From DSC:
First of all, an article:

The four definitive use cases for AR and VR in retail — from forbes.com by Nikki Baird

AR in retail

Excerpt (emphasis DSC):

AR is the go-to engagement method of choice when it comes to product and category exploration. A label on a product on a shelf can only do so much to convey product and brand information, vs. AR, which can easily tap into a wealth of digital information online and bring it to life as an overlay on a product or on the label itself.

 

From DSC:
Applying this concept to the academic world…what might this mean for a student in a chemistry class who has a mobile device and/or a pair of smart goggles on and is working with an Erlenmeyer flask? A burette? A Bunsen burner?

Along these lines...what if all of those confused students — like *I* was struggling through chem lab — could see how an experiment was *supposed to be done!?*

That is, if there’s only 30 minutes of lab time left, the professor or TA could “flip a switch” to turn on the AR cloud within the laboratory space to allow those struggling students to see how to do their experiment.

I can’t tell you how many times I was just trying to get through the lab — not knowing what I was doing, and getting zero help from any professor or TA. I hardly learned a thing that stuck with me…except the names of a few devices and the abbreviations of a few chemicals. For the most part, it was a waste of money. How many students experience this as well and feel like I did?

Will the terms “blended learning” and/or “hybrid learning” take on whole new dimensions with the onset of AR, MR, and VR-related learning experiences?

#IntelligentTutoring #IntelligentSystems #LearningExperiences
#AR #VR #MR #XR #ARCloud #AssistiveTechnologies
#Chemistry #BlendedLearning #HybridLearning #DigitalLearning

 

Also see:

 

“It is conceivable that we’re going to be moving into a world without screens, a world where [glasses are] your screen. You don’t need any more form factor than [that].”

(AT&T CEO)

 

 

Philips, Microsoft Unveils Augmented Reality Concept for Operating Room of the Future — from hitconsultant.net by Fred Pennic

Excerpt:

Health technology company Philips unveiled a unique mixed reality concept developed together with Microsoft Corp. for the operating room of the future. Based on the state-of-the-art technologies of Philips’Azurion image-guided therapy platform and Microsoft’s HoloLens 2 holographic computing platform, the companies will showcase novel augmented reality applications for image-guided minimally invasive therapies.

 

 

 

Police across the US are training crime-predicting AIs on falsified data — from technologyreview.com by Karen Hao
A new report shows how supposedly objective systems can perpetuate corrupt policing practices.

Excerpts (emphasis DSC):

Despite the disturbing findings, the city entered a secret partnership only a year later with data-mining firm Palantir to deploy a predictive policing system. The system used historical data, including arrest records and electronic police reports, to forecast crime and help shape public safety strategies, according to company and city government materials. At no point did those materials suggest any effort to clean or amend the data to address the violations revealed by the DOJ. In all likelihood, the corrupted data was fed directly into the system, reinforcing the department’s discriminatory practices.


But new research suggests it’s not just New Orleans that has trained these systems with “dirty data.” In a paper released today, to be published in the NYU Law Review, researchers at the AI Now Institute, a research center that studies the social impact of artificial intelligence, found the problem to be pervasive among the jurisdictions it studied. This has significant implications for the efficacy of predictive policing and other algorithms used in the criminal justice system.

“Your system is only as good as the data that you use to train it on,” says Kate Crawford, cofounder and co-director of AI Now and an author on the study.

 

How AI is enhancing wearables — from techopedia.com by Claudio Butticev
Takeaway: Wearable devices have been helping people for years now, but the addition of AI to these wearables is giving them capabilities beyond anything seen before.

Excerpt:

Restoring Lost Sight and Hearing – Is That Really Possible?
People with sight or hearing loss must face a lot of challenges every day to perform many basic activities. From crossing the street to ordering food on the phone, even the simplest chore can quickly become a struggle. Things may change for these struggling with sight or hearing loss, however, as some companies have started developing machine learning-based systems to help the blind and visually impaired find their way across cities, and the deaf and hearing impaired enjoy some good music.

