5 things you will see in the future “smart city” — from interestingengineering.com by Taylor Donovan Barnett
The Smart City is on the horizon and here are some of the crucial technologies part of it.

5 Things You Will See in the Future of the Smart City

Excerpt:

A New Framework: The Smart City
So, what exactly is a smart city? A smart city is an urban center that hosts a wide range of digital technology across its ecosystem. However, smart cities go far beyond just this definition.

Smart cities use technology to better population’s living experiences, operating as one big data-driven ecosystem.

The smart city uses that data from the people, vehicles, buildings etc. to not only improve citizens lives but also minimize the environmental impact of the city itself, constantly communicating with itself to maximize efficiency.

So what are some of the crucial components of the future smart city? Here is what you should know.

 

 

 

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. 

 

 

EdTechs and Instructional Designers—What’s the Difference? — from er.educause.edu by Pat Reid

Excerpt:

Both edtechs and instructional designers (IDs) work with computer systems and programs, yet their actual duties differ from traditional IT tasks. The resulting confusion over what edtechs and IDs do—and how the two roles differ—is rampant, not least in the sector that needs them most: higher education.

 

Can online learning help higher ed reverse its tuition spiral? — from edsurge.com by Robert Ubell (Columnist)

Excerpt:

Classic economic theory predicts that when demand falls, so do prices. But when it comes to the price of college in the past few decades, it’s been just the other way around.

As data from the National Student Clearinghouse Center shows, tuition has escalated even as enrollments fell.

 

 

The dispiriting result is that half of all low-income high school graduates, cowed by sticker shock, don’t even bother to fill-out applications to go to college. A report by the American Council on Education concludes: “The rapid price increases in recent years, especially in the public college sector, may have led many students—particularly low-income students—to think that college is out of reach financially.”

 

Still, colleges that have devoted imagination and commitment show that even with the financial stranglehold in which most schools are locked, the spiral can actually be arrested.

College leaders need to recognize that prices have shot up too far. In the next budget cycle, as they face their treacherous spreadsheets—and before they add yet another percentage point to next year’s tuition—they must act to roll back the perilous climb.

 

 

Virtual classes shouldn’t be cringeworthy. Here are 5 tips for teaching live online — from edsurge.com by Bonni Stachowiak (Columnist)

Excerpt:

Dear Bonni: I’m wanting to learn about best practices for virtual courses that are “live” (e.g., using a platform like Zoom). It differs both from face-to-face classroom learning and traditional (asynchronous) online courses. I’d love to know about resources addressing this learning format. —Keith Johnson. director of theological development at Cru. My team facilitates and teaches graduate-level theological courses for a non-profit.

Teaching a class by live video conference is quite different than being in person with a room full of students. But there are some approaches we can draw from traditional classrooms that work quite well in a live, online environment.

Here are some recommendations for virtual teaching…

 

 

Hey bot, what’s next in line in chatbot technology? — from blog.engati.com by Imtiaz Bellary

Excerpts:

Scenario 1: Are bots the new apps?
Scenario 2: Bot conversations that make sense
Scenario 3: Can bots increase employee throughput?
Scenario 4: Let voice take over!

 

Voice as an input medium is catching up with an increasing number of folks adopting Amazon Echo and other digital assistants for their daily chores. Can we expect bots to gauge your mood and provide personalised experience as compared to a standard response? In regulated scenarios, voice acts as an authentication mechanism for the bot to pursue actions. Voice as an input adds sophistication and ease to do tasks quickly, thereby increasing user experience.

 

 

All automated hiring software is prone to bias by default — from technologyreview.com

Excerpt:

new report out from nonprofit Upturn analyzed some of the most prominent hiring algorithms on the market and found that by default, such algorithms are prone to bias.

The hiring steps: Algorithms have been made to automate four primary stages of the hiring process: sourcing, screening, interviewing, and selection. The analysis found that while predictive tools were rarely deployed to make that final choice on who to hire, they were commonly used throughout these stages to reject people.

 

“Because there are so many different points in that process where biases can emerge, employers should definitely proceed with caution,” says Bogen. “They should be transparent about what predictive tools they are using and take whatever steps they can to proactively detect and address biases that arise—and if they can’t confidently do that, they should pull the plug.”

