Google’s robot assistant now makes eerily lifelike phone calls for you — from theguardian.com by Olivia Solon
Google Duplex contacts hair salon and restaurant in demo, adding ‘er’ and ‘mmm-hmm’ so listeners think it’s human

Excerpt:

Google’s virtual assistant can now make phone calls on your behalf to schedule appointments, make reservations in restaurants and get holiday hours.

The robotic assistant uses a very natural speech pattern that includes hesitations and affirmations such as “er” and “mmm-hmm” so that it is extremely difficult to distinguish from an actual human phone call.

The unsettling feature, which will be available to the public later this year, is enabled by a technology called Google Duplex, which can carry out “real world” tasks on the phone, without the other person realising they are talking to a machine. The assistant refers to the person’s calendar to find a suitable time slot and then notifies the user when an appointment is scheduled.

 

 

Google employees quit over the company’s military AI project — from thenextweb.com by Tristan Greene

Excerpt:

About a dozen Google employees reportedly left the company over its insistence on developing AI for the US military through a program called Project Maven. Meanwhile 4,000 others signed a petition demanding the company stop.

It looks like there’s some internal confusion over whether the company’s “Don’t Be Evil” motto covers making machine learning systems to aid warfare.

 

 

 

The link between big tech and defense work — from wired.com by Nitasha Tiku

Except:

FOR MONTHS, A growing faction of Google employees has tried to force the company to drop out of a controversial military program called Project Maven. More than 4,000 employees, including dozens of senior engineers, have signed a petition asking Google to cancel the contract. Last week, Gizmodo reported that a dozen employees resigned over the project. “There are a bunch more waiting for job offers (like me) before we do so,” one engineer says. On Friday, employees communicating through an internal mailing list discussed refusing to interview job candidates in order to slow the project’s progress.

Other tech giants have recently secured high-profile contracts to build technology for defense, military, and intelligence agencies. In March, Amazon expanded its newly launched “Secret Region” cloud services supporting top-secret work for the Department of Defense. The same week that news broke of the Google resignations, Bloomberg reported that Microsoft locked down a deal with intelligence agencies. But there’s little sign of the same kind of rebellion among Amazon and Microsoft workers.

 

 

Amazon urged not to sell facial recognition tool to police — from wpxi.com by Gene Johnson

Excerpt:

Facebook SEATTLE (AP) – The American Civil Liberties Union and other privacy advocates are asking Amazon to stop marketing a powerful facial recognition tool to police, saying law enforcement agencies could use the technology to “easily build a system to automate the identification and tracking of anyone.”

The tool, called Rekognition, is already being used by at least one agency – the Washington County Sheriff’s Office in Oregon – to check photographs of unidentified suspects against a database of mug shots from the county jail, which is a common use of such technology around the country.

 

 

From DSC:
Google’s C-Suite — as well as the C-Suites at Microsoft, Amazon, and other companies — needs to be very careful these days, as they could end up losing the support/patronage of a lot of people — including more of their own employees. It’s not an easy task to know how best to build and use technologies in order to make the world a better place…to create a dream vs. a nightmare for our future. But just because we can build something, doesn’t mean we should.

 

 

The Complete Guide to Conversational Commerce | Everything you need to know. — from chatbotsmagazine.com by Matt Schlicht

Excerpt:

What is conversational commerce? Why is it such a big opportunity? How does it work? What does the future look like? How can I get started? These are the questions I’m going to answer for you right now.

The guide covers:

  • An introduction to conversational commerce.
  • Why conversational commerce is such a big opportunity.
  • Complete breakdown of how conversational commerce works.
  • Extensive examples of conversational commerce using chatbots and voicebots.
  • How artificial intelligence impacts conversational commerce.
  • What the future of conversational commerce will look like.

 

Definition: Conversational commerce is an automated technology, powered by rules and sometimes artificial intelligence, that enables online shoppers and brands to interact with one another via chat and voice interfaces.

 

 

 

Notes from the AI frontier: Applications and value of deep learning — from mckinsey.com by Michael Chui, James Manyika, Mehdi Miremadi, Nicolaus Henke, Rita Chung, Pieter Nel, and Sankalp Malhotra

Excerpt:

Artificial intelligence (AI) stands out as a transformational technology of our digital age—and its practical application throughout the economy is growing apace. For this briefing, Notes from the AI frontier: Insights from hundreds of use cases (PDF–446KB), we mapped both traditional analytics and newer “deep learning” techniques and the problems they can solve to more than 400 specific use cases in companies and organizations. Drawing on McKinsey Global Institute research and the applied experience with AI of McKinsey Analytics, we assess both the practical applications and the economic potential of advanced AI techniques across industries and business functions. Our findings highlight the substantial potential of applying deep learning techniques to use cases across the economy, but we also see some continuing limitations and obstacles—along with future opportunities as the technologies continue their advance. Ultimately, the value of AI is not to be found in the models themselves, but in companies’ abilities to harness them.

