The 2022 L&D Global Sentiment Survey — from donaldtaylor.co.uk by Donald Taylor

Excerpt:

This year’s L&D Global Sentiment Survey, the ninth, shows L&D at a turning point, as the result of two forces. One is the demands of organisations, as they emerge from the pandemic, for more training delivery, very often with unchanged or reduced resources for L&D. The other is the need to deal with the emergency measures put in place in 2020 to deal with the immediate impact of COVID-19.

This sense of practitioners being under pressure is amply illustrated by responses to the free text question ‘What is your biggest L&D challenge in 2022?’ 40% of respondents answered, with the answers painting a picture of practitioners being asked to do more, in difficult circumstances, to support the learning of overworked employees and uninterested employers.

It is tempting to see this as a return to business-as-usual for L&D. Hasn‘t it always been the case that the department needed to fight for the attention of both executives and employees? Behind this undeniable reality, however, there are definite signs of longer-term trends emerging.


 


 

How to ensure we benefit society with the most impactful technology being developed today — from deepmind.com by Lila Ibrahim

In 2000, I took a sabbatical from my job at Intel to visit the orphanage in Lebanon where my father was raised. For two months, I worked to install 20 PCs in the orphanage’s first computer lab, and to train the students and teachers to use them. The trip started out as a way to honour my dad. But being in a place with such limited technical infrastructure also gave me a new perspective on my own work. I realised that without real effort by the technology community, many of the products I was building at Intel would be inaccessible to millions of people. I became acutely aware of how that gap in access was exacerbating inequality; even as computers solved problems and accelerated progress in some parts of the world, others were being left further behind. 

After that first trip to Lebanon, I started reevaluating my career priorities. I had always wanted to be part of building groundbreaking technology. But when I returned to the US, my focus narrowed in on helping build technology that could make a positive and lasting impact on society. That led me to a variety of roles at the intersection of education and technology, including co-founding Team4Tech, a non-profit that works to improve access to technology for students in developing countries. 


Also relevant/see:

Microsoft AI news: Making AI easier, simpler, more responsible — from venturebeat.com by Sharon Goldman

But one common theme bubbles over consistently: For AI to become more useful for business applications, it needs to be easier, simpler, more explainable, more accessible and, most of all, responsible

 

 

Radar trends to watch: May 2022 — from oreilly.com
Developments in Web3, Security, Biology, and More

Excerpt:

April was the month for large language models. There was one announcement after another; most new models were larger than the previous ones, several claimed to be significantly more energy efficient.

 

China is about to regulate AI—and the world is watching — from wired.com by Jennifer Conrad
Sweeping rules will cover algorithms that set prices, control search results, recommend videos, and filter content.

Excerpt:

Some provisions aim to address complaints about online services. Under the rules, for instance, companies will be prohibited from using personal characteristics to offer users different prices for a product; they also will be required to notify users, and allow them to opt out, when algorithms are used to make recommendations.

Companies that violate the rules could face fines, be barred from enrolling new users, have their business licenses pulled, or see their websites or apps shut down.

Some elements of the new regulations may prove difficult or impossible to enforce. It can be technically challenging to police the behavior of an algorithm that is continually changing due to new input, for instance.

 

12 examples of artificial intelligence in everyday life — from itproportal.com by Christopher Oldman

Excerpt:

4. Plagiarism
The college students’ (or is it professor’s?) nightmare. Whether you are a content manager or a teacher grading essays, you have the same problem – the internet makes plagiarism easier.

There is a nigh unlimited amount of information and data out there, and less-than-scrupulous students and employees will readily take advantage of that.

Indeed, no human could compare and contrast somebody’s essay with all the data out there. AIs are a whole different beast.

They can sift through an insane amount of information, compare it with the relevant text, and see if there is a match or not.

Furthermore, thanks to advancement and growth in this area, some tools can actually check sources in foreign languages, as well as images and audio.

Intel calls its AI that detects student emotions a teaching tool. Others call it ‘morally reprehensible.’ — from protocol.com by Kate Kaye
Virtual school software startup Classroom Technologies will test the controversial “emotion AI” technology.

Excerpts:

But Intel and Classroom Technologies, which sells virtual school software called Class, think there might be a better way. The companies have partnered to integrate an AI-based technology developed by Intel with Class, which runs on top of Zoom. Intel claims its system can detect whether students are bored, distracted or confused by assessing their facial expressions and how they’re interacting with educational content.

But critics argue that it is not possible to accurately determine whether someone is feeling bored, confused, happy or sad based on their facial expressions or other external signals.