German AI company AiServe combined computer vision and wearable hardware (camera, microphone and earphones) with AI and location services to design a system that is able to acquire data over time to help people navigate through neighborhoods and city blocks. Sort of like a car navigation system, but in a much more adaptable form which can “learn how to walk like a human” by identifying all the visual cues needed to avoid common obstacles such as light posts, curbs, benches and parked cars.

 

From DSC:
So once again we see the pluses and minuses of a given emerging technology. In fact, most technologies can be used for good or for ill. But I’m left with asking the following questions:

  • As citizens, what do we do if we don’t like a direction that’s being taken on a given technology or on a given set of technologies? Or on a particular feature, use, process, or development involved with an emerging technology?

One other reflection here…it’s the combination of some of these emerging technologies that will be really interesting to see what happens in the future…again, for good or for ill. 

The question is:
How can we weigh in?

 

Also relevant/see:

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

Excerpt:

University AI programs should expand beyond computer science and engineering disciplines. AI began as an interdisciplinary field, but over the decades has narrowed to become a technical discipline. With the increasing application of AI systems to social domains, it needs to expand its disciplinary orientation. That means centering forms of expertise from the social and humanistic disciplines. AI efforts that genuinely wish to address social implications cannot stay solely within computer science and engineering departments, where faculty and students are not trained to research the social world. Expanding the disciplinary orientation of AI research will ensure deeper attention to social contexts, and more focus on potential hazards when these systems are applied to human populations.

 

Furthermore, it is long overdue for technology companies to directly address the cultures of exclusion and discrimination in the workplace. The lack of diversity and ongoing tactics of harassment, exclusion, and unequal pay are not only deeply harmful to employees in these companies but also impacts the AI products they release, producing tools that perpetuate bias and discrimination.

The current structure within which AI development and deployment occurs works against meaningfully addressing these pressing issues. Those in a position to profit are incentivized to accelerate the development and application of systems without taking the time to build diverse teams, create safety guardrails, or test for disparate impacts. Those most exposed to harm from 42 these systems commonly lack the financial means and access to accountability mechanisms that would allow for redress or legal appeals. 233 This is why we are arguing for greater funding for public litigation, labor organizing, and community participation as more AI and algorithmic systems shift the balance of power across many institutions and workplaces.

 

Also relevant/see:

 

 

 
 

Training the workforce of the future: Education in America will need to adapt to prepare students for the next generation of jobs – including ‘data trash engineer’ and ‘head of machine personality design’– from dailymail.co.uk by Valerie Bauman

Excerpts:

  • Careers that used to safely dodge the high-tech bullet will soon require at least a basic grasp of things like web design, computer programming and robotics – presenting a new challenge for colleges and universities
  • A projected 85 percent of the jobs that today’s college students will have in 2030 haven’t been invented yet
  • The coming high-tech changes are expected to touch a wider variety of career paths than ever before
  • Many experts say American universities aren’t ready for the change because the high-tech skills most workers will need are currently focused just on people specializing in science, technology, engineering and math

.

 

 

The WT2 in-ear translator will be available in January, real-time feedback soon — from wearable-technologies.com by Cathy Russey

Excerpt:

Shenzhen, China & Pasadena, CA-based startup Timekettle wants to solve the language barrier problem. So, the company developed WT2 translator – an in-ear translator for real-time, natural and hands-free communication. The company just announced they’ll be shipping the new translator in January, 2019.

 

 

 

Google Glass wasn’t a failure. It raised crucial concerns. — from wired.com by Rose Eveleth

Excerpts:

So when Google ultimately retired Glass, it was in reaction to an important act of line drawing. It was an admission of defeat not by design, but by culture.

These kinds of skirmishes on the front lines of surveillance might seem inconsequential — but they can not only change the behavior of tech giants like Google, they can also change how we’re protected under the law. Each time we invite another device into our lives, we open up a legal conversation over how that device’s capabilities change our right to privacy. To understand why, we have to get wonky for a bit, but it’s worth it, I promise.

