We Built an ‘Unbelievable’ (but Legal) Facial Recognition Machine — from nytimes.com by Sahil Chinoy

“The future of human flourishing depends upon facial recognition technology being banned,” wrote Woodrow Hartzog, a professor of law and computer science at Northeastern, and Evan Selinger, a professor of philosophy at the Rochester Institute of Technology, last year. ‘Otherwise, people won’t know what it’s like to be in public without being automatically identified, profiled, and potentially exploited.’ Facial recognition is categorically different from other forms of surveillance, Mr. Hartzog said, and uniquely dangerous. Faces are hard to hide and can be observed from far away, unlike a fingerprint. Name and face databases of law-abiding citizens, like driver’s license records, already exist. And for the most part, facial recognition surveillance can be set up using cameras already on the streets.” — Sahil Chinoy; per a weekly e-newsletter from Sam DeBrule at Machine Learnings in Berkeley, CA

Excerpt:

Most people pass through some type of public space in their daily routine — sidewalks, roads, train stations. Thousands walk through Bryant Park every day. But we generally think that a detailed log of our location, and a list of the people we’re with, is private. Facial recognition, applied to the web of cameras that already exists in most cities, is a threat to that privacy.

To demonstrate how easy it is to track people without their knowledge, we collected public images of people who worked near Bryant Park (available on their employers’ websites, for the most part) and ran one day of footage through Amazon’s commercial facial recognition service. Our system detected 2,750 faces from a nine-hour period (not necessarily unique people, since a person could be captured in multiple frames). It returned several possible identifications, including one frame matched to a head shot of Richard Madonna, a professor at the SUNY College of Optometry, with an 89 percent similarity score. The total cost: about $60.

 

 

 

 

From DSC:
What do you think about this emerging technology and its potential impact on our society — and on other societies like China? Again I ask…what kind of future do we want?

As for me, my face is against the use of facial recognition technology in the United States — as I don’t trust where this could lead.

This wild, wild, west situation continues to develop. For example, note how AI and facial recognition get their foot in the door via techs installed years ago:

The cameras in Bryant Park were installed more than a decade ago so that people could see whether the lawn was open for sunbathing, for example, or check how busy the ice skating rink was in the winter. They are not intended to be a security device, according to the corporation that runs the park.

So Amazon’s use of facial recognition is but another foot in the door. 

This needs to be stopped. Now.

 

Facial recognition technology is a menace disguised as a gift. It’s an irresistible tool for oppression that’s perfectly suited for governments to display unprecedented authoritarian control and an all-out privacy-eviscerating machine.

We should keep this Trojan horse outside of the city. (source)

 

Six global banks sign up to issue stablecoins on IBM’s now-live Blockchain Network — from cointelegraph.com by Marie Huillet

 

 

From DSC:
For the law schools, relevant lawyers, legislators, and judges out there…how soon before you are addressing blockchain-related issues, questions, and topics? My guess…? Sooner than you think.

 

 

Amazon is pushing facial technology that a study says could be biased — from nytimes.com by Natasha Singer
In new tests, Amazon’s system had more difficulty identifying the gender of female and darker-skinned faces than similar services from IBM and Microsoft.

Excerpt:

Over the last two years, Amazon has aggressively marketed its facial recognition technology to police departments and federal agencies as a service to help law enforcement identify suspects more quickly. It has done so as another tech giant, Microsoft, has called on Congress to regulate the technology, arguing that it is too risky for companies to oversee on their own.

Now a new study from researchers at the M.I.T. Media Lab has found that Amazon’s system, Rekognition, had much more difficulty in telling the gender of female faces and of darker-skinned faces in photos than similar services from IBM and Microsoft. The results raise questions about potential bias that could hamper Amazon’s drive to popularize the technology.

 

 

From DSC:
In this posting, I discussed an idea for a new TV show — a program that would be both entertaining and educational. So I suppose that this posting is a Part II along those same lines. 

The program that came to my mind at that time was a program that would focus on significant topics and issues within American society — offered up in a debate/presentation style format.

I had envisioned that you could have different individuals, groups, or organizations discuss the pros and cons of an issue or topic. The show would provide contact information for helpful resources, groups, organizations, legislators, etc. These contacts would be for learning more about a subject or getting involved with finding a solution for that problem.

