Artificial intelligence is taking over real estate – here’s what that means for homebuyers— from cnbc.com by Diana Olick

Excerpt:

  • Real estate companies are increasingly using artificial intelligence in every aspect of buying, selling and home financing.
  • Algorithms can now go through millions of documents in seconds, looking through property values, debt levels, home renovations, and even some of a homeowner’s personal information.
  • “The traditional agent would go knock on the doors of a lot of homes. Now AI helps you find the homes that are most likely to sell in the next 12 months,” said Compass’ chief technology officer.

For those searching to buy a home, all the data available can also help them to find exactly what they’re looking for, rather than touring house after house.

 

Defining the skills citizens will need in the future world of work — from McKinsey & Company; with thanks to Ryan Craig for this resource

Excerpts:

Our findings help define the particular skills citizens are likely to require in the future world of work and suggest how proficiency in them can influence work-related outcomes, namely employment, income, and job satisfaction. This, in turn, suggests three actions governments may wish to take.

  1. Reform education systems
  2. Reform adult-training systems
  3. Ensure affordability of lifelong education

Establish an AI aggregator of training programs to attract adult learners and encourage lifelong learning. AI algorithms could guide users on whether they need to upskill or reskill for a new profession and shortlist relevant training programs. 

Foundational skills that will help citizens thrive in the future of work


From DSC:
No one will have all 56 skills that McKinsey recommends here. So (HR) managers, please don’t load up your job postings with every single skill listed here. The search for purple unicorns can get tiring, old, and discouraging for those who are looking for work.

That said, much of what McKinsey’s research/data shows — and what their recommendations are — resonates with me. And that’s why I keep adding to the developments out at:

Learning from the living class room

A powerful, global, next-generation learning platform — meant to help people reinvent themselves quickly, safely, cost-effectively, conveniently, & consistently!!!

 

OPINION: Meet certificates and “microcredentials” — they could be the future of higher education — from hechingerreport.org by Arthur Levine and Scott Van Pelt
In years to come, they will become prevalent — and possibly preferred — to college degrees

Excerpt:

What is new is that we are calling them badges and microcredentials and using them primarily to certify specific skills, such as cross-cultural competency, welding and conversational Spanish.

So what are they? Microcredentials are certifications of mastery; badges verify the attainment of specific competencies.

No matter what we are calling them, they may be here to stay.

We now live in a time that is more open to rethinking college and university credentials. We are witnessing experimentation with competency-based education, through which students earn credits by demonstrating skills instead of spending time in courses. We are also seeing discussion of free or reduced tuition, along with subscription pricing that lets students take as many courses as they like for one low cost.

Also see:

Can an AI tutor teach your child to read? — from hechingerreport.org by Jackie Mader
Some AI reading programs are boosting early literacy skills

Excerpt:

Artificial intelligence has been used for years in education to monitor teaching quality, teach classes, grade assignments and tailor instruction to student ability levels. Now, a small but growing number of programs are attempting to use AI to target reading achievement in the early years — a longstanding struggle for America’s schools.

 

What Will Online Learning Look Like in 10 Years? Zoom Has Some Ideas — from edsurge.com by Stephen Noonoo

Excerpt:

This week at Zoom’s annual conference, Zoomtopia, a trio of education-focused Zoom employees (er, Zoomers?) speculated wildly about what hybrid Zoom learning might look like 10 years from now, given the warp speed advances in artificial intelligence and machine learning expected. Below are highlights of their grandiose, if sometimes vague, vision for the future of learning on Zoom.

Zoom very much sees itself as one day innovating on personalized learning in a substantial way, although beyond breakout rooms and instant translation services, they have few concrete ideas in mind. Mostly, the company says it will be working to add more choices to how teachers can present materials and how students can display mastery to teachers in realtime. They’re bullish on Kahoot-like gamification features and new ways of assessing students, too.

Also see:

An Eighth Grader Was Tired of Being Late to Zoom School. So He Made an App for That. — from edsurge.com by Nadia Tamez-Robledo

“I could not find anything else that exists like this to automatically join meetings at the right times,” says Seth, a high school freshman based in Walnut Creek, Calif. “Reminders are just really easy to ignore. I’ll get a notification maybe five minutes before my meeting, and it’ll just sit there and not do anything. [LinkJoin] interrupts whatever you’re doing and says, ‘Join this meeting. In fact it’s already opening, so better get on it.’”

 

 

Gartner: 4 Key Trends Speeding AI Innovation — from campustechnology.com by Rhea Kelly

Excerpt:

Research firm Gartner has identified four trends that are driving artificial intelligence innovation in the near term. These technologies and approaches will be key to scaling AI initiatives, the company emphasized in a news announcement…

 

In the US, the AI Industry Risks Becoming Winner-Take-Most — from wired.com by Khari Johnson
A new study illustrates just how geographically concentrated AI activity has become.

Excerpt:

A NEW STUDY warns that the American AI industry is highly concentrated in the San Francisco Bay Area and that this could prove to be a weakness in the long run. The Bay leads all other regions of the country in AI research and investment activity, accounting for about one-quarter of AI conference papers, patents, and companies in the US. Bay Area metro areas see levels of AI activity four times higher than other top cities for AI development.

“When you have a high percentage of all AI activity in Bay Area metros, you may be overconcentrating, losing diversity, and getting groupthink in the algorithmic economy. It locks in a winner-take-most dimension to this sector, and that’s where we hope that federal policy will begin to invest in new and different AI clusters in new and different places to provide a balance or counter,” Mark Muro, policy director at the Brookings Institution and the study’s coauthor, told WIRED.

Also relevant/see:

 

“Algorithms are opinions embedded in code.”

