This unique free event is designed to give our learning community a chance to explore the most popular topics discussed at Learning Technologies.

The 2020 Learning Technologies Summer Forum (#LTSF20) takes place online, looking at some of the key topics we examined at February’s conference. Once again, the Summer event is an opportunity to interact, experiment and try some new things together.

 

What is blockchain technology? The ultimate guide for beginners. — from cryptocoinsociety.com by Jesús Cedeño

Excerpt:

The purpose of this article is to address three central questions that should be discussed to fully understand and appreciate this revolutionary and disruptive technology called blockchain. This will include historical details about nascent technology and its evolutionary progress through the first decade of existence. We will also explore the different types of this technology and explain why the blockchain name is a misnomer and introduce a more proper name for the technology.

Why do we Need Blockchain Technology?
To answer this question we need to state what is the value proposition of Blockchain Technology. Blockchain’s value hinges on decentralization. Without decentralization blockchain technology is no different from regular databases. Decentralization removes the need to have an intermediary or a single authority that acts as gatekeepers of truth or having to trust an entity to ensure the trustworthiness of any transaction. Through blockchain, people will be able to transact with each other directly without having to worry that transactions will push through and will not be reversible.

 

 

Acts of meaning: How AI-based interviewing will transform career preparation in higher education — from er.educause.edu by Alan Jones, Suzan Harkness and Nathan Mondragon

Excerpt:

Machines parrot and correlate information. They do not comprehend or synthesize information the way humans do. Factors such as accents in pronunciation, word ambiguity (especially if a word has multiple meanings), deeply coded biases, limited association data sets, narrow and limited network layers used in job screening, and static translations will continue to provide valid ground for caution in placing too much weight or attributing too much confidence in AI in its present form. Nonetheless, AI has crept into job candidate screening, the medical field, business analytics, higher education, and social media. What is currently essential is establishing an understanding of how best to harness and shape the use of AI to ensure it is equitable, valid, and reliable and to understand the shifting paradigm that professional career counselors play on campus as AI becomes more ubiquitous.

There appear to be three points worth considering: the AI interview in general, the predominance of word choice, and expressiveness as read by facial coding.

From DSC:
Until there is a lot more diversity within the fields of computer science and data science, I’m not as hopeful that biases can be rooted out. My niece, who worked for Microsoft for many years, finally left the company. She was tired of fighting the culture there. The large tech companies will need to do a lot better if AI is going to make FAIR and JUST inroads.

Plus, consider how many biases there are!

 

Blockchain Can Disrupt Higher Education Today, Global Labor Market Tomorrow — from cointelegraph.com by Andrew Singer
Blockchain can play its part in the education sector — record-keeping in 2–3 years and then adoption by the labor market?

Excerpt (emphasis DSC):

In the post-pandemic world, individuals will need to seize ownership and control of their educational credentials — documents like degrees and transcripts — from schools, universities and governments. That notion received key support last week from the American Council on Education in a study funded by the United States Department of Education focusing on the use of blockchain in higher education.

“Blockchain, in particular, holds promise to create more efficient, durable connections between education and work,” wrote Ted Mitchell, the president of ACE, in the foreword to the study published on June 8, adding: “In the wake of the COVID-19 crisis, learners will be more mobile, moving in and out of formal education as their job, health, and family situations change.”

A key theme of the report is personal data agency — i.e., how “distributed ledger technologies [DLT] can ‘democratize’ data and empower individuals with agency over their personal information.”

 

Blockchain has been described as a hammer in search of a nail. If so, academic credentialing appears to be as obvious a nail as one can find. The current international trade in fake academic degrees, after all, is “staggering,” as the BBC reported, and with a global labor market increasingly mobile, the world could badly use a decentralized, borderless, tamper-free ledger of verifiable credentials — both for education and the broader labor market.

 

 

 

Flipped Learning Review -- May/June 2020

 

Flipped Learning Review — May | June 2020

Except from one of the articles entitled, “Preparing to switch between in-class and online learning — from flr.flglobal.org by Thomas Mennella

“I claim that Flipped Learning is the perfect bridge between face-to-face, on-ground instruction, and an online format. It excels in both worlds and makes transitioning between the two seamless. I am not over-reaching. I am not extrapolating. And I claim to be no expert. I simply showed you the data.”

 

From DSC:
I can’t help but reflect on how slippery the slope is when we start talking about using drones — especially as sponsored and used by governments, including our government here in the U.S. Consider the following from The Future Institute.