OR

…as I revist that idea today…perhaps the show could feature humans versus an artificial intelligence such as IBM’s Project Debater:

 

 

Project Debater is the first AI system that can debate humans on complex topics. Project Debater digests massive texts, constructs a well-structured speech on a given topic, delivers it with clarity and purpose, and rebuts its opponent. Eventually, Project Debater will help people reason by providing compelling, evidence-based arguments and limiting the influence of emotion, bias, or ambiguity.

 

 

 

Big tech may look troubled, but it’s just getting started — from nytimes.com by David Streitfeld

Excerpt:

SAN JOSE, Calif. — Silicon Valley ended 2018 somewhere it had never been: embattled.

Lawmakers across the political spectrum say Big Tech, for so long the exalted embodiment of American genius, has too much power. Once seen as a force for making our lives better and our brains smarter, tech is now accused of inflaming, radicalizing, dumbing down and squeezing the masses. Tech company stocks have been pummeled from their highs. Regulation looms. Even tech executives are calling for it.

The expansion underlines the dizzying truth of Big Tech: It is barely getting started.

 

“For all intents and purposes, we’re only 35 years into a 75- or 80-year process of moving from analog to digital,” said Tim Bajarin, a longtime tech consultant to companies including Apple, IBM and Microsoft. “The image of Silicon Valley as Nirvana has certainly taken a hit, but the reality is that we the consumers are constantly voting for them.”

 

Big Tech needs to be regulated, many are beginning to argue, and yet there are worries about giving that power to the government.

Which leaves regulation up to the companies themselves, always a dubious proposition.

 

 

 

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. 

 

 

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.

 

 

 

To higher ed: When the race track is going 180mph, you can’t walk or jog onto the track. [Christian]

From DSC:
When the race track is going 180mph, you can’t walk or jog onto the track.  What do I mean by that? 

Consider this quote from an article that Jeanne Meister wrote out at Forbes entitled, “The Future of Work: Three New HR Roles in the Age of Artificial Intelligence:”*

This emphasis on learning new skills in the age of AI is reinforced by the most recent report on the future of work from McKinsey which suggests that as many as 375 million workers around the world may need to switch occupational categories and learn new skills because approximately 60% of jobs will have least one-third of their work activities able to be automated.

Go scan the job openings and you will likely see many that have to do with technology, and increasingly, with emerging technologies such as artificial intelligence, deep learning, machine learning, virtual reality, augmented reality, mixed reality, big data, cloud-based services, robotics, automation, bots, algorithm development, blockchain, and more. 

 

From Robert Half’s 2019 Technology Salary Guide 

 

 

How many of us have those kinds of skills? Did we get that training in the community colleges, colleges, and universities that we went to? Highly unlikely — even if you graduated from one of those institutions only 5-10 years ago. And many of those institutions are often moving at the pace of a nice leisurely walk, with some moving at a jog, even fewer are sprinting. But all of them are now being asked to enter a race track that’s moving at 180mph. Higher ed — and society at large — are not used to moving at this pace. 

This is why I think that higher education and its regional accrediting organizations are going to either need to up their game hugely — and go through a paradigm shift in the required thinking/programming/curricula/level of responsiveness — or watch while alternatives to institutions of traditional higher education increasingly attract their learners away from them.

This is also, why I think we’ll see an online-based, next generation learning platform take place. It will be much more nimble — able to offer up-to-the minute, in-demand skills and competencies. 

 

 

The below graphic is from:
Jobs lost, jobs gained: What the future of work will mean for jobs, skills, and wages

 

 

 


 

* Three New HR Roles To Create Compelling Employee Experiences
These new HR roles include:

  1. IBM: Vice President, Data, AI & Offering Strategy, HR
  2. Kraft Heinz Senior Vice President Global HR, Performance and IT
  3. SunTrust Senior Vice President Employee Wellbeing & Benefits

What do these three roles have in common? All have been created in the last three years and acknowledge the growing importance of a company’s commitment to create a compelling employee experience by using data, research, and predictive analytics to better serve the needs of employees. In each case, the employee assuming the new role also brought a new set of skills and capabilities into HR. And importantly, the new roles created in HR address a common vision: create a compelling employee experience that mirrors a company’s customer experience.

