As Thomson Reuters readies layoffs of 3,200, what’s it mean for customers? — from lawsitesblog.com by Bob Ambrogi

Excerpts:

Thomson Reuters, the dominant provider of research and information services for the legal profession, last week announced plans to reduce its workforce by 3,200 and close 30 percent of its offices by the end of 2020. What is going on and what does it mean for the company’s customers?

The overall goal, the company said, is to create a leaner, more agile organization that will allow it to better serve its customers and shift its orientation from a content company to a software company.

“As the velocity of technology change increases and the iteration cycles become ever shorter, the new Thomson Reuters needs to run leaner, be faster and more effective,” Neil T. Masterson, co-COO, told the investors. TR plans to accomplish that through three “levers” which will result in a headcount reduction of 12 percent by 2020…

 

New operating structure of Thomson Reuters

 

 

 

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 American 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

 

 

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.

 

 

 

 

 

 

From DSC:
This is where the quizzing features/tools within a Learning Management System such as Canvas, Moodle, Blackboard Learn, etc. are so valuable. They provide students with opportunities for low-stakes (or no-stakes) practice in retrieving information and to see if they are understanding things or not. Doing such formative assessments along the way can point out areas where they need further practice, as well as areas where the students are understanding things well (and only need an occasional question or two on that item in order to reduce the effects of the forgetting curve).

 

 

 

 

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 Insecurity of Things: a Brief History of US IoT Cybersecurity Legislation (Part 2) — from zone.com by Cate Lawrence
Check out these national attempts to legislate IoT security.

Excerpt:

There’s been a number of efforts over the last few years to legislate or provide a legal response to matters of cybersecurity. Part 1 of this article takes a look at recent efforts by California. This article examines the national attempts to legislate these poorly secured connected devices.

 

Beijing to judge every resident based on behavior by end of 2020 — from bloomberg.com

  • China capital plans ‘social credit’ system by end of 2020
  • Citizens with poor scores will be ‘unable to move’ a step

Excerpt:

China’s plan to judge each of its 1.3 billion people based on their social behavior is moving a step closer to reality, with  Beijing set to adopt a lifelong points program by 2021 that assigns personalized ratings for each resident.

The capital city will pool data from several departments to reward and punish some 22 million citizens based on their actions and reputations by the end of 2020, according to a plan posted on the Beijing municipal government’s website on Monday. Those with better so-called social credit will get “green channel” benefits while those who violate laws will find life more difficult.

The Beijing project will improve blacklist systems so that those deemed untrustworthy will be “unable to move even a single step,” according to the government’s plan.

 

From DSC:
Matthew 18:21-35 comes to mind big time here! I’m glad the LORD isn’t like this…we would all be in trouble.

 

 

Mama Mia It’s Sophia: A Show Robot Or Dangerous Platform To Mislead? — from forbes.com by Noel Sharkey

Excerpts:

A collective eyebrow was raised by the AI and robotics community when the robot Sophia was given Saudia citizenship in 2017 The AI sharks were already circling as Sophia’s fame spread with worldwide media attention. Were they just jealous buzz-kills or is something deeper going on? Sophia has gripped the public imagination with its interesting and fun appearances on TV and on high-profile conference platforms.

Sophia is not the first show robot to attain celebrity status. Yet accusations of hype and deception have proliferated about the misrepresentation of AI to public and policymakers alike. In an AI-hungry world where decisions about the application of the technologies will impact significantly on our lives, Sophia’s creators may have crossed a line. What might the negative consequences be? To get answers, we need to place Sophia in the context of earlier show robots.

 

 

A dangerous path for our rights and security
For me, the biggest problem with the hype surrounding Sophia is that we have entered a critical moment in the history of AI where informed decisions need to be made. AI is sweeping through the business world and being delegated decisions that impact significantly on peoples lives from mortgage and loan applications to job interviews, to prison sentences and bail guidance, to transport and delivery services to medicine and care.

It is vitally important that our governments and policymakers are strongly grounded in the reality of AI at this time and are not misled by hype, speculation, and fantasy. It is not clear how much the Hanson Robotics team are aware of the dangers that they are creating by appearing on international platforms with government ministers and policymakers in the audience.

 

 

Ahead of the Curve: Coffee Shop Clinic — from law.com by Karen Sloan (sorry…an account/sign-in is required with this article)
At William and Mary Law School’s Military Mondays program, veterans can get benefits assistance at the local Starbucks

Excerpt:

Thus far, Military Mondays has helped 369 veterans with benefit claims, with five or six sessions each semester. It has become more comprehensive as well. A representative from the Virginia Department of Veterans Services typically attends now, meaning veterans can often file benefit claims on the spot. The state veterans services workers can also look through a veterans’ file to find necessary information, Stone told me.“It has gone really well,” he said. “It has not only helped a lot of veterans, but it has provided students a great educational experience by allowing them to meet face-to-face with veterans.

