collaboration

How Do You Build a Learner-Centered Ecosystem? — from gettingsmart.com by Bobbi Macdonald and Alin Bennett

Key Points

It’s not just about redesigning public education—it’s about rethinking how, where and with whom learning happens. Communities across the United States are shaping learner-centered ecosystems and gathering insights along the way.
What does it take to build a learner-centered ecosystem? A shared vision. Distributed leadership. Place-based experiences. Repurposed resources. And more. This piece unpacks 10 real-world insights from pilots in action.
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We believe the path forward is through the cultivation of learner-centered ecosystems — adaptive, networked structures that offer a transformed way of organizing, supporting, and credentialing community-wide learning. These ecosystems break down barriers between schools, communities, and industries, creating flexible, real-world learning experiences that tap into the full range of opportunities a community has to offer.

Last year, we announced our Learner-Centered Ecosystem Lab, a collaborative effort to create a community of practice consisting of twelve diverse sites across the country — from the streets of Brooklyn to the mountains of Ojai — that are demonstrating or piloting ecosystemic approaches. Since then, we’ve been gathering together, learning from one another, and facing the challenges and opportunities of trying to transform public education. And while there is still much more work to be done, we’ve begun to observe a deeper pattern language — one that aligns with our ten-point Ecosystem Readiness Framework, and one that, we hope, can help all communities start to think more practically and creatively about how to transform their own systems of learning.

So while it’s still early, we suspect that the way to establish a healthy learner-centered ecosystem is by paying close attention to the following ten conditions:

Cultivating a responsible innovation mindset among future tech leaders — from timeshighereducation.com by Andreas Alexiou from the University of Southampton
The classroom is a perfect place to discuss the messy, real-world consequences of technological discoveries, writes Andreas Alexiou. Beyond ‘How?’, students should be asking ‘Should we…?’ and ‘What if…?’ questions around ethics and responsibility

University educators play a crucial role in guiding students to think about the next big invention and its implications for privacy, the environment and social equity. To truly make a difference, we need to bring ethics and responsibility into the classroom in a way that resonates with students. Here’s how.

Debating with industry pioneers on incorporating ethical frameworks in innovation, product development or technology adoption is eye-opening because it can lead to students confronting assumptions they hadn’t questioned before.
…
Students need more than just skills; they need a mindset that sticks with them long after graduation. By making ethics and responsibility a key part of the learning process, educators are doing more than preparing students for a career; they’re preparing them to navigate a world shaped by their choices.

Talk to Me: NVIDIA and Partners Boost People Skills and Business Smarts for AI Agents — from blogs.nvidia.com by Adel El Hallak
NVIDIA Enterprise AI Factory validated design and latest NVIDIA AI Blueprints help businesses add intelligent AI teammates that can speak, research and learn to their daily operations.

Call it the ultimate proving ground. Collaborating with teammates in the modern workplace requires fast, fluid thinking. Providing insights quickly, while juggling webcams and office messaging channels, is a startlingly good test, and enterprise AI is about to pass it — just in time to provide assistance to busy knowledge workers.

To support enterprises in boosting productivity with AI teammates, NVIDIA today introduced a new NVIDIA Enterprise AI Factory validated design at COMPUTEX. IT teams deploying and scaling AI agents can use the design to build accelerated infrastructure and easily integrate with platforms and tools from NVIDIA software partners.

NVIDIA also unveiled new NVIDIA AI Blueprints to aid developers building smart AI teammates. Using the new blueprints, developers can enhance employee productivity through adaptive avatars that understand natural communication and have direct access to enterprise data.

NVIDIA CEO Envisions AI Infrastructure Industry Worth ‘Trillions of Dollars’ — from blogs.nvidia.com by Brian Caulfield
In his COMPUTEX keynote, Huang unveiled a sweeping vision for an AI-powered future, showcasing new platforms and partnerships.

“AI is now infrastructure, and this infrastructure, just like the internet, just like electricity, needs factories,” Huang said. “These factories are essentially what we build today.”