 


 

An excerpt from McKinsey Global Institute | Notes from the Frontier | Modeling the Impact of AI on the World Economy 

Workers.
A widening gap may also unfold at the level of individual workers. Demand for jobs could shift away from repetitive tasks toward those that are socially and cognitively driven and others that involve activities that are hard to automate and require more digital skills.12 Job profiles characterized by repetitive tasks and activities that require low digital skills may experience the largest decline as a share of total employment, from some 40 percent to near 30 percent by 2030. The largest gain in share may be in nonrepetitive activities and those that require high digital skills, rising from some 40 percent to more than 50 percent. These shifts in employment would have an impact on wages. We simulate that around 13 percent of the total wage bill could shift to categories requiring nonrepetitive and high digital skills, where incomes could rise, while workers in the repetitive and low digital skills categories may potentially experience stagnation or even a cut in their wages. The share of the total wage bill of the latter group could decline from 33 to 20 percent.13 Direct consequences of this widening gap in employment and wages would be an intensifying war for people, particularly those skilled in developing and utilizing AI tools, and structural excess supply for a still relatively high portion of people lacking the digital and cognitive skills necessary to work with machines.

 


 

 

Incumbents Strike Back: Insights from the Global C-suite Study — by the IBM Institute for Business Value

Excerpts:

Dancing with disruption
Incumbents hit their stride
We explore the forces at play in shaping the current competitive environment, the opportunities emerging, and how a balance between stability and dynamism favors the Reinventors.

Trust in the journey
The path to personalization
Here we show how the Reinventors as design thinkers are testing their assumptions and re-orienting their organizations to engage their customers and create bonds based on trust.

Orchestrating the future
The pull of platform business models
This section reveals the step change in capability that occurs as organizations scale their partner networks in new ways. We chart how organizations will need to reconsider their value propositions and allocation of resources to own or participate in platforms.

Innovation in motion
Agility for the enterprise
We delineate how leaders are liberating their employees to experiment and innovate, get up close to customers and thrive in an ever-evolving ecosystem of dynamic teams and partnerships.

 

 

 

The Law Firm Disrupted: Walmart Won’t Pay You to Cut and Paste — from law.com by Roy Strom
The world’s largest retailer, locked in a battle over the future of its business, has developed a tool to help make its many outside lawyers more efficient.

Excerpt (emphasis DSC):

Earlier this week, Walmart Inc. announced it would be rolling out 500 more giant vending machines in its stores to deliver online orders in seconds. The tool is designed to compete with online delivery services from Amazon.com Inc.

The world’s largest retailer also announced this week a tool that will compete (in some sense) with its outside counsel. Walmart has licensed a product from LegalMation that automatically drafts responses and initial discovery requests for employment and slip-and-fall suits filed in California. By this fall, the product should cover those cases in all 50 states.

LegalMation says it takes under two minutes to drag and drop a PDF of a suit into its product and receive a response to that case, in addition to a set of targeted requests for documents, form interrogatories and special interrogatories. That work has traditionally been handled by junior lawyers at Walmart’s outside firms, and LegalMation claims it can take them up to 10 hours to do. The savings on preparing an answer to these complaints is as much as 80 percent, LegalMation said.

“You’re still reviewing the outcome and reviewing the affirmative defenses,” said LegalMation co-founder Thomas Suh, a longtime legal technology advocate. “You’re eliminating the brainless cutting and pasting.”

 

About six months after the Harvard program, Lee and Suh had drilled down on where to apply AI, and they teamed up with IBM’s Watson to build their product. They also had to develop their own neural network that they said is the “secret sauce” to LegalMation’s ability to parse legalese.  “We would not be able to do this without an AI engine like Watson, and likewise I don’t think a product like this would be doable without our neural network,” Lee said.

 

 

Also see:

 

Also see:

Automation in the Legal Industry: How Will It Affect Recent Law School Grads? — from nationaljurist.com by Martin Pritikin

Excerpt:

A 2017 study by McKinsey Global Institute found that roughly half of all work activities globally have the potential to be automated by technology. A follow-on study (also from McKinsey in 2017) concluded that up to one-third of work activities could be displaced by 2030. What, if any, impacts do these eye-popping findings have on the future on the legal profession, especially for recent law school graduates embarking on their careers?