The Future Institute Today -- discussing the slippery slope of using drones

Excerpt:

Eyes in the sky
As nationwide racial justice protests continue, some journalists and protestors have noticed a new addition to the armed police officers and National Guard troops: a drone flying a hexagon-shaped route 20,000 feet above the streets in Minneapolis. The drone, flown by U.S. Customs and Border Protection, is called a Predator, and is a piece of military technology used for identifying and targeting terrorists overseas. Lately, it’s become a more common sight domestically.

Last month, a number of New Yorkers witnessed a drone floating above them, barking orders to follow social distancing guidelines. The mysterious drone wasn’t official police equipment, but rather a privately owned device piloted by a man named Xavier Arthur in Queens, who was frustrated that people weren’t following stay-at-home orders. He claimed to represent the “Anti-Covid-19 Volunteer Drone Task Force. 

It’s not an isolated incident. During the outbreak, drones have been used extensively to monitor residents and encourage them to stay indoors, to inspect traffic stops and hospitals, and to spray cities with disinfectants. In Paris and Mumbai, they’re patrolling social distancing violators. In China, a video clip went viral, showing a drone breaking up a mahjong game—residents had defied local orders that they stay indoors. Drones with infrared cameras also allegedly flew overhead and checked for people with fevers.

Advanced drones can pinpoint certain behaviors in crowds from high altitudes, recognize and automatically follow targets, and communicate with each other or to command centers on the ground with remarkable precision and low latency. The pandemic and protests are playing to the strengths of an emerging real-time aerial surveillance ecosystem.

3 Things You Should Know

  1. The Flying Internet of Things is taking off.
  2. New drones can self-destruct.
  3. Shareable drones may drive growth in the industry.
 

litera tv dot com -- Daniel Linna and Bob Ambrogi's conversation on June 3, 2020

WEDNESDAY | 6.3 | Law Insights with Bob Ambrogi and Daniel Linna, Director of Law and Technology Initiatives, Northwestern University Pritzker School of Law

Notes (emphasis DSC):

  • Trying to build community, collaborate, work together
  • How do you manage a team remotely? How build community online?
  • Spontaneous interactions still needed
  • In what ways does the online ecosystem ADD to what we are doing?
  • Jury trial – online; equalizer for those involved in trial; “all in same space on the screen”
  • Start with some basic/smaller things – landlord/tenant
  • Racism going on heavily this week – a second pandemic
  • Developing a quality movement in law (Linna)
  • We need quality metrics and we need to measure the value being provided. What makes something effective, high-quality, and valuable? Now apply that thinking to the delivery of legal services.
  • Project mgmt / quality movement – less defects, etc. in 1980’s / lean thinking / 6 sigma in GE / but haven’t seen this in the area of law
  • Empiricism in law – 100 years ago medicine and law were in the same spot; since then medicine started more testing, empirical work, data-driven practices; but law didn’t
  • Daniel Linna’s blog – https://www.legaltechlever.com/
  • Can we come up with metrics?
  • Dan worked with a lawyer-assisted program in Lansing, MI – what happened? What was duration of cases? Data-driven thinking; measure; make it more of a science
  • Bob asked isn’t law less scientific and perhaps more art than a science?
  • What kinds of metrics are we talking about in litigation?
  • Contracts – can we figure out what adds value and what makes a contract “better?” (Insert from DSC: Better for whom though?)
  • What actually matters to the client? Clauses that lawyers think that are important, businesspeople don’t think are important. Risk mitigation is not all the client thinks about.
  • Incomprehensible contracts – too hard to understand
  • Natural language generation – what inputs do we need? We don’t want many contracts to be the dataset that an algorithm gets trained on.
  • (Insert from DSC: Daniel relayed some information that reminded me of Clayton Christensen’s disruptive thinking: 80% of impoverished folks get NOTHING. Totally disconnected. Perhaps we don’t need perfection, but even something is much better than nothing. For example, provide an online legal aid booklet to those who are trying to represent themselves.)
  • Go for low-hanging fruit for more empirical
  • Ambrogi: How does the work you are doing impact access to justice (#A2J)? How could quality movement impact police procedures? Is there applicability in terms of what you are writing about?
  • Human-Centered Design – uncovering biases. Why would people TRUST the criminal system if they can’t trust the CIVIL system? Perhaps if landlords thought differently. Disconnected.
  • Innovate, improve, project management;
  • Way decisions are made vary greatly; need more open data from our courts; lack of transparency from courts.
  • Leadership – commitment to resolve issues. Lacking vision. What do we want our legal systems to look like/act like?