“They’re not data centers of the past,” Huang added. “These AI data centers, if you will, are improperly described. They are, in fact, AI factories. You apply energy to it, and it produces something incredibly valuable, and these things are called tokens.”

More’s coming, Huang said, describing the growing power of AI to reason and perceive. That leads us to agentic AI — AI able to understand, think and act. Beyond that is physical AI — AI that understands the world. The phase after that, he said, is general robotics.

Everything Revealed at Nvidia’s 2025 Computex Press Conference in 19 Minutes — from mashable.com
Nvidia is creating Omniverse Digital Twins of factories including humanoid robots

Watch all the biggest announcements from Nvidia’s keynote address at Computex 2025 in Taipei, Taiwan.

Dell unveils new AI servers powered by Nvidia chips to boost enterprise adoption — from reuters.com

May 19 (Reuters) – Dell Technologies (DELL.N), opens new tab on Monday unveiled new servers powered by Nvidia’s (NVDA.O), opens new tab Blackwell Ultra chips, aiming to capitalize on the booming demand for artificial intelligence systems.

The servers, available in both air-cooled and liquid-cooled variations, support up to 192 Nvidia Blackwell Ultra chips but can be customized to include as many as 256 chips.

Nvidia announces humanoid robotics, custom AI infrastructure tech at Computex 2025 — from finance.yahoo.com by Daniel Howley

Nvidia (NVDA) rolled into this year’s Computex Taipei tech expo on Monday with several announcements, ranging from the development of humanoid robots to the opening up of its high-powered NVLink technology, which allows companies to build semi-custom AI servers with Nvidia’s infrastructure.
…
During the event on Monday, Nvidia revealed its Nvidia Isaac GR00T-Dreams, which the company says helps developers create enormous amounts of training data they can use to teach robots how to perform different behaviors and adapt to new environments.

Addendums on 5/22/25:

? BREAKING: NVIDIA JUST announced roadmap for physical AI, robotics and national-scale AI factories.

Here’s a breakdown of the top important announcements: ??

1. DeepSeek R1 is now 4x faster, setting the standard for AI in inference and reasoning. pic.twitter.com/FOirPFNrU2

— Shruti (@heyshrutimishra) May 19, 2025

Stop Trying to Make Everyone Go to College — from nytimes.com by Randi Weingarten; this is a gifted article

For years, America’s approach to education has been guided by an overly simplistic formula: 4+4 — the idea that students need four years of high school and four years of college to succeed in life.

Even with this prevailing emphasis on college, around 40 percent of high schoolers do not enroll in college upon graduating, and only 60 percent of students who enroll in college earn a degree or credential within eight years of high school graduation.

While college completion has positive effects — on health, lifetime earnings, civic engagement and even happiness — it’s increasingly clear that college for all should no longer be our North Star. It’s time to scale up successful programs that create multiple pathways for students so high school is a gateway to both college and career.

I propose a different strategy: aligning high school to both college prep and in-demand vocational career pathways. Just as students who plan to go to college can get a head start through Advanced Placement programs, high schools, colleges and employers should work together to provide the relevant coursework to engage students in promising career opportunities.

2025: The Year the Frontier Firm Is Born — from Microsoft

We are entering a new reality—one in which AI can reason and solve problems in remarkable ways. This intelligence on tap will rewrite the rules of business and transform knowledge work as we know it. Organizations today must navigate the challenge of preparing for an AI-enhanced future, where AI agents will gain increasing levels of capability over time that humans will need to harness as they redesign their business. Human ambition, creativity, and ingenuity will continue to create new economic value and opportunity as we redefine work and workflows.

As a result, a new organizational blueprint is emerging, one that blends machine intelligence with human judgment, building systems that are AI-operated but human-led. Like the Industrial Revolution and the internet era, this transformation will take decades to reach its full promise and involve broad technological, societal, and economic change.