The classroom is just one arena where controversial “emotion AI” is finding its way into everyday tech products and generating investor interest. It’s also seeping into delivery and passenger vehicles and virtual sales and customer service software.

MIT’s FutureMakers programs help kids get their minds around — and hands on — AI — from news.mit.edu by Kim Patch
The programs are designed to foster an understanding of how artificial intelligence technologies work, including their social implications.

Excerpt:

During one-week, themed FutureMakers Workshops organized around key topics related to AI, students learn how AI technologies work, including social implications, then build something that uses AI.

“AI is shaping our behaviors, it’s shaping the way we think, it’s shaping the way we learn, and a lot of people aren’t even aware of that,” says Breazeal. “People now need to be AI literate given how AI is rapidly changing digital literacy and digital citizenship.”

AI can now kill those annoying cookie pop-ups — from thenextweb.com by Thomas Macaulay
The notifications have been put on notice

Excerpt:

After years of suffering this digital torture, a new AI tool has finally offered hope of an escape.

Named CookieEnforcer, the system was created by researchers from Google and the University of Wisconsin-Madison.

The system was created to stop cookies from manipulating people into making website-friendly choices that put their privacy at risk. Yet it could also end the constant hassle of navigating the notices.

Using machine learning to improve student success in higher education — from mckinsey.com
Deploying machine learning and advanced analytics thoughtfully and to their full potential may support improvements in student access, success, and the overall student experience.

Excerpt:

Yet higher education is still in the early stages of data capability building. With universities facing many challenges (such as financial pressures, the demographic cliff, and an uptick in student mental-health issues) and a variety of opportunities (including reaching adult learners and scaling online learning), expanding use of advanced analytics and machine learning may prove beneficial.

Below, we share some of the most promising use cases for advanced analytics in higher education to show how universities are capitalizing on those opportunities to overcome current challenges, both enabling access for many more students and improving the student experience.

Artificial intelligence (AI): 7 roles to prioritize now — from enterprisersproject.com by Marc Lewis
Which artificial intelligence (AI) jobs are hottest now? Consider these seven AI/ML roles to prioritize in your organization

Excerpt:

Rather than a Great Resignation, this would suggest a Great Reallocation of the workforce. As a global search consultant, we are seeing this precipitous shift in positions, with great demand for skills in artificial intelligence and machine learning (AI/ML).

With that in mind, here are seven artificial intelligence (AI)-related roles to consider prioritizing right now as the workforce reallocates talent to new jobs that drive economic value for leading companies…

4 ways AI will be a great teaching assistant — from thetechedvocate.org by Matthew Lynch

 

2022 Outlook: 6 Legal Trends and Predictions to Have on Your Radar — from jdsupra.com by Vivian Susko

Excerpt:

In January, 2020, we made some bold predictions about what would lie ahead for legal operations in the new decade. Let’s dive back into some of our top forecasts, survey our new landscape, and see which legal trends are currently impacting the industry in 2022. Mitratech expert, Justin Silverman, weighs in on what you can expect to see on the horizon for legal ops.

Points on a radar screen

 

Weighing the best strategies for reading intervention — from hechingerreport.org by Caralee Adams
Some schools are overhauling reading instruction and trying a variety of approaches to address the pandemic’s impact on learning

Excerpt:

But, some experts say, schools should also invest in deeper changes that tackle the root of the problem: Many teachers aren’t well versed in the science of reading and the best ways to teach to the widening range of abilities they are seeing in students.

Teachers need training on the science of reading research, guidance on leveraging data and ongoing support to help them target instruction.

 

The Skills Needed to Practice “New Law” — from abaforlawstudents.com by Ram Vasudevan

Excerpt:

…but proficiencies in technology, data and analytics, math and statistics, finance and budgeting, and large-scale project management are among the most valuable. Each of these skill sets now comes into play in the practice of law on a near-daily basis.

All these new legal competencies have in common the recognition that legal projects involve far more than legal skills. Too many lawyers, however, are still narrowly focused on the legal aspect of their work and are therefore missing out on a whole host of opportunities. Rising lawyers and law firm graduates who might have previously struggled to be part of the hiring conversation can now make themselves highly marketable by becoming experts in one or more of these areas and filling a pressing need in today’s legal organizations.

Also relevant/see:

 

Radar trends to watch: April 2022 — from oreillky.com by Mike Loukides
Developments in Programming, Biology, Hardware, and More

5 Digital Transformation Themes for Higher Education — from
Explore key topics and event recordings from our latest deep dive into Digital Transformation in Higher Education.