Recently, it was announced that ROSS, a legal research artificial intelligence platform powered in part by IBM’s Watson technology, was unveiling a new product, EVA, which will not only find applicable cases, but quality check case citations and history. As usual, this latest development has gotten people worried that human lawyers—and, in particular, recent law grads who have traditionally been tasked with legal research—may be on a path to extinction.

Obviously, no one can predict the future with certainty. But if history is any guide, these new technological developments will shift the type of work new lawyers are expected to do, but won’t necessarily eliminate it.

We may not be facing a future without lawyers. But it is going to be a future that requires lawyers to learn how to utilize technology effectively to serve their clients—something we should all welcome, not fear.

 

College of Law Announces the Launch of the Nation’s First Live Online J.D. Program — from law.syr.edu

Excerpt:

The American Bar Association has granted the Syracuse University College of Law a variance to offer a fully interactive online juris doctor program. The online J.D. program will be the first in the nation to combine real-time and self-paced online classes, on-campus residential classes, and experiential learning opportunities.


The online J.D. was subject to intense scrutiny and review by legal education experts before the College was granted the variance. Students in the online program will be taught by College of Law faculty, will be held to the same high admission and academic standards as students in the College’s residential program, and will take all courses required by its residential J.D. program.

 

Also see:

 

 

Blockchain: Is it Good for Education? — from virtuallyinspired.org

Excerpt:

What is Blockchain?

Blockchain is a public ledger type database made up of records called blocks that are linked together like a chain.  It is a shared unchallengeable ledger for recording the history of transactions. Here, the ledger records the history of academic accomplishments. An education ledger (blockchain) could store academic information such as degrees, diplomas, tests etc. It could be kind of digital transcript.

A Few Potential Applications of Blockchain

  • Learning Credentials Repository – A blockchain database of credentials and achievements can be a secure online repository. Digitized records/blocks replace paper copies for sharing proof of learning and can be easily accessible and tracked. Blockchain can make it easy to access all of your academic accomplishments in a digitized and ultra-secure way. Each record is a block. Your records would be chained together and new credentials will be added as you go throughout your lifetime of learning.
  • Lifelong Learning Building Blocks – Informal learning activities could be captured, validated and stored in addition to formal learning accomplishments. This can be as simple as noting a watched video or completed online lesson. We’re already seeing some universities using blockchain with badges, credits, and qualifications.
  • Authenticating Credentials – Institutions, recruiting firms or employers can easily access and verify credentials. No more gathering of papers or trying to digitize to share. Blocks are digital “learning” records and come in multilingual format eliminating the painstaking task of translation.

What’s more, with diploma mills and fake credentials causing havoc for institutions and employers, blockchain solves the issue by providing protection from fraud. It has two-step authentication and spreads blocks across numerous computer nodes. It would take hitting over 51% of computers to falsify a block.

Sony and IBM have partnered and filed patents to develop a blockchain educational platform that can house student data, their performance reports and other information related to their academic records. Some universities have created their own platforms.

 

 

Also see:

Blockchain in Education — from by Alexander Grech and Anthony F. Camilleri

Context
Blockchain technology is forecast to disrupt any field of activity that is founded on timestamped record-keeping of titles of ownership. Within education, activities likely to be disrupted by blockchain technology include the award of qualifications, licensing and accreditation, management of student records, intellectual property management and payments.

Key Advantages of Blockchain Technology
From a social perspective, blockchain technology offers significant possibilities beyond those currently available. In particular, moving records to the blockchain can allow for:

  • Self-sovereignty, i.e. for users to identify themselves while at the same time maintaining control over the storage and management of their personal data;
  • Trust, i.e. for a technical infrastructure that gives people enough confidence in its operations to carry through with transactions such as payments or the issue of certificates;
  • Transparency & Provenance, i.e. for users to conduct transactions in knowledge that each party has the capacity to enter into that transaction;
  • Immutability, i.e. for records to be written and stored permanently, without thepossibility of modification;
  • Disintermediation, i.e. the removal of the need for a central controlling authority to manage transactions or keep records;
  • Collaboration, i.e. the ability of parties to transact directly with each other without the need for mediating third parties.