To help leaders understand how knowledge work will evolve, Microsoft analyzed survey data from 31,000 workers across 31 countries, LinkedIn labor market trends, and trillions of Microsoft 365 productivity signals. We also spoke with AI-native startups, academics, economists, scientists, and thought leaders to explore what work could become. The data and insights point to the emergence of an entirely new organization, a Frontier Firm that looks markedly different from those we know today. Structured around on-demand intelligence and powered by “hybrid” teams of humans + agents, these companies scale rapidly, operate with agility, and generate value faster.

Frontier Firms are already taking shape, and within the next 2–5 years we expect that every organization will be on their journey to becoming one. 82% of leaders say this is a pivotal year to rethink key aspects of strategy and operations, and 81% say they expect agents to be moderately or extensively integrated into their company’s AI strategy in the next 12–18 months. Adoption is accelerating: 24% of leaders say their companies have already deployed AI organization-wide, while just 12% remain in pilot mode.

The time to act is now. The question for every leader and employee is: how will you adapt?

On a somewhat related note, also see:

Exclusive: Anthropic warns fully AI employees are a year away — from axios.com by Sam Sabin

Anthropic expects AI-powered virtual employees to begin roaming corporate networks in the next year, the company’s top security leader told Axios in an interview this week.

Why it matters: Managing those AI identities will require companies to reassess their cybersecurity strategies or risk exposing their networks to major security breaches.

The big picture: Virtual employees could be the next AI innovation hotbed, Jason Clinton, the company’s chief information security officer, told Axios.

Bob Ambrogi posts several solid items re: legaltech & legal education

On 04/17/2025, in Access to Justice (A2J), Artificial Intelligence/Agents/LLMs/and Related, collaboration, Europe, innovation, intelligent systems, law schools, legal reform, legal technologies, legislatures / government / legal, research, United States, user experience (UX), vendors, by Daniel Christian

Thomson Reuters Survey: Over 95% of Legal Professionals Expect Gen AI to Become Central to Workflow Within Five Year — from lawnext.com by Bob Ambrogi

Thomson Reuters today released its 2025 Generative AI in Professional Services Report, and it reveals that legal professionals have become increasingly optimistic about generative AI, with adoption rates nearly doubling over the past year and a growing belief that the technology should be incorporated into legal work.

According to the report, 26% of legal organizations are now actively using gen AI, up from 14% in 2024. While only 15% of law firm respondents say gen AI is currently central to their workflow, a striking 78% believe it will become central within the next five years.

AI-Powered Legal Work Redefined: Libra Launches Major Update for Legal Professionals — from lawnext.com by Bob Ambrogi

Berlin, April 14, 2025 – Berlin-based Legal Tech startup Libra is launching its most comprehensive update to date, leveraging AI to relieve law firms and legal departments of routine tasks, accelerate research, and improve team collaboration. “Libra v2” combines highly developed AI, a modern user interface, and practical tools to set a new standard for efficient and precise work in all legal areas.

“We listened intently to feedback from law firms and in-house teams,” said Viktor von Essen, founder of Libra. “The result is Libra v2: an AI solution that intelligently supports every step of daily legal work – from initial research to final contract review. We want legal experts to be able to fully concentrate on what is essential: excellent legal advice.”

The Three Cs of Teaching Technology to Law Students — from lawnext.com by Bob Ambrogi

In law practice today, technology is no longer optional — it’s essential. As practicing attorneys increasingly rely on technology tools to serve clients, conduct research, manage documents and streamline workflows, the question is often debated: Are law schools adequately preparing students for this reality?

Unfortunately, for the majority of law schools, the answer is no. But that only begs the question: What should they be doing?

A coincidence of events last week had me thinking about law schools and legal tech, chief among them my attendance at LIT Con, Suffolk Law School’s annual conference to showcase legal innovation and technology — with a portion of it devoted to access-to-justice projects developed by Suffolk Law students themselves.

While not from Bob, I’m also going to include this one here:

Your AI Options: 7 Considerations Before You Buy — from artificiallawyer.com by Liza Pestillos-Ocat

But here’s the problem: not all AI is useful and not all of it is built for the way your legal team works.