It is important to highlight that, even as we see economic potential in the use of AI techniques, the use of data must always take into account concerns including data security, privacy, and potential issues of bias.

  1. Mapping AI techniques to problem types
  2. Insights from use cases
  3. Sizing the potential value of AI
  4. The road to impact and value

 

 

 

AI for Good — from re-work.co by Ali Shah, Head of Emerging Technology and Strategic Direction – BBC

 

 

 

Algorithms are making the same mistakes assessing credit scores that humans did a century ago — from qz.com by Rachel O’Dwyer

 

 

 

 

Microsoft’s meeting room of the future is wild — from theverge.com by Tom Warren
Transcription, translation, and identification

Excerpts:

Microsoft just demonstrated a meeting room of the future at the company’s Build developer conference.

It all starts with a 360-degree camera and microphone array that can detect anyone in a meeting room, greet them, and even transcribe exactly what they say in a meeting regardless of language.

Microsoft takes the meeting room scenario even further, though. The company is using its artificial intelligence tools to then act on what meeting participants say.

 

 

From DSC:
Whoa! Many things to think about here. Consider the possibilities for global/blended/online-based learning (including MOOCs) with technologies associated with translation, transcription, and identification.

 

 

Creating continuous, frictionless learning with new technologies — from clomedia.com by Karen Hebert-Maccaro
Point-of-need and on-the-job learning experiences are about to get a lot more creative.

Excerpt:

Technology has conditioned workers to expect quick and easy experiences — from Google searches to help from voice assistants — so they can get the answers they need and get back to work. While the concept of “on-demand” learning is not new, it’s been historically tough to deliver, and though most learning and development departments have linear e-learning modules or traditional classroom experiences, today’s learners are seeking more performance-adjacent, “point-of-need” models that fit into their busy, fast-paced work environments.

Enter emerging technologies. Artificial intelligence, voice interfaces and augmented reality, when applied correctly, have the potential to radically change the nature of how we learn at work. What’s more, these technologies are emerging at a consumer-level, meaning HR’s lift in implementing them into L&D may not be substantial. Consider the technologies we already use regularly — voice assistants like Alexa, Siri and Google Assistant may be available in 55 percent of homes by 2022, providing instant, seamless access to information we need on the spot. While asking a home assistant for the weather, the best time to leave the house to beat traffic or what movies are playing at a local theater might not seem to have much application in the workplace, this nonlinear, point-of-need interaction is already playing out across learning platforms.

 

Artificial intelligence, voice interfaces and augmented reality, when applied correctly, have the potential to radically change the nature of how we learn at work.

 

 

The rise of newsroom smart machines: Optimizing workflow with artificial intelligence — from mediablog.prnewswire.com by Julian Dossett

Excerpts:

As computer algorithms become more advanced, artificial intelligence (AI) increasingly has grown prominent in the workplace.  Top news organizations now use AI for a variety of newsroom tasks.

But current AI systems largely are still dependent on humans to function correctly, and the most pressing concern is understanding how to correctly operate these systems as they continue to thrive in a variety of media-related industries.

So, while [Machine Learning] systems soon will become ubiquitous in many professions, they won’t replace the professionals working in those fields for some time — rather, they will become an advanced tool that will aid in decision making. This is not to say that AI will never endanger human jobs. Automation always will find a way.

 

 

 
AI and Chatbots in Education: What Does The FutureHold? — from chatbotsmagazine.com by Robin Singh

From DSC:
While I don’t find this  article to be exemplary, I post this one mainly to encourage innovative thinking about how we might use some of these technologies in our future learning ecosystems. 

 

 

 

 

Home Voice Control — See Josh Micro in Action!

 

 

From DSC:
Along these lines, will faculty use their voices to control their room setups (i.e., the projection, shades, room lighting, what’s shown on the LMS, etc.)?

Or will machine-to-machine communications, the Internet of Things, sensors, mobile/cloud-based apps, and the like take care of those items automatically when a faculty member walks into the room?

 

 

 

From DSC:
Check out the 2 items below regarding the use of voice as it pertains to using virtual assistants: 1 involves healthcare and the other involves education (Canvas).


1) Using Alexa to go get information from Canvas:

“Alexa Ask Canvas…”

Example questions as a student:

  • What grades am I getting in my courses?
  • What am I missing?