 

 

 

How faculty can ‘click’ their way to a more inclusive classroom — from edsurge.com by Kelly Hogan and Viji Sathy

Excerpt:

What do you think is important for an instructor to do when using classroom response systems (polling software or clickers)? Select all that apply.

A) Choose questions that most students will be able to answer correctly.

B) Vary the types of poll questions beyond multiple choice.

C) Ask students “Please discuss your answer with a neighbor.”

D) Stress that students answer questions independent of their peers.

Classroom response systems (CRS) have a mixed reputation. Studies have suggested that these tools, which allow students to respond in real time to questions provided by an instructor, can improve student learning. But other reports show that is not always the case.

Like many education tools, it depends. And in the case of clickers and other classroom polling software, it largely depends on how instructors are using them. If used thoughtfully, we’ve seen that CRSs can help facilitate active learning in a classroom. What’s more, these tools can be used to also facilitate an inclusive classroom.

What do we mean by an inclusive classroom? Faculty risk excluding certain students and impeding their ability to succeed when they aren’t intentional about design and facilitation. Inclusive course design involves more than choosing content; it also requires considering the number of assessments, opportunities for practice, the chances for students to assess their understanding of material, among other attributes.

 

 

From DSC:
First of all, an excerpt from an email from RetrievalPractice.org:

Last week, we talked about an activity we call Flash Forward. Simply ask your students these questions:

“Now that you’ve taken this class, what is one thing you want to remember 10 years from now (and why)?”

“How will you remember that one thing? What will you do to make sure you don’t forget?”

Second of all, the topic of remembering something 10 years from now (from some current learning) made me think about obtaining a long-term return on investment (ROI) from that learning.

In the online-based course that I’ve been teaching for a while now, I’m all about helping the students in my classes obtain long-term benefits from taking the class. Grades aren’t the key. The learning is the key!

The class is entitled, “Foundations of Information Technology” and I want them to be using the tools, technologies, services, and concepts (that we learned about) loooooong after they graduate from college! We work on things like RSS feeds, Twitter, LinkedIn, WordPress, building their network, building their personal brand, HTML/web design, Microsoft Excel, the Internet of Things and much more. I want them to be practicing those things, leveraging those tools, pulse-checking their surroundings, networking with others, serving others with their gifts, and building on the foundations that they put into place waaaay back in 201__.

 

 

 

Forecast 5.0 – The Future of Learning: Navigating the Future of Learning  — from knowledgeworks.org by Katherine Prince, Jason Swanson, and Katie King
Discover how current trends could impact learning ten years from now and consider ways to shape a future where all students can thrive.

 

 

 

Can space activate learning? UC Irvine seeks to find out with $67M teaching facility  — from edsurge.com by Sydney Johnson

Excerpt:

When class isn’t in session, UC Irvine’s shiny new Anteater Learning Pavillion looks like any modern campus building. There are large lecture halls, hard-wired lecture capture technology, smaller classrooms, casual study spaces and brightly colored swivel chairs.

But there’s more going on in this three-level, $67-million facility, which opened its doors in September. For starters, the space is dedicated to “active learning,” a term that often refers to teaching styles that go beyond a one-way lecture format. That could range from simply giving students a chance to pause and discuss with peers, to role playing, to polling students during class, and more.

To find out what that really looks like—and more importantly, if it works—the campus is also conducting a major study over the next year to assess active learning in the new building.

 

 

 

 

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

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

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

Excerpt (emphasis DSC):

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

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

 

Also see:

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

 

Also see:

Excerpt:

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

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

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

 

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

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

 

 

 

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


 

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

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

 

 

 

 

 


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

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

 

 


 

 

Alexa, get me the articles (voice interfaces in academia) — from blog.libux.co by Kelly Dagan

Excerpt:

Credit to Jill O’Neill, who has written an engaging consideration of applications, discussions, and potentials for voice-user interfaces in the scholarly realm. She details a few use case scenarios: finding recent, authoritative biographies of Jane Austen; finding if your closest library has an item on the shelf now (and whether it’s worth the drive based on traffic).

Coming from an undergraduate-focused (and library) perspective, I can think of a few more:

  • asking if there are any group study rooms available at 7 pm and making a booking
  • finding out if [X] is open now (Archives, the Cafe, the Library, etc.)
  • finding three books on the Red Brigades, seeing if they are available, and saving the locations
  • grabbing five research articles on stereotype threat, to read later

 

Also see:

 

 

 
 
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