 

 

From DSC:
I have often reflected on differentiation or what some call personalized learning and/or customized learning. How does a busy teacher, instructor, professor, or trainer achieve this, realistically?

It’s very difficult and time-consuming to do for sure. But it also requires a team of specialists to achieve such a holy grail of learning — as one person can’t know it all. That is, one educator doesn’t have the necessary time, skills, or knowledge to address so many different learning needs and levels!

  • Think of different cognitive capabilities — from students that have special learning needs and challenges to gifted students
  • Or learners that have different physical capabilities or restrictions
  • Or learners that have different backgrounds and/or levels of prior knowledge
  • Etc., etc., etc.

Educators  and trainers have so many things on their plates that it’s very difficult to come up with _X_ lesson plans/agendas/personalized approaches, etc.  On the other side of the table, how do students from a vast array of backgrounds and cognitive skill levels get the main points of a chapter or piece of text? How can they self-select the level of difficulty and/or start at a “basics” level and work one’s way up to harder/more detailed levels if they can cognitively handle that level of detail/complexity? Conversely, how do I as a learner get the boiled down version of a piece of text?

Well… just as with the flipped classroom approach, I’d like to suggest that we flip things a bit and enlist teams of specialists at the publishers to fulfill this need. Move things to the content creation end — not so much at the delivery end of things. Publishers’ teams could play a significant, hugely helpful role in providing customized learning to learners.

Some of the ways that this could happen:

Use an HTML like language when writing a textbook, such as:

<MainPoint> The text for the main point here. </MainPoint>

<SubPoint1>The text for the subpoint 1 here.</SubPoint1>

<DetailsSubPoint1>More detailed information for subpoint 1 here.</DetailsSubPoint1>

<SubPoint2>The text for the subpoint 2 here.</SubPoint2>

<DetailsSubPoint2>More detailed information for subpoint 2 here.</DetailsSubPoint2>

<SubPoint3>The text for the subpoint 3 here.</SubPoint3>

<DetailsSubPoint3>More detailed information for subpoint 3 here.</DetailsSubPoint1>

<SummaryOfMainPoints>A list of the main points that a learner should walk away with.</SummaryOfMainPoints>

<BasicsOfMainPoints>Here is a listing of the main points, but put in alternative words and more basic ways of expressing those main points. </BasicsOfMainPoints>

<Conclusion> The text for the concluding comments here.</Conclusion>

 

<BasicsOfMainPoints> could be called <AlternativeExplanations>
Bottom line: This tag would be to put things forth using very straightforward terms.

Another tag would be to address how this topic/chapter is relevant:
<RealWorldApplication>This short paragraph should illustrate real world examples

of this particular topic. Why does this topic matter? How is it relevant?</RealWorldApplication>

 

On the students’ end, they could use an app that works with such tags to allow a learner to quickly see/review the different layers. That is:

  • Show me just the main points
  • Then add on the sub points
  • Then fill in the details
    OR
  • Just give me the basics via an alternative ways of expressing these things. I won’t remember all the details. Put things using easy-to-understand wording/ideas.

 

It’s like the layers of a Microsoft HoloLens app of the human anatomy:

 

Or it’s like different layers of a chapter of a “textbook” — so a learner could quickly collapse/expand the text as needed:

 

This approach could be helpful at all kinds of learning levels. For example, it could be very helpful for law school students to obtain outlines for cases or for chapters of information. Similarly, it could be helpful for dental or medical school students to get the main points as well as detailed information.

Also, as Artificial Intelligence (AI) grows, the system could check a learner’s cloud-based learner profile to see their reading level or prior knowledge, any IEP’s on file, their learning preferences (audio, video, animations, etc.), etc. to further provide a personalized/customized learning experience. 

To recap:

  • “Textbooks” continue to be created by teams of specialists, but add specialists with knowledge of students with special needs as well as for gifted students. For example, a team could have experts within the field of Special Education to help create one of the overlays/or filters/lenses — i.e., to reword things. If the text was talking about how to hit a backhand or a forehand, the alternative text layer could be summed up to say that tennis is a sport…and that a sport is something people play. On the other end of the spectrum, the text could dive deeply into the various grips a person could use to hit a forehand or backhand.
  • This puts the power of offering differentiation at the point of content creation/development (differentiation could also be provided for at the delivery end, but again, time and expertise are likely not going to be there)
  • Publishers create “overlays” or various layers that can be turned on or off by the learners
  • Can see whole chapters or can see main ideas, topic sentences, and/or details. Like HTML tags for web pages.
  • Can instantly collapse chapters to main ideas/outlines.

 

 

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