 

 

Sony wants to digitize education records using the blockchain

 

 

 

 

With great tech success, comes even greater responsibility — from techcrunch.com by Ron Miller

Excerpts:

As we watch major tech platforms evolve over time, it’s clear that companies like Facebook, Apple, Google and Amazon (among others) have created businesses that are having a huge impact on humanity — sometimes positive and other times not so much.

That suggests that these platforms have to understand how people are using them and when they are trying to manipulate them or use them for nefarious purposes — or the companies themselves are. We can apply that same responsibility filter to individual technologies like artificial intelligence and indeed any advanced technologies and the impact they could possibly have on society over time.

We can be sure that Twitter’s creators never imagined a world where bots would be launched to influence an election when they created the company more than a decade ago. Over time though, it becomes crystal clear that Twitter, and indeed all large platforms, can be used for a variety of motivations, and the platforms have to react when they think there are certain parties who are using their networks to manipulate parts of the populace.

 

 

But it’s up to the companies who are developing the tech to recognize the responsibility that comes with great economic success or simply the impact of whatever they are creating could have on society.

 

 

 

 

Why the Public Overlooks and Undervalues Tech’s Power — from morningconsult.com by Joanna Piacenza
Some experts say the tech industry is rapidly nearing a day of reckoning

Excerpts:

  • 5% picked tech when asked which industry had the most power and influence, well behind the U.S. government, Wall Street and Hollywood.
  • Respondents were much more likely to say sexual harassment was a major issue in Hollywood (49%) and government (35%) than in Silicon Valley (17%).

It is difficult for Americans to escape the technology industry’s influence in everyday life. Facebook Inc. reports that more than 184 million people in the United States log on to the social network daily, or roughly 56 percent of the population. According to the Pew Research Center, nearly three-quarters (73 percent) of all Americans and 94 percent of Americans ages 18-24 use YouTube. Amazon.com Inc.’s market value is now nearly three times that of Walmart Inc.

But when asked which geographic center holds the most power and influence in America, respondents in a recent Morning Consult survey ranked the tech industry in Silicon Valley far behind politics and government in Washington, finance on Wall Street and the entertainment industry in Hollywood.

 

 

 

 

Personalized Learning Meets AI With Watson Classroom

Personalized Learning Meets AI With Watson Classroom — from gettingsmart.com by Erin Gohl

Excerpt (emphasis DSC):

Teaching is truly a Herculean challenge. Even the very best teachers can keep only so many of these insights in their heads and make only so many connections between expectations and circumstances. They can be aware of only a fraction of the research on best practices. They have only so much time to collaborate and communicate with the other adults in a particular student’s life to share information and insights. To be the best of themselves, teachers need to have access to a warehouse of information, a research assistant to mine best practices, note takers to gather and record information on each student, a statistician to gauge effective practices, and someone to collaborate with to distill the next best step with each student. In recent years, a plethora of vendors have developed software solutions that promise to simplify this process and give schools and teachers the answers to understand and address the individual needs of each student. One of the most promising, which I recently had a chance to learn about, is IBM’s Watson Classroom.

IBM is clear about what makes Watson different than existing solutions. First of all, it is a cognitive partner; not a solution. Secondly, it does not require proprietary or additional assessments, curriculum, or content. It uses whatever a district has in place. But it goes beyond the performance of tiering difficulty, pace, and reading level that is now standard fare for the solutions promising individualized, adaptive and personalized learning. Watson takes the stew of data from existing systems (including assessments, attendance records, available accommodations), adds the ability to infer meaning from written reports, and is able to connect the quality of the result to the approach that was taken. And then adjust the next recommendation based on what was learned. It is artificial intelligence (AI) brought to education that goes far beyond the adaptive learning technologies of today.

Watson Classroom is currently being piloted in 12 school districts across the country. In those classrooms, Watson Classroom is utilizing cutting-edge computing power to give teachers a full range of support to be the best versions of themselves. Watson is facilitating the kind of education the great teachers strive for every day–one where learning is truly personalized for each and every student. Bringing the power of big data to the interactions between students and teachers can help assure that every student reaches beyond our expectations to achieve their full potential.