Call to action:

  • Have or develop a quality mindset
  • Leadership needs to paint a vision for what the future looks like
  • Training around legal operations
  • How to measure quality and value – be more data-driven

We need disruption AND continuous improvement – not one or the other.
–Daniel Linna

 

Making complex data approachable through art and information design — from vtnews.vt.edu

Excerpt:

Michael Stamper, University Libraries at Virginia Tech’s data visualization designer, plays a unique role in the research process by transforming faculty and student clients’ complex research data into vibrant, interactive, and dynamic visualizations to better communicate their findings to a broad audience.

 

Why education is a ‘wicked problem’ for learning engineers to solve — from edsurge.com by Rebecca Koenig

Excerpts (emphasis DSC):

So, back to the wicked problem: How do we make education that’s both quality education and at the same time accessible and affordable?

“Now, we are building a new technology that we call Agent Smith. It’s another AI technology— and we’re very excited about it—that builds [a] Jill Watson for you. And Agent Smith can build a Jill Watson for you in less than 10 percent of the hours.”

So one question for online education is, can we build a new set of tools—and I think that’s where AI is going to go, that learning engineering is going to go—where AI is not helping individual humans as much as AI is helping human-human interaction.

Huge ethical issues and something that learning engineering has not yet started focusing on in a serious manner. We are still in a phase of, “Look ma, no hands, I can ride a bike without hands.”

Technology should not be left to technologists.

Learning from the living class room

 

My thanks to a friend for causing me to further reflect on this article: “Can computers ever replace the classroom?” [Beard]


From DSC:
I’d like to thank Mr. Eric Osterberg — a fraternity brother and friend of mine — for sending me the following article. I wrote back to him. After thanking Eric for the article, I said:

Such an article makes me reflect on things — which is always a good thing for me to try to see my blindspots and/or to think about the good and bad of things. Technologies are becoming more powerful and integrated into our lives — for better at times and for worse at other times.

I’m wondering how the legal realm can assist and/or help create a positive future for societies throughout the globe…any thoughts?


Can computers ever replace the classroom? — from theguardian.com by Alex Beard
With 850 million children worldwide shut out of schools, tech evangelists claim now is the time for AI education. But as the technology’s power grows, so too do the dangers that come with it. 

Excerpts:

But it’s in China, where President Xi Jinping has called for the nation to lead the world in AI innovation by 2030, that the fastest progress is being made. In 2018 alone, Li told me, 60 new AI companies entered China’s private education market. Squirrel AI is part of this new generation of education start-ups. The company has already enrolled 2 million student users, opened 2,600 learning centres in 700 cities across China, and raised $150m from investors.

The supposed AI education revolution is not here yet, and it is likely that the majority of projects will collapse under the weight of their own hype.

The point, in short, is that AI doesn’t have to match the general intelligence of humans to be useful – or indeed powerful. This is both the promise of AI, and the danger it poses.

It was a reminder that Squirrel AI’s platform, like those of its competitors worldwide, doesn’t have to be better than the best human teachers – to improve people’s lives, it just needs to be good enough, at the right price, to supplement what we’ve got. The problem is that it is hard to see technology companies stopping there. For better and worse, their ambitions are bigger. “We could make a lot of geniuses,” Li told me.

 

Evaluating Legal Services: The Need for a Quality Movement and Standard Measures of Quality and Value – Chapter in Research Handbook on Big Data Law — from legaltechlever.com by Daniel Linna Jr.

Excerpt (emphasis DSC):

How do we evaluate the quality and value of legal services? For example, if we compare two proposed contracts for a commercial agreement, how do we determine which contract is of higher quality? How do we determine the total value produced by the process of drafting, negotiating, and finalizing each contract? Would our answers change if some or all of the services are produced by a software application? If a software application is used, how would we evaluate the quality of any training data inputs, the development process, and the outputs of the software application? Would our assessment of the quality and value of the software application change if the software application is used to serve individuals who would otherwise go without a lawyer?

These are just some of the questions that I discuss in this draft book chapter, Evaluating Legal Services: The Need for a Quality Movement and Standard Measures of Quality and Value, the final version of which will be available in the Research Handbook on Big Data Law edited by Dr. Roland Vogl, forthcoming 2020, Edward Elgar Publishing Ltd.