The semiconductor decade: A trillion-dollar industry — from mckinsey.com by Ondrej Burkacky, Julia Dragon, and Nikolaus Lehmann

Drilling down into individual subsegments, about 70 percent of growth is predicted to be driven by just three industries: automotive, computation and data storage, and wireless.

Addendum later on 4/8/22:

 

Technology Trends for 2022 — from oreilly.com
What O’Reilly Learning Platform Usage Tells Us About Where the Industry Is Headed

Excerpt:

It’s been a year since our last report on the O’Reilly learning platform. Last year we cautioned against a “horse race” view of technology. That caution is worth remembering: focus on the horse race and the flashy news and you’ll miss the real stories. While new technologies may appear on the scene suddenly, the long, slow process of making things that work rarely attracts as much attention. We start with an explosion of fantastic achievements that seem like science fiction—imagine, GPT-3 can write stories!—but that burst of activity is followed by the process of putting that science fiction into production, of turning it into real products that work reliably, consistently, and fairly. AI is making that transition now; we can see it in our data. But what other transitions are in progress? What developments represent new ways of thinking, and what do those ways of thinking mean? What are the bigger changes shaping the future of software development and software architecture? This report is about those transitions.

O’Reilly Answers
We’re very excited about O’Reilly Answers, the newest product on the platform. Answers is an intelligent search that takes users directly to relevant content, whether that’s a paragraph from a book, a snippet of a video, or a block of code that answers a question. Rather than searching for an appropriate book or video and skimming through it, you can ask a specific question like “How do you flatten a list of lists in Python?” (a question I’ve asked several times). 


Also see:


 

Now we just need a “Likewise TV” for learning-related resources! [Christian]

Likewise TV Brings Curation to Streaming — from lifewire.com by Cesar Aroldo-Cadenas
And it’s available on iOS, Android, and some smart TVs

All your streaming services in one place. One search. One watchlist. Socially powered recommendations.

Entertainment startup Likewise has launched a new recommendations hub that pulls from all the different streaming platforms to give you personalized picks.

Likewise TV is a streaming hub powered by machine learning, people from the Likewise community, and other streaming services. The service aims to do away with mindlessly scrolling through a menu, looking for something to watch, or jumping from one app to another by providing a single location for recommendations.

Note that Likewise TV is purely an aggregator.


Also see:

Likewise TV -- All your streaming services in one place. One search. One watchlist. Socially powered recommendations.

 


From DSC:
Now we need this type of AI-based recommendation engine, aggregator, and service for learning-related resources!

I realize that we have a long ways to go here — as a friend/former colleague of mine just reminded me that these recommendation engines often miss the mark. I’m just hoping that a recommendation engine like this could ingest our cloud-based learner profiles and our current goals and then present some promising learning-related possibilities for us. Especially if the following graphic is or will be the case in the future:


Learning from the living class room


Also relevant/see:

From DSC:
Some interesting/noteworthy features:

  • “The 32- inch display has Wi-Fi capabilities to supports multiple streaming services, can stream smartphone content, and comes with a removable SlimFit Cam.”
  • The M8 has Wi-Fi connectivity for its native streaming apps so you won’t have to connect to a computer to watch something on Netflix. And its Far Field Voice mic can be used w/ the Always On feature to control devices like Amazon Alexa with your voice, even if the monitor is off.
  • “You can also connect devices to the monitor via the SmartThings Hub, which can be tracked with the official SmartThings app.”

I wonder how what we call the TV (or television) will continue to morph in the future.


Addendum on 3/31/22 from DSC:
Perhaps people will co-create their learning playlists…as is now possible with Spotify’s “Blend” feature:

Today’s Blend update allows you to share your personal Spotify playlists with your entire group chat—up to 10 users. You can manually invite these friends and family members to join you from in the app, then Spotify will create a playlist for you all to listen to using a mixture of everyone’s music preferences. Spotify will also create a special share card that everyone in the group can use to save and share the created playlist in the future.


 

Announcing the 2022 AI Index Report — from hai.stanford.edu by Stanford University

Excerpt/description:

Welcome to the Fifth Edition of the AI Index

The AI Index is an independent initiative at the Stanford Institute for Human-Centered Artificial Intelligence (HAI), led by the AI Index Steering Committee, an interdisciplinary group of experts from across academia and industry. The annual report trackscollatesdistills, and visualizes data relating to artificial intelligence, enabling decision-makers to take meaningful action to advance AI responsibly and ethically with humans in mind.