 

But where many people see Google Glass as a cautionary tale about tech adoption failure, I see a wild success. Not for Google of course, but for the rest of us. Google Glass is a story about human beings setting boundaries and pushing back against surveillance…

 

IN THE UNITED States, the laws that dictate when you can and cannot record someone have a several layers. But most of these laws were written when smartphones and digital home assistants weren’t even a glimmer in Google’s eye. As a result, they are mostly concerned with issues of government surveillance, not individuals surveilling each other or companies surveilling their customers. Which means that as cameras and microphones creep further into our everyday lives, there are more and more legal gray zones.

 

From DSC:
We need to be aware of the emerging technologies around us. Just because we can, doesn’t mean we should. People need to be aware of — and involved with — which emerging technologies get rolled out (or not) and/or which features are beneficial to roll out (or not).

One of the things that’s beginning to alarm me these days is how the United States has turned over the keys to the Maserati — i.e., think an expensive, powerful thing — to youth who lack the life experiences to know how to handle such power and, often, the proper respect for such power. Many of these youthful members of our society don’t own the responsibility for the positive and negative influences and impacts that such powerful technologies can have.

If you owned the car below, would you turn the keys of this ~$137,000+ car over to your 16-25 year old? Yet that’s what America has been doing for years. And, in some areas, we’re now paying the price.

 

If you owned this $137,000+ car, would you turn the keys of it over to your 16-25 year old?!

 

The corporate world continues to discard the hard-earned experience that age brings…as they shove older people out of the workforce. (I hesitate to use the word wisdom…but in some cases, that’s also relevant/involved here.) Then we, as a society, sit back and wonder how did we get to this place?

Even technologists and programmers in their 20’s and 30’s are beginning to step back and ask…WHY did we develop this application or that feature? Was it — is it — good for society? Is it beneficial? Or should it be tabled or revised into something else?

Below is but one example — though I don’t mean to pick on Microsoft, as they likely have more older workers than the Facebooks, Googles, or Amazons of the world. I fully realize that all of these companies have some older employees. But the youth-oriented culture in American today has almost become an obsession — and not just in the tech world. Turn on the TV, check out the new releases on Netflix, go see a movie in a theater, listen to the radio, cast but a glance at the magazines in the check out lines, etc. and you’ll instantly know what I mean.

In the workplace, there appears to be a bias against older employees as being less innovative or tech-savvy — such a perspective is often completely incorrect. Go check out LinkedIn for items re: age discrimination…it’s a very real thing. But many of us over the age of 30 know this to be true if we’ve lost a job in the last decade or two and have tried to get a job that involves technology.

Microsoft argues facial-recognition tech could violate your rights — from finance.yahoo.com by Rob Pegoraro

Excerpt (emphasis DSC):

On Thursday, the American Civil Liberties Union provided a good reason for us to think carefully about the evolution of facial-recognition technology. In a study, the group used Amazon’s (AMZN) Rekognition service to compare portraits of members of Congress to 25,000 arrest mugshots. The result: 28 members were mistakenly matched with 28 suspects.

The ACLU isn’t the only group raising the alarm about the technology. Earlier this month, Microsoft (MSFT) president Brad Smith posted an unusual plea on the company’s blog asking that the development of facial-recognition systems not be left up to tech companies.

Saying that the tech “raises issues that go to the heart of fundamental human rights protections like privacy and freedom of expression,” Smith called for “a government initiative to regulate the proper use of facial recognition technology, informed first by a bipartisan and expert commission.”

But we may not get new laws anytime soon.

 

just because we can does not mean we should

 

Just because we can…

 

just because we can does not mean we should

 

Addendum on 12/27/18: — also related/see:

‘We’ve hit an inflection point’: Big Tech failed big-time in 2018 — from finance.yahoo.com by JP Mangalindan

Excerpt (emphasis DSC):

2018 will be remembered as the year the public’s big soft-hearted love affair with Big Tech came to a screeching halt.