Most firms aren’t asking whether they should use AI because they already are. The real question now is what comes next? How do you expand the value of AI across more teams, more matters, and more workflows without introducing unnecessary risk, complexity, or cost?

To get this right, legal professionals need to understand which tools will solve real problems and deliver the most value to their team. That starts with asking better questions, including the ones that follow, before making your next investment in AI for lawyers.

Organizing Teams for Continuous Learning: A Complete Guide [intelligentHQ]

On 04/16/2025, in business, collaboration, communications, corporate / business world, corporate universities / corporate training, training / L&D, using teams, vendors, by Daniel Christian

Organizing Teams for Continuous Learning: A Complete Guide — from intelligenthq.com

In today’s fast-paced business world, continuous learning has become a vital element for both individual and organizational growth. Teams that foster a culture of learning remain adaptable, innovative, and competitive. However, simply encouraging learning isn’t enough; the way teams are structured and supported plays a huge role in achieving long-term success. In this guide, we’ll explore how to effectively organize teams for continuous learning, leveraging tools, strategies, and best practices.

Reflections on “Are You Ready for the AI University? Everything is about to change.” [Latham]

On 04/10/2025, in 21st century, 24x7x365 access, accreditation, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, assessment, Blockchain, bots, career development, change, changing business models, cloud-based computing / apps / other cloud-related, CMS/LMS, collaboration, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, cost of getting a degree, credentialing, culture, curriculum, dangers of the status quo, Daniel S. Christian, data related items, Design Thinking, digital learning, disruption, education technology, emerging technologies, Emotion, engagement / engaging students, expectations, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, global / globalization, Google, higher education, human-computer interaction (HCI), IBM, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, leadership, learner profiles, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, learning spaces, liberal arts, lifelong learning, MBA, Michigan, new business models, online learning, online media, online tutoring, organizational change, pace of change, pedagogy, personalized/customized learning, platforms, productivity / tips and tricks, professional development, reinvent, skills, society, staying relevant, strategy, student-related, surviving, teaching & learning, technologies for your home, tools, trends, United States, universities, usability, user experience (UX), virtual tutoring, vision/possibilities, web-based collaboration, workplace, by Daniel Christian

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Are You Ready for the AI University? Everything is about to change. — from chronicle.com by Scott Latham

Over the course of the next 10 years, AI-powered institutions will rise in the rankings. US News & World Report will factor a college’s AI capabilities into its calculations. Accrediting agencies will assess the degree of AI integration into pedagogy, research, and student life. Corporations will want to partner with universities that have demonstrated AI prowess. In short, we will see the emergence of the AI haves and have-nots.
…
What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.
…
Out of the gate, professors will work with technologists to get AI up to speed on specific disciplines and pedagogy. For example, AI could be “fed” course material on Greek history or finance and then, guided by human professors as they sort through the material, help AI understand the structure of the discipline, and then develop lectures, videos, supporting documentation, and assessments.
…
In the near future, if a student misses class, they will be able watch a recording that an AI bot captured. Or the AI bot will find a similar lecture from another professor at another accredited university. If you need tutoring, an AI bot will be ready to help any time, day or night. Similarly, if you are going on a trip and wish to take an exam on the plane, a student will be able to log on and complete the AI-designed and administered exam. Students will no longer be bound by a rigid class schedule. Instead, they will set the schedule that works for them.

Early and mid-career professors who hope to survive will need to adapt and learn how to work with AI. They will need to immerse themselves in research on AI and pedagogy and understand its effect on the classroom.

From DSC:
I had a very difficult time deciding which excerpts to include. There were so many more excerpts for us to think about with this solid article. While I don’t agree with several things in it, EVERY professor, president, dean, and administrator working within higher education today needs to read this article and seriously consider what Scott Latham is saying.