 

 

 

Learn with Google AI: Making ML education available to everyone — from blog.google

Excerpt:

To help everyone understand how AI can solve challenging problems, we’ve created a resource called Learn with Google AI. This site provides ways to learn about core ML concepts, develop and hone your ML skills, and apply ML to real-world problems. From deep learning experts looking for advanced tutorials and materials on TensorFlow, to “curious cats” who want to take their first steps with AI, anyone looking for educational content from ML experts at Google can find it here.

Learn with Google AI also features a new, free course called Machine Learning Crash Course (MLCC). The course provides exercises, interactive visualizations, and instructional videos that anyone can use to learn and practice ML concepts.

 

 

7 Ways Chatbots and AI are Disrupting HR — from chatbotsmagazine.com
Enterprises are embracing AI for automating human resources

Excerpt:

Chatbots and AI have become household names and enterprises are taking notice. According to a recent Forrester survey, roughly “85% of customer interactions within an enterprise will be with software robots in five years’ time” and “87% of CEOs are looking to expand their AI workforce” using AI bots.

In an effort to drive increased labor efficiencies, reduce costs, and deliver better customer/employee experiences enterprises are quickly introducing AI, machine learning, and natural language understanding as core elements of their digital transformation strategy in 2018.

Human resources (HR) is one area ripe for intelligent automation within an enterprise. AI-powered bots for HR are able to streamline and personalize the HR process across seasonal, temporary, part-time, and full-time employees.


There are 7 ways in which enterprises can use HR bots to drive increased labors efficiencies, reduced costs, and better employee experiences:

  1. Recruitment
  2. Onboarding
  3. Company Policy FAQs
  4. Employee Training
  5. Common Questions
  6. Benefits Enrollment
  7. Annual Self-Assessment/Reviews

 

From DSC:
Again, this article paint a bit too rosy of a picture for me re: the use of AI and HR, especially in regards to recruiting employees.

 

 

 

Implementation of AI into eLearning. Interview with Christopher Pappas — from joomlalms.com by Darya Tarliuk

Excerpt:

Every day we hear more and more about the impact that Artificial Intelligence gains in every sphere of our life. In order to discover how AI implementation is going to change the eLearning we decided to ask Christopher Pappas to share his views and find out what he thinks about it. Christopher is an experienced eLearning specialist and the Founder of the eLearning Industry’s Network.


How to get ready preparing course materials now, while considering the future impact of AI?
Christopher: Regardless of whether you plan to adopt an AI system as soon as they’re available to the mass market or you opt to hold off (and let others work out the glitches), infrastructure is key. You can prepare your course materials now by developing course catalogs, microlearning online training repositories, and personalized online training paths that fall into the AI framework. For example, the AI system can easily recommend existing resources based on a learners’ assessment scores or job duties. All of the building blocks are in place, allowing the system to focus on content delivery and data analysis.

 

 

 

Can You Trust Intelligent Virtual Assistants? — from nojitter.com by Gary Audin
From malicious hackers to accidental voice recordings, data processed through virtual assistants may open you to security and privacy risks.

Excerpt:

Did you know that with such digital assistants your voice data is sent to the cloud or another remote location for processing? Is it safe to talk in front of your TV remote? Are you putting your business data at risk of being compromised by asking Alexa to start your meeting?

 


 

 

 

Thanks, Robots! Now These Four Non-Tech Job Skills Are In Demand — from fastcompany.com by Christian Madsbjerg
The more we rely on AI and machine learning, the more work we need social scientists and humanities experts to do.

Excerpt:

Automation isn’t a simple struggle between people and technology, with the two sides competing for jobs. The more we rely on robots, artificial intelligence (AI), and machine learning, the clearer it’s become just how much we need social scientists and humanities experts–not the reverse.

These four skills in particular are all unique to us humans, and will arguably rise in value in the coming years, as more and more companies realize they need the best of both worlds to unleash the potential from both humans and machines.

 

 

 

 

 

AI plus human intelligence is the future of work — from forbes.com by Jeanne Meister

Excerpts:

  • 1 in 5 workers will have AI as their co worker in 2022
  • More job roles will change than will be become totally automated so HR needs to prepare today


As we increase our personal usage of chatbots (defined as software which provides an automated, yet personalized, conversation between itself and human users), employees will soon interact with them in the workplace as well. Forward looking HR leaders are piloting chatbots now to transform HR, and, in the process, re-imagine, re-invent, and re-tool the employee experience.