For years, lawmakers and the public let massive companies like Facebook, Google, and Amazon run largely unchecked. Billions of people handed them their data — photos, locations, and other status-rich updates — with little scrutiny or question. Then came revelations around several high-profile data breaches from Facebook: a back-to-back series of rude awakenings that taught casual web-surfing, smartphone-toting citizens that uploading their data into the digital ether could have consequences. Google reignited the conversation around sexual harassment, spurring thousands of employees to walk out, while Facebook reminded some corners of the U.S. that racial bias, even in supposedly egalitarian Silicon Valley, remained alive and well. And Amazon courted well over 200 U.S. cities in its gaudy and protracted search for a second headquarters.

“I think 2018 was the year that people really called tech companies on the carpet about the way that they’ve been behaving conducting their business,” explained Susan Etlinger, an analyst at the San Francisco-based Altimeter Group. “We’ve hit an inflection point where people no longer feel comfortable with the ways businesses are conducting themselves. At the same time, we’re also at a point, historically, where there’s just so much more willingness to call out businesses and institutions on bigotry, racism, sexism and other kinds of bias.”

 

The public’s love affair with Facebook hit its first major rough patch in 2016 when Russian trolls attempted to meddle with the 2016 U.S. presidential election using the social media platform. But it was the Cambridge Analytica controversy that may go down in internet history as the start of a series of back-to-back, bruising controversies for the social network, which for years, served as the Silicon Valley poster child of the nouveau American Dream. 

 

 

Reflections on “Are ‘smart’ classrooms the future?” [Johnston]

Are ‘smart’ classrooms the future? — from campustechnology.com by Julie Johnston
Indiana University explores that question by bringing together tech partners and university leaders to share ideas on how to design classrooms that make better use of faculty and student time.

Excerpt:

To achieve these goals, we are investigating smart solutions that will:

  • Untether instructors from the room’s podium, allowing them control from anywhere in the room;
  • Streamline the start of class, including biometric login to the room’s technology, behind-the-scenes routing of course content to room displays, control of lights and automatic attendance taking;
  • Offer whiteboards that can be captured, routed to different displays in the room and saved for future viewing and editing;
  • Provide small-group collaboration displays and the ability to easily route content to and from these displays; and
  • Deliver these features through a simple, user-friendly and reliable room/technology interface.

Activities included collaborative brainstorming focusing on these questions:

  • What else can we do to create the classroom of the future?
  • What current technology exists to solve these problems?
  • What could be developed that doesn’t yet exist?
  • What’s next?

 

 

 

From DSC:
Though many peoples’ — including faculty members’ — eyes gloss over when we start talking about learning spaces and smart classrooms, it’s still an important topic. Personally, I’d rather be learning in an engaging, exciting learning environment that’s outfitted with a variety of tools (physically as well as digitally and virtually-based) that make sense for that community of learners. Also, faculty members have very limited time to get across campus and into the classroom and get things setup…the more things that can be automated in those setup situations the better!

I’ve long posted items re: machine-to-machine communications, voice recognition/voice-enabled interfaces, artificial intelligence, bots, algorithms, a variety of vendors and their products including Amazon’s Alexa / Apple’s Siri / Microsoft’s Cortana / and Google’s Home or Google Assistant, learning spaces, and smart classrooms, as I do think those things are components of our future learning ecosystems.

 

 

 

Blackboard, Apple mobile student ID has arrived — from cr80news.com by Andrew Hudson
Mobile Credential officially goes live at launch campuses

Excerpt:

We’ve officially reached the kickoff of Blackboard’s long-standing vision for the mobile student ID. Starting today on the campuses of the University of Alabama, Duke University and the University of Oklahoma, Blackboard with the aid of Apple is enabling students to use mobile credentials everywhere their plastic ID card was previously accepted.

[On 10/2/18], for the first time, iPhones and Apple Watches are enabling users to navigate the full range of transactions both on and off campus. At these three launch institutions, students can add their official student ID card to Apple Wallet to make purchases, authenticate for privileges, as well as enable physical access to dorms, rec centers, libraries and academic buildings.

 

 

 

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