The 2022 AI Index report measures and evaluates the rapid rate of AI advancement from research and development to technical performance and ethics, the economy and education, AI policy and governance, and more. The latest edition includes data from a broad set of academic, private, and non-profit organizations as well as more self-collected data and original analysis than any previous editions.

Also relevant/see:

  • Andrew Ng predicts the next 10 years in AI — from venturebeat.com by George Anadiotis
  • Nvidia’s latest AI wizardry turns 2D photos into 3D scenes in milliseconds — from thenextweb.com by Thomas Macaulay
    The Polaroid of the future?
    Nvidia events are renowned for mixing technical bravado with splashes of showmanship — and this year’s GTC conference was no exception. The company ended a week that introduced a new enterprise GPU and an Arm-based “superchip” with a trademark flashy demo. Some 75 years after the world’s first instant photo captured the 3D world in a 2D picture…

Nvidia believes Instant NeRF could generate virtual worlds, capture video conferences in 3D, and reconstruct scenes for 3D maps.

 

Reflections on “Do We Really Want Academic Permanent Records to Live Forever on Blockchain?” [Bohnke]

From DSC:
Christin Bohnke raises a great and timely question out at edsurge.com in her article entitled:
Do We Really Want Academic Permanent Records to Live Forever on Blockchain?

Christin does a wonderful job of addressing the possibilities — but also the challenges — of using blockchain for educational/learning-related applications. She makes a great point that the time to look at this carefully is now:

Yet as much as unchangeable education records offer new chances, they also create new challenges. Setting personal and academic information in stone may actually counter the mission of education to help people evolve over time. The time to assess the benefits and drawbacks of blockchain technology is right now, before adoption in schools and universities is widespread.

As Christin mentions, blockchain technology can be used to store more than formal certification data. It could also store such informal certification data such as “research experience, individual projects and skills, mentoring or online learning.”

The keeping of extensive records via blockchain certainly raises numerous questions. Below are a few that come to my mind:

  • Will this type of record-keeping help or hurt in terms of career development and moving to a different job?
  • Will — or should — CMS/LMS vendors enable this type of feature/service in their products?
  • Should credentials from the following sources be considered relevant?
    • Microlearning-based streams of content
    • Data from open courseware/courses
    • Learning that we do via our Personal Learning Networks (PLNs) and social networks
    • Learning that we get from alternatives such as bootcamps, coding schools, etc.
  • Will the keeping of records impact the enjoyment of learning — or vice versa? Or will it depend upon the person?
  • Will there be more choice, more control — or less so?
  • To what (granular) level of competency-based education should we go? Or from project-based learning?
  • Could instructional designers access learners’ profiles to provide more personalized learning experiences?
  • …and I’m certain there are more questions than these.

All that said…

To me, the answers to these questions — and likely other questions as well — lie in:

  1. Giving a person a chance to learn, practice, and then demonstrate the required skills (regardless of the data the potential employer has access to)
    .
  2. Giving each user the right to own their own data — and to release it as they see fit. Each person should have the capability of managing their own information/data without having to have the skills of a software engineer or a database administrator. When something is written to a blockchain, there would be a field for who owns — and can administer — the data.

In the case of finding a good fit/job, a person could use a standardized interface to generate a URL that is sent out to a potential employer. That URL would be good for X days. The URL gives the potential employer the right to access whatever data has been made available to them. It could be full access, in which case the employer is able to run their own queries/searches on the data. Or the learner could restrict the potential employer’s reach to a more limited subset of data.

Visually, speaking:


Each learner can say who can access what data from their learner's profile


I still have a lot more thinking to do about this, but that’s where I’m at as of today. Have a good one all!


 

 

RESULTS ARE IN: HERE ARE THE 15 LEGAL TECH WINNERS OF THE 2022 ABA TECHSHOW STARTUP ALLEY COMPETITION — from techshow.com

Excerpts:

After nearly 32,000 votes, the results are in. Readers have been voting to select the 15 legal technology startups that will get to participate in the sixth-annual Startup Alley at ABA TECHSHOW 2022, taking place March 2-5, 2022.

These 15 will face off in an opening night pitch competition that will be the opening event of this year’s TECHSHOW, with the conference’s attendees voting to pick the top winner. The first-place winner gets a package of marketing and advertising prizes.

Here are the winners in order of their vote tallies. The descriptions were provided by each company.

 
© 2024 | Daniel Christian