How does all of this impact HR in your organization? The following ten HR trends will matter most as AI enters the workplace…

The most visible aspect of how HR is being impacted by artificial intelligence is the change in the way companies source and recruit new hires. Most notably, IBM has created a suite of tools that use machine learning to help candidates personalize their job search experience based on the engagement they have with Watson. In addition, Watson is helping recruiters prioritize jobs more efficiently, find talent faster, and match candidates more effectively. According to Amber Grewal, Vice President, Global Talent Acquisition, “Recruiters are focusing more on identifying the most critical jobs in the business and on utilizing data to assist in talent sourcing.”

 

…as we enter 2018, the next journey for HR leaders will be to leverage artificial intelligence combined with human intelligence and create a more personalized employee experience.

 

 

From DSC:
Although I like the possibility of using machine learning to help employees navigate their careers, I have some very real concerns when we talk about using AI for talent acquisition. At this point in time, I would much rather have an experienced human being — one with a solid background in HR — reviewing my resume to see if they believe that there’s a fit for the job and/or determine whether my skills transfer over from a different position/arena or not. I don’t think we’re there yet in terms of developing effective/comprehensive enough algorithms. It may happen, but I’m very skeptical in the meantime. I don’t want to be filtered out just because I didn’t use the right keywords enough times or I used a slightly different keyword than what the algorithm was looking for.

Also, there is definitely age discrimination occurring out in today’s workplace, especially in tech-related positions. Folks who are in tech over the age of 30-35 — don’t lose your job! (Go check out the topic of age discrimination on LinkedIn and similar sites, and you’ll find many postings on this topic — sometimes with 10’s of thousands of older employees adding comments/likes to a posting). Although I doubt that any company would allow applicants or the public to see their internally-used algorithms, how difficult would it be to filter out applicants who graduated college prior to ___ (i.e., some year that gets updated on an annual basis)? Answer? Not difficult at all. In fact, that’s at the level of a Programming 101 course.

 

 

 

Artificial intelligence is going to supercharge surveillance – from theverge.com by James Vincent
What happens when digital eyes get the brains to match?

From DSC:
Persons of interest” comes to mind after reading this article. Persons of interest is a clever, well done show, but still…the idea of combining surveillance w/ a super intelligent is a bit unnerving.

 

 

 

Artificial intelligence | 2018 AI predictions — from thomsonreuters.com

Excerpts:

  • AI brings a new set of rules to knowledge work
  • Newsrooms embrace AI
  • Lawyers assess the risks of not using AI
  • Deep learning goes mainstream
  • Smart cars demand even smarter humans
  • Accountants audit forward
  • Wealth managers look to AI to compete and grow

 

 

 

Chatbots and Virtual Assistants in L&D: 4 Use Cases to Pilot in 2018 —  from bottomlineperformance.com by Steven Boller

Excerpt:

  1. Use a virtual assistant like Amazon Alexa or Google Assistant to answer spoken questions from on-the-go learners.
  2. Answer common learner questions in a chat window or via SMS.
  3. Customize a learning path based on learners’ demographic information.
  4. Use a chatbot to assess learner knowledge.

 

 

 

Suncorp looks to augmented reality for insurance claims — from itnews.com.au by Ry Crozier with thanks to Woontack Woo for this resource

Excerpts:

Suncorp has revealed it is exploring image recognition and augmented reality-based enhancements for its insurance claims process, adding to the AI systems it deployed last year.

The insurer began testing IBM Watson software last June to automatically determine who is at fault in a vehicle accident.

“We are working on increasing our use of emerging technologies to assist with the insurance claim process, such as using image recognition to assess type and extent of damage, augmented reality that would enable an off-site claims assessor to discuss and assess damage, speech recognition, and obtaining telematic data from increasingly automated vehicles,” the company said.

 

 

 

6 important AI technologies to look out for in 2018 — from itproportal.com by  Olga Egorsheva
Will businesses and individuals finally make AI a part of their daily lives?

 

 

 

 

 

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