Example question as a teacher:

  • How many submissions do I need to grade?

See the section on asking Alexa questions…roughly between http://www.youtube.com/watch?v=e-30ixK63zE &t=38m18s through http://www.youtube.com/watch?v=e-30ixK63zE &t=46m42s

 

 

 

 


 

2) Why voice assistants are gaining traction in healthcare — from samsungnext.com by Pragati Verma

Excerpt (emphasis DSC):

The majority of intelligent voice assistant platforms today are built around smart speakers, such as the Amazon Echo and Google Home. But that might change soon, as several specialized devices focused on the health market are slated to be released this year.

One example is ElliQ, an elder care assistant robot from Samsung NEXT portfolio company Intuition Robotics. Powered by AI cognitive technology, it encourages an active and engaged lifestyle. Aimed at older adults aging in place, it can recognizing their activity level and suggest activities, while also making it easier to connect with loved ones.

Pillo is an example of another such device. It is a robot that combines machine learning, facial recognition, video conferencing, and automation to work as a personal health assistant. It can dispense vitamins and medication, answer health and wellness questions in a conversational manner, securely sync with a smartphone and wearables, and allow users to video conference with health care professionals.

“It is much more than a smart speaker. It is HIPAA compliant and it recognizes the user; acknowledges them and delivers care plans,” said Rogers, whose company created the voice interface for the platform.

Orbita is now working with toSense’s remote monitoring necklace to track vitals and cardiac fluids as a way to help physicians monitor patients remotely. Many more seem to be on their way.

“Be prepared for several more devices like these to hit the market soon,” Rogers predicted.

 

 


From DSC:

I see the piece about Canvas and Alexa as a great example of where a piece of our future learning ecosystems are heading towards — in fact, it’s been a piece of my Learning from the Living [Class] Room vision for a while now. The use of voice recognition/NLP is only picking up steam; look for more of this kind of functionality in the future. 

 

The Living [Class] Room -- by Daniel Christian -- July 2012 -- a second device used in conjunction with a Smart/Connected TV

 


 

 

 

AWS unveils ‘Transcribe’ and ‘Translate’ machine learning services — from business-standard.com

Excerpts:

  • Amazon “Transcribe” provides grammatically correct transcriptions of audio files to allow audio data to be analyzed, indexed and searched.
  • Amazon “Translate” provides natural sounding language translation in both real-time and batch scenarios.

 

 

Google’s ‘secret’ smart city on Toronto’s waterfront sparks row — from bbc.com by Robin Levinson-King BBC News, Toronto

Excerpt:

The project was commissioned by the publically funded organisation Waterfront Toronto, who put out calls last spring for proposals to revitalise the 12-acre industrial neighbourhood of Quayside along Toronto’s waterfront.

Prime Minister Justin Trudeau flew down to announce the agreement with Sidewalk Labs, which is owned by Google’s parent company Alphabet, last October, and the project has received international attention for being one of the first smart-cities designed from the ground up.

But five months later, few people have actually seen the full agreement between Sidewalk and Waterfront Toronto.

As council’s representative on Waterfront Toronto’s board, Mr Minnan-Wong is the only elected official to actually see the legal agreement in full. Not even the mayor knows what the city has signed on for.

“We got very little notice. We were essentially told ‘here’s the agreement, the prime minister’s coming to make the announcement,'” he said.

“Very little time to read, very little time to absorb.”

Now, his hands are tied – he is legally not allowed to comment on the contents of the sealed deal, but he has been vocal about his belief it should be made public.

“Do I have concerns about the content of that agreement? Yes,” he said.

“What is it that is being hidden, why does it have to be secret?”

From DSC:
Google needs to be very careful here. Increasingly so these days, our trust in them (and other large tech companies) is at stake.

 

 

Addendum on 4/16/18 with thanks to Uros Kovacevic for this resource:
Human lives saved by robotic replacements — from injuryclaimcoach.com

Excerpt:

For academics and average workers alike, the prospect of automation provokes concern and controversy. As the American workplace continues to mechanize, some experts see harsh implications for employment, including the loss of 73 million jobs by 2030. Others maintain more optimism about the fate of the global economy, contending technological advances could grow worldwide GDP by more than $1.1 trillion in the next 10 to 15 years. Whatever we make of these predictions, there’s no question automation will shape the economic future of the nation – and the world.

But while these fiscal considerations are important, automation may positively affect an even more essential concern: human life. Every day, thousands of Americans risk injury or death simply by going to work in dangerous conditions. If robots replaced them, could hundreds of lives be saved in the years to come?