With this chapter, I aim to demonstrate the need for a quality movement and standard measures of quality and value and highlight some of the research and resources. My goal is to catalyze debate, rigorous research, and sustained action. If we do not undertake this work, we risk squandering abundant opportunities to improve legal services, legal systems, justice, and the law itself.

 

 

Another legal item of note:

 

How AI can bridge the gap between business and IT — from technative.io

Excerpts:

Artificial intelligence and intelligent automation are changing how businesses function. How they collect data, capture information, present it, and leverage it to gain more customers, convert more visitors, and expand their operations.

According to Gartner, the global business value derived from AI will reach $3.9 trillion by 2022, through improved customer experience, reduced operating costs, and new revenue generation. Gartner also predicts that automating decision-making by harnessing unstructured data will be a key driving force of this trend- growing AI-derived value from just 2 percent in 2018 to 16 percent in 2022.

Also see:

Cybercrime, meet AI — from technative.io

Excerpt:

The value of AI in this model is that it lets companies take large volumes of information and find clusters of similarity. This is always the focus of cybersecurity to a degree, but organisations are often unequipped to do so in sufficient depth because of time and resourcing constraints. By contrast, AI can whittle down vast quantities of seemingly unrelated data into a few actionable incidents or outputs at speed, giving companies the ability to quickly pick out potential threats in a huge haystack.

The ability to quickly turn large amounts of data into actionable insights is something that cybersecurity teams are going to need in the coming years, because AI could become a formidable enemy. Unlike malware, which is purely automated, AI is beginning to mimic humans to a worryingly accurate degree. It can draw pictures, age photographs of people, write well enough to persuade people of truths – or lies.

 

Why law librarians are so important in a data-driven world — from Oxford University Press (blog.oup.com) by Femi Cadmus

Excerpt (emphasis DSC):

Looking ahead, the integration of technology in the work of law librarians will only increase. Over 90% of government law library employees say that artificial intelligence or machine learning has already affected their workflow by automating routine tasks. Over a quarter of law firms or corporations now have at least one active artificial intelligence initiative. Of those, more than half involve the library. It is therefore not surprising that the skills law library employees plan to develop in the next two years include artificial intelligence or machine learning, data analytics, and blockchain (in that order).

 

Strategy Matters | Elliott Masie on where we’re headed — from performancematters.podbean.com by Bob Mosher and Elliott Masie
Listen as Bob Mosher and Elliott Masie discuss how learning is changing and what suggestions Elliott gave to two different airlines.

#corporatelearning #training #L&D
#strategy #learning #everydaylearning

 

How higher education can adapt to the future of work — from weforum.org by Farnam Jahanian, President, Carnegie Mellon University; with thanks to Evan Kirstel for sharing this here

Excerpts:

Embrace the T-shaped approach to knowledge
The broad set of skills needed by tomorrow’s workforce also affects our approach to educational structure. At Carnegie Mellon University—like many other institutions—we have been making disciplinary boundaries much more porous and have launched programmes at the edges and intersections of traditional fields, such as behavioral economics, computational biology, and the nexus of design, arts, and technology. We believe this approach prepares our students for a future where thinking and working across boundaries will be vital. The value of combining both breadth and depth in higher education has also led to many universities embracing “T-shaped” teaching and learning philosophies, in which vertical (deep disciplinary) expertise is combined with horizontal (cross-cutting) knowledge.

Invest in personalised, technology-enhanced learning
The demand for more highly skilled workers continues to grow. Recent analysis of U.S. data by The Wall Street Journal found that more than 40% of manufacturing workers now have a college degree. By 2022, manufacturers are projected to employ more college graduates than workers with a high-school education or less. Technology-enhanced learning can help us keep up with demand and offer pathways for the existing workforce to gain new skills. AI-based learning tools developed in the past decade have incredible potential to personalise education, enhance college readiness and access, and improve educational outcomes. And perhaps most importantly, technology-enhanced learning has the compelling potential to narrow socioeconomic and racial achievement gaps among students.

The rapid pace of today’s advances requires a more comprehensive workforce and education strategy across a spectrum of measures, including policy, access, programmes and outreach. The private sector, government, educators and policy-makers must work together to deliver multiple pathways to opportunity for young people looking for their first foothold in the job market, as well as to re-skill and up-skill workers striving to maintain their place in the workforce. 

 

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