has now confirmed to TechCrunch that the number is accurate.

According to Voicebot, which only analyzed skills in the U.S., the milestone was reached for the first time on June 30, 2017. During the month of June, new skill introductions increased by 23 percent, up from the less than 10 percent growth that was seen in each of the prior three months.

The milestone also represents a more than doubling of the number of skills that were available at the beginning of the year, when Voicebot reported there were then 7,000 skills. That number was officially confirmed by Amazon at CES.

From DSC:
Again, I wonder…what are the implications for learning from this new, developing platform?

Robots and AI are going to make social inequality even worse, says new report [Vincent]

On 07/18/2017, in 21st century, adult learning, Artificial Intelligence/Agents/LLMs/and Related, business, career development, change, changing business models, colleges, community colleges, corporate / business world, corporate universities / corporate training, cost of getting a degree, dangers of the status quo, Daniel S. Christian, disruption, economics, education, future, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, learning, Learning from the Living [Class] Room, legislatures / government / legal, lifelong learning, marketplaces, organizational change, pace of change, platforms, professional development, reinvent, robotics, society, sociology, staying relevant, strategy, student-related, surviving, the downsides of how people use tech, traditional / tradition, training / L&D, trends, UK, United States, universities, vendors, vision/possibilities, workplace, youth, by Daniel Christian

Robots and AI are going to make social inequality even worse, says new report — from theverge.com by James Vincent
Rich people are going to find it easier to adapt to automation

Excerpt:

Most economists agree that advances in robotics and AI over the next few decades are likely to lead to significant job losses. But what’s less often considered is how these changes could also impact social mobility. A new report from UK charity Sutton Trust explains the danger, noting that unless governments take action, the next wave of automation will dramatically increase inequality within societies, further entrenching the divide between rich and poor.

The are a number of reasons for this, say the report’s authors, including the ability of richer individuals to re-train for new jobs; the rising importance of “soft skills” like communication and confidence; and the reduction in the number of jobs used as “stepping stones” into professional industries.

For example, the demand for paralegals and similar professions is likely to be reduced over the coming years as artificial intelligence is trained to handle more administrative tasks. In the UK more than 350,000 paralegals, payroll managers, and bookkeepers could lose their jobs if automated systems can do the same work.

Re-training for new jobs will also become a crucial skill, and it’s individuals from wealthier backgrounds that are more able to do so, says the report. This can already be seen in the disparity in terms of post-graduate education, with individuals in the UK with working class or poorer backgrounds far less likely to re-train after university.

From DSC:
I can’t emphasize this enough. There are dangerous, tumultuous times ahead if we can’t figure out ways to help ALL people within the workforce reinvent themselves quickly, cost-effectively, and conveniently. Re-skilling/up-skilling ourselves is becoming increasingly important. And I’m not just talking about highly-educated people. I’m talking about people whose jobs are going to be disappearing in the near future — especially people whose stepping stones into brighter futures are going to wake up to a very different world. A very harsh world.

That’s why I’m so passionate about helping to develop a next generation learning platform. Higher education, as an industry, has some time left to figure out their part/contribution out in this new world. But the window of time could be closing, as another window of opportunity / era could be opening up for “the next Amazon.com of higher education.”

It’s up to current, traditional institutions of higher education as to how much they want to be a part of the solution. Some of the questions each institution ought to be asking are:

Given our institutions mission/vision, what landscapes should we be pulse-checking?
Do we have faculty/staff/members of administration looking at those landscapes that are highly applicable to our students and to their futures? How, specifically, are the insights from those employees fed into the strategic plans of our institution?
What are some possible scenarios as a result of these changing landscapes? What would our response(s) be for each scenario?
Are there obstacles from us innovating and being able to respond to the shifting landscapes, especially within the workforce?
How do we remove those obstacles?
On a scale of 0 (we don’t innovate at all) to 10 (highly innovative), where is our culture today? Where do we hope to be 5 years from now? How do we get there?

…and there are many other questions no doubt. But I don’t think we’re looking into the future nearly enough to see the massive needs — and real issues — ahead of us.

The report, which was carried out by the Boston Consulting Group and published this Wednesday [7/12/17], looks specifically at the UK, where it says some 15 million jobs are at risk of automation. But the Sutton Trust says its findings are also relevant to other developed nations, particularly the US, where social mobility is a major problem.

AI is making it extremely easy for students to cheat — from wired.com by Pippa Biddle

Excerpt (emphasis DSC):

For years, students have turned to CliffsNotes for speedy reads of books, SparkNotes to whip up talking points for class discussions, and Wikipedia to pad their papers with historical tidbits. But today’s students have smarter tools at their disposal—namely, Wolfram|Alpha, a program that uses artificial intelligence to perfectly and untraceably solve equations. Wolfram|Alpha uses natural language processing technology, part of the AI family, to provide students with an academic shortcut that is faster than a tutor, more reliable than copying off of friends, and much easier than figuring out a solution yourself.

Use of Wolfram|Alpha is difficult to trace, and in the hands of ambitious students, its perfect solutions are having unexpected consequences.

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