In this project, we studied how many fatal injuries could be averted if dangerous occupations were automated. To do so, we analyzed which fields are most deadly and the likelihood of their automation according to expert predictions. To see how automation could save Americans’ lives, keep reading.

Also related to this item is :
How AI is improving the landscape of work  — from forbes.com by Laurence Bradford

Excerpts:

There have been a lot of sci-fi stories written about artificial intelligence. But now that it’s actually becoming a reality, how is it really affecting the world? Let’s take a look at the current state of AI and some of the things it’s doing for modern society.

  • Creating New Technology Jobs
  • Using Machine Learning To Eliminate Busywork
  • Preventing Workplace Injuries With Automation
  • Reducing Human Error With Smart Algorithms

From DSC:
This is clearly a pro-AI piece. Not all uses of AI are beneficial, but this article mentions several use cases where AI can make positive contributions to society.

 

 

 

It’s About Augmented Intelligence, not Artificial Intelligence — from informationweek.com
The adoption of AI applications isn’t about replacing workers but helping workers do their jobs better.

 

From DSC:
This article is also a pro-AI piece. But again, not all uses of AI are beneficial. We need to be aware of — and involved in — what is happening with AI.

 

 

 

Investing in an Automated Future — from clomedia.com by Mariel Tishma
Employers recognize that technological advances like AI and automation will require employees with new skills. Why are so few investing in the necessary learning?

 

 

 

 

 

2018 TECH TRENDS REPORT — from the Future Today Institute
Emerging technology trends that will influence business, government, education, media and society in the coming year.

Description:

The Future Today Institute’s 11th annual Tech Trends Report identifies 235 tantalizing advancements in emerging technologies—artificial intelligence, biotech, autonomous robots, green energy and space travel—that will begin to enter the mainstream and fundamentally disrupt business, geopolitics and everyday life around the world. Our annual report has garnered more than six million cumulative views, and this edition is our largest to date.

Helping organizations see change early and calculate the impact of new trends is why we publish our annual Emerging Tech Trends Report, which focuses on mid- to late-stage emerging technologies that are on a growth trajectory.

In this edition of the FTI Tech Trends Report, we’ve included several new features and sections:

  • a list and map of the world’s smartest cities
  • a calendar of events that will shape technology this year
  • detailed near-future scenarios for several of the technologies
  • a new framework to help organizations decide when to take action on trends
  • an interactive table of contents, which will allow you to more easily navigate the report from the bookmarks bar in your PDF reader

 


 

01 How does this trend impact our industry and all of its parts?
02 How might global events — politics, climate change, economic shifts – impact this trend, and as a result, our organization?
03 What are the second, third, fourth, and fifth-order implications of this trend as it evolves, both in our organization and our industry?
04 What are the consequences if our organization fails to take action on this trend?
05 Does this trend signal emerging disruption to our traditional business practices and cherished beliefs?
06 Does this trend indicate a future disruption to the established roles and responsibilities within our organization? If so, how do we reverse-engineer that disruption and deal with it in the present day?
07 How are the organizations in adjacent spaces addressing this trend? What can we learn from their failures and best practices?
08 How will the wants, needs and expectations of our consumers/ constituents change as a result of this trend?
09 Where does this trend create potential new partners or collaborators for us?
10 How does this trend inspire us to think about the future of our organization?

 


 

 

From DSC:
After seeing the article entitled, “Scientists Are Turning Alexa into an Automated Lab Helper,” I began to wonder…might Alexa be a tool to periodically schedule & provide practice tests & distributed practice on content? In the future, will there be “learning bots” that a learner can employ to do such self-testing and/or distributed practice?

 

 

From page 45 of the PDF available here:

 

Might Alexa be a tool to periodically schedule/provide practice tests & distributed practice on content?

 

 

 

Scientists Are Turning Alexa into an Automated Lab Helper — from technologyreview.com by Jamie Condliffe
Amazon’s voice-activated assistant follows a rich tradition of researchers using consumer tech in unintended ways to further their work.

Excerpt:

Alexa, what’s the next step in my titration?

Probably not the first question you ask your smart assistant in the morning, but potentially the kind of query that scientists may soon be leveling at Amazon’s AI helper. Chemical & Engineering News reports that software developer James Rhodes—whose wife, DeLacy Rhodes, is a microbiologist—has created a skill for Alexa called Helix that lends a helping hand around the laboratory.

It makes sense. While most people might ask Alexa to check the news headlines, play music, or set a timer because our hands are a mess from cooking, scientists could look up melting points, pose simple calculations, or ask for an experimental procedure to be read aloud while their hands are gloved and in use.