 
 

Graphic of digital audio for the article entitled An Edtech User’s Glossary to Speech Recognition and AI in the Classroom

An Edtech User’s Glossary to Speech Recognition and AI in the Classroom — from edsurge.com by Thomas C. Murray

Per Thomas Murray:

Recently, I collaborated with SoapBox Labs’ Amelia Kelly, the vice president of speech technology there, to create a glossary to help educators and edtech developers better familiarize themselves with speech recognition and make informed decisions about its use in educational settings. Below are some of the key terms that are particularly important, along with an explanation for why those terms matter.

 

 

Personalized Learning Using AI — from datafloq.com by Dmitry Baraishuk

Excerpt:

Process of Implementing Personalized Learning Using AI

  • The system tested every learner using short quizzes and games. Then AI adapted the learning path to each learner’s knowledge of a topic based on the test results.
  • If a pilot struggled with a certain topic, the AI LMS repeated it by presenting the information in a new way.
  • After completing a section, every pilot was retested and progressed to the next module.

Personalized learning with AI encompasses all the core aspects of online training:

  • personalized learning path;
  • relevant content based on knowledge level, skills, interests, and goals;
  • automated knowledge checks;
  • prediction of knowledge gaps;
  • proactive learners’ support;
  • tutoring, etc.
 

The Fight to Define When AI Is ‘High Risk’ — from wired.com by Khari Johnson
Everyone from tech companies to churches wants a say in how the EU regulates AI that could harm people.

Excerpt:

The AI Act is one of the first major policy initiatives worldwide focused on protecting people from harmful AI. If enacted, it will classify AI systems according to risk, more strictly regulate AI that’s deemed high risk to humans, and ban some forms of AI entirely, including real-time facial recognition in some instances. In the meantime, corporations and interest groups are publicly lobbying lawmakers to amend the proposal according to their interests.

 

Scaling HyFlex for the Post-Pandemic Campus — from er.educause.edu by Jennifer Rider and Ayla Moore

Excerpt:

Setting up HyFlex courses on any campus requires thoughtful planning, careful analysis, continual assessment, and faculty support. But is HyFlex something that higher education institutions can and should permanently adopt in a post-pandemic world?

 

Fort Lewis College's USDA Grant Proposal

 

The Tomorrow Room on campus is a space where new technology will be showcased so that faculty can become familiar with the room design and technology before teaching in a HyFlex classroom.

 

How Will Blockchain Technology Affect Law Firms? — from legalreader.com by Aleksandra Arsic
Blockchain and cryptocurrencies are here to stay. The technology might yet still be new when compared to the Internet as a whole, but it has already proved it’s ready for wider usage.

Excerpt:

With the dawn of the 21st century, many new and exciting technologies arrived, promising to take off the workload, streamline day-to-day operations, and improve finances. One of the hottest innovations in recent years has been the invention of blockchain.

While it may have started as a way to keep a ledger of Bitcoin transactions, blockchain has grown way beyond that. It has been adopted by many industries, including the legal. But, what is it, and how can it be implemented in a law firm environment? Let’s find out.

Also see:

You’re pretty familiar with artificial intelligence and machine learning in your everyday life. When you use a navigation app to see the fastest route to your destination – AI. When you ask your smart home device what time your favorite store opens – AI. And when your streaming device suggests shows you might like – yes, that’s AI, too.

While AI is becoming more and more mainstream in our homes, it’s also making its way into our jobs. You may be wondering what AI-enhanced legal technology can do for you and your law firm. Here are a few ways AI can (or already has) further advance your firm’s reputation and success.

So, what does AI look like for law firms?

 

College Was Supposed to Close the Wealth Gap for Black Americans. The Opposite Happened. — from wsj.com by Rachel Louise Ensign and Shane Shifflett
Black college graduates in their 30s have lost ground over three decades, the result of student debt and sluggish income growth

Excerpt:

The drop is driven by skyrocketing student debt and sluggish income growth, which combine to make it difficult to build savings or buy a home. Now, the generation that hoped to close the racial wealth gap is finding it is only growing wider.

More than 84% of college-educated Black households in their 30s have student debt, up from 35% three decades ago, when many baby boomers were at the same age. The younger generation owes a median of $44,000, up from less than $6,000. By comparison, 53% of white college-educated households in their 30s have debt, up from 27% three decades earlier. The median amount rose to $35,000 from $8,000. All figures are adjusted for inflation.

Also see:

American Talent Initiative 2021 | Third Annual Progress Report — from sr.ithaka.org by Martin Kurzweil, Tania LaViolet, Elizabeth Davidson Pisacreta, Adam Rabinowitz, Emily Schwartz, Joshua Wyner; with thanks to Goldie Blumenstyk at The Chronicle of Higher Education for this resource

Excerpt:

The progress report includes new enrollment data from the 2019-20 academic year as well as Fall 2020. The pre-COVID and COVID era data reveal four key findings:

  1. Before the pandemicbetween 2015-16 and 2019-20, ATI members (130 during this data collection period) collectively increased Pell enrollment by 10,417
  2. In the years leading up to the pandemic, 2018-19 and 2019-20, ATI’s progress leveled off and began to reverse, with an enrollment decline of 3,873 Pell students, attributable to two main factors: (1) substantial declines at a set of ATI member institutions that enroll very high shares of Pell students, and (2) insufficient progress at a set of institutions with lower Pell
  3. Fall 2020 enrollment data for 115 ATI members show a single-year drop of 7,166 Pell students (compared to Fall 2019). Driven in large part by declines in first-time and transfer Pell student enrollment at public institutions, and decreased Pell student retention rates at private
  4. COVID-era declines have nearly returned Pell enrollment levels among ATI members to 2015-16
 
 
 
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