Manufacturers have thus far incorporated the voice assistant into speakers, phones, thermostats, and more — but being incorporated into a wearable device is a first for Alexa.
The headphones will let users tap a button to launch the voice assistant, which will connect to the device through the user’s mobile phone and the Bragi app. They will let a wearer engage with the voice assistant while on the go, searching for basic information, shopping for goods on Amazon, or calling for a vehicle from ride-hailing services like Uber, among other possibilities. While all of these capabilities are already possible using a phone, enabling hands-free voice control brings a new level of convenience.
…emerging technologies such as machine learning, blockchain, drones (commercial UAVs), software-defined security and brain-computer interfaces have moved significantly along the Hype Cycle since 2016.
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The Gartner Hype Cycle for Emerging Technologies, 2017 focuses on three emerging technology mega-trends: Artificial intelligence (AI) everywhere, transparently immersive experiences and digital platforms. Enterprise architects and technology innovation leaders should explore and ideate these three mega-trends to understand the future impacts to their business.
“Organizations will continue to be faced with rapidly accelerating technology innovation that will profoundly impact the way they deal with their workforces, customers and partners,” says Mike J. Walker, research director. “Our 2017 Hype Cycle reveals three distinct technology trends that profoundly create new experiences with unrivaled intelligence, and offer platforms that propel organizations to connect with new business ecosystems in order to become competitive over the next five to 10 years.”
The most innovative AI breakthroughs, and the companies that promote them – such as DeepMind, Magic Pony, Aysadi, Wolfram Alpha and Improbable – have their origins in universities. Now AI will transform universities.
We believe AI is a new scientific infrastructure for research and learning that universities will need to embrace and lead, otherwise they will become increasingly irrelevant and eventually redundant.
Through their own brilliant discoveries, universities have sown the seeds of their own disruption. How they respond to this AI revolution will profoundly reshape science, innovation, education – and society itself.
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As AI gets more powerful, it will not only combine knowledge and data as instructed, but will search for combinations autonomously. It can also assist collaboration between universities and external parties, such as between medical research and clinical practice in the health sector.
The implications of AI for university research extend beyond science and technology.
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When it comes to AI in teaching and learning, many of the more routine academic tasks (and least rewarding for lecturers), such as grading assignments, can be automated. Chatbots, intelligent agents using natural language, are being developed by universities such as the Technical University of Berlin; these will answer questions from students to help plan their course of studies.
Virtual assistants can tutor and guide more personalized learning. As part of its Open Learning Initiative (OLI), Carnegie Mellon University has been working on AI-based cognitive tutors for a number of years. It found that its OLI statistics course, run with minimal instructor contact, resulted in comparable learning outcomes for students with fewer hours of study. In one course at the Georgia Institute of Technology, students could not tell the difference between feedback from a human being and a bot.
I built an Amazon Alexa skill called Introduction to Computing Flashcards. In using the skill, or Amazon Alexa app, students are able to listen to Alexa and then answer questions. Alexa helps students prepare for an exam by speaking definitions and then waiting for their identification. In addition to quizzing the student, Alexa is also keeping track of the correct answers. If a student answers five questions correctly, Alexa shares a game code, which is worth class experience points in the course gamification My Game app.
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Certainly, exam preparation apps are one way to use digital assistants in education. As development and publishing of Amazon Alexa skills becomes easier, faculty will be able to produce such skills just as easily as they now create PowerPoints. Given the basic code available through Amazon tutorials, it takes 20 minutes to create a new exam preparation app. Basic voice experience Amazon Alexa skills can take as much as five minutes to complete.
Universities can publish their campus news through the Alexa Flash Briefing. This type of a skill can publish news, success stories, and other events associated with the campus.
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If you are a faculty member, how can you develop your first Amazon Alexa skill? You can use any of the tutorials already available. You can also participate in an Amazon Alexa classroom training provided by Alexa Dev Days. It is possible that schools or maker spaces near you offer in-person developer sessions. You can use meetup.com to track these opportunities.
With virtual assistants answering our emails and robots replacing humans on manufacturing assembly lines, mass unemployment due to widespread automation seems imminent. But it is easy to forget amid our growing unease that these systems are not “all-knowing” and fully competent.
As many of us have observed in our interactions with artificial intelligence, these systems perform repetitive, narrowly defined tasks very well but are quickly stymied when asked to go off script — often to great comical effect. As technological advances eliminate historic roles, previously unimaginable jobs will arise in the new economic reality. We combine these two ideas to map out potential new jobs that may arise in the highly automated economy of 2030.
Despite many claims to the contrary, designing a fully autonomous system is incredibly complex and remains far out of reach. For now, training a human is still much cheaper than developing robot replacement.
From DSC:
Moving forward, perhaps one of the key values/deliverables that higher education will bring to the table will be helping people decide which of the jobs out there are “safe for now and/or into the next decade” and which jobs students should steer clear of (as such positions are already disappearing or will soon be disappearing — to be replaced by robotics, algorithms, AI, and such).*
Along these lines, Tom Vander Ark’s recent posting (below) is akin to what I’m talking about:
Now if only we could get our accrediting methods/agencies up to speed (i.e., to become far more responsive), this could be a very valuable service to provide for prospective students in the future.
*Addendum added on 8/24/17 — a relevant quote from Cathy Engelbert, Deloitte’s CEO, on 8/22/17
We ultimately need to help today’s workers—drivers, factory workers, and beyond—discover where demand for skills will be in five to 10 years and help them gain the necessary expertise and experience to do them well. Historically, wholesale job retraining has been challenging to scale, but the inexorable nature of this transition demands that we try to help them be productive in an even more digitized world economy. We already have a skills gap; we need to figure out how to digitize and skill those workers to match them with the demand for available jobs. There is a collective dialogue that should be engaged now so we can create meaningful, fulfilling, and productive opportunities for all.
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.
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
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 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:
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 requirementsfor 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.
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.
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.
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.
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.
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.
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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.
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.
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.
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.
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.
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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.
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 — 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
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.