For now, Helix is still a proof-of-concept. But you can sign up to try an early working version, and Rhodes has plans to extend its abilities…

 

Also see:

Helix

 

 

What is Artificial Intelligence, Machine Learning and Deep Learning — from geospatialworld.net by Meenal Dhande

 

 

 

 

 


 

What is the difference between AI, machine learning and deep learning? — from geospatialworld.net by Meenal Dhande

Excerpt:

In the first part of this blog series, we gave you simple and elaborative definitions of what is artificial intelligence (AI), machine learning and deep learning. This is the second part of the series; here we are elucidating our readers with – What is the difference between AI, machine learning, and deep learning.

You can think of artificial intelligence (AI), machine learning and deep learning as a set of a matryoshka doll, also known as a Russian nesting doll. Deep learning is a subset of machine learning, which is a subset of AI.

 

 

 

 

 


Chatbot for College Students: 4 Chatbots Tips Perfect for College Students — from chatbotsmagazine.com by Zevik Farkash

Excerpts:

1. Feed your chatbot with information your students don’t have.
Your institute’s website can be as elaborate as it gets, but if your students can’t find a piece of information on it, it’s as good as incomplete. Say, for example, you offer certain scholarships that students can voluntarily apply for. But the information on these scholarships are tucked away on a remote page that your students don’t access in their day-to-day usage of your site.

So Amy, a new student, has no idea that there’s a scholarship that can potentially make her course 50% cheaper. She can scour your website for details when she finds the time. Or she can ask your university’s chatbot, “Where can I find information on your scholarships?”

And the chatbot can tell her, “Here’s a link to all our current scholarships.”

The best chatbots for colleges and universities tend to be programmed with even more detail, and can actually strike up a conversation by saying things like:

“Please give me the following details so I can pull out all the scholarships that apply to you.
“Which department are you in? (Please select one.)
“Which course are you enrolled in? (Please select one.)
“Which year of study are you in? (Please select one.)
“Thank you for the details! Here’s a list of all applicable scholarships. Please visit the links for detailed information and let me know if I can be of further assistance.”

2. Let it answer all the “What do I do now?” questions.

3. Turn it into a campus guide.

4. Let it take care of paperwork.

 

From DSC:
This is the sort of thing that I was trying to get at last year at the NGLS 2017 Conference:

 

 

 

 


18 Disruptive Technology Trends For 2018 — from disruptionhub.com by Rob Prevett

Excerpts:

1. Mobile-first to AI-first
A major shift in business thinking has placed Artificial Intelligence at the very heart of business strategy. 2017 saw tech giants including Google and Microsoft focus on an“AI first” strategy, leading the way for other major corporates to follow suit. Companies are demonstrating a willingness to use AI and related tools like machine learning to automate processes, reduce administrative tasks, and collect and organise data. Understanding vast amounts of information is vital in the age of mass data, and AI is proving to be a highly effective solution. Whilst AI has been vilified in the media as the enemy of jobs, many businesses have undergone a transformation in mentalities, viewing AI as enhancing rather than threatening the human workforce.

7. Voice based virtual assistants become ubiquitous
Google HomeThe wide uptake of home based and virtual assistants like Alexa and Google Home have built confidence in conversational interfaces, familiarising consumers with a seamless way of interacting with tech. Amazon and Google have taken prime position between brand and customer, capitalising on conversational convenience. The further adoption of this technology will enhance personalised advertising and sales, creating a direct link between company and consumer.

 


 

5 Innovative Uses for Machine Learning — from entrepreneur.com
They’ll be coming into your life — at least your business life — sooner than you think.

 


 

Philosophers are building ethical algorithms to help control self-driving cars – from qz.com by Olivia Goldhill

 


 

Tech’s Ethical ‘Dark Side’: Harvard, Stanford and Others Want to Address It — from nytimes.com by Natasha Singerfeb

Excerpt:

PALO ALTO, Calif. — The medical profession has an ethic: First, do no harm.

Silicon Valley has an ethos: Build it first and ask for forgiveness later.

Now, in the wake of fake news and other troubles at tech companies, universities that helped produce some of Silicon Valley’s top technologists are hustling to bring a more medicine-like morality to computer science.

This semester, Harvard University and the Massachusetts Institute of Technology are jointly offering a new course on the ethics and regulation of artificial intelligence. The University of Texas at Austin just introduced a course titled “Ethical Foundations of Computer Science” — with the idea of eventually requiring it for all computer science majors.

And at Stanford University, the academic heart of the industry, three professors and a research fellow are developing a computer science ethics course for next year. They hope several hundred students will enroll.

The idea is to train the next generation of technologists and policymakers to consider the ramifications of innovations — like autonomous weapons or self-driving cars — before those products go on sale.

 


 

 

 

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