Change is already here, but according to Scott, we haven’t seen anything yet. I agree with him and, as a futurist, one has to consider the potential scenarios that Scott lays out for AI’s creative destruction of what higher education may look like. Scott asserts that some significant and upcoming impacts will be experienced by faculty members, doctoral students, and graduate/teaching assistants (and Teaching & Learning Centers and IT Departments, I would add). But he doesn’t stop there. He brings in presidents, deans, and other members of the leadership teams out there.

There are a few places where Scott and I differ.

The foremost one is the importance of the human element — i.e., the human faculty member and students’ learning preferences. I think many (most?) students and lifelong learners will want to learn from a human being. IBM abandoned their 5-year, $100M ed push last year and one of the key conclusions was that people want to learn from — and with — other people:

To be sure, AI can do sophisticated things such as generating quizzes from a class reading and editing student writing. But the idea that a machine or a chatbot can actually teach as a human can, he said, represents “a profound misunderstanding of what AI is actually capable of.”

Nitta, who still holds deep respect for the Watson lab, admits, “We missed something important. At the heart of education, at the heart of any learning, is engagement. And that’s kind of the Holy Grail.”

— Satya Nitta, a longtime computer researcher at
IBM’s Watson Research Center in Yorktown Heights, NY
.

By the way, it isn’t easy for me to write this. As I wanted AI and other related technologies to be able to do just what IBM was hoping that it would be able to do.

Also, I would use the term learning preferences where Scott uses the term learning styles.

Scott also mentions:

“In addition, faculty members will need to become technologists as much as scholars. They will need to train AI in how to help them build lectures, assessments, and fine-tune their classroom materials. Further training will be needed when AI first delivers a course.”

It has been my experience from working with faculty members for over 20 years that not all faculty members want to become technologists. They may not have the time, interest, and/or aptitude to become one (and vice versa for technologists who likely won’t become faculty members).

That all said, Scott relays many things that I have reflected upon and relayed for years now via this Learning Ecosystems blog and also via The Learning from the Living [AI-Based Class] Room vision — the use of AI to offer personalized and job-relevant learning, the rising costs of higher education, the development of new learning-related offerings and credentials at far less expensive prices, the need to provide new business models and emerging technologies that are devoted more to lifelong learning, plus several other things.

So this article is definitely worth your time to read, especially if you are working in higher education or are considering a career therein!

Addendum later on 4/10/25:

U-M’s Ross School of Business, Google Public Sector launch virtual teaching assistant pilot program — from news.umich.edu by Jeff Karoub; via Paul Fain

Google Public Sector and the University of Michigan’s Ross School of Business have launched an advanced Virtual Teaching Assistant pilot program aimed at improving personalized learning and enlightening educators on artificial intelligence in the classroom.

The AI technology, aided by Google’s Gemini chatbot, provides students with all-hours access to support and self-directed learning. The Virtual TA represents the next generation of educational chatbots, serving as a sophisticated AI learning assistant that instructors can use to modify their specific lessons and teaching styles.

The Virtual TA facilitates self-paced learning for students, provides on-demand explanations of complex course concepts, guides them through problem-solving, and acts as a practice partner. It’s designed to foster critical thinking by never giving away answers, ensuring students actively work toward solutions.

The 2025 AI Index Report [Stanford University]

On 04/09/2025, in 21st century, 24x7x365 access, Africa, Artificial Intelligence/Agents/LLMs/and Related, Asia, bots, business, Canada, change, changing business models, cloud-based computing / apps / other cloud-related, collaboration, communities of practice, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, economics, education, education technology, emerging technologies, ethics, Europe, experimentation, faculty/staff, future, game-changing environment, global / globalization, health, human-computer interaction (HCI), innovation, intelligent systems, learning ecosystem, legislatures / government / legal, mathematics, morals/values, platforms, policy, research, science, society, trends, United States, universities, workplace, by Daniel Christian

The 2025 AI Index Report — from Stanford University’s Human-Centered Artificial Intelligence Lab (hai.stanford.edu); item via The Neuron

Top Takeaways

AI performance on demanding benchmarks continues to improve.
AI is increasingly embedded in everyday life.
Business is all in on AI, fueling record investment and usage, as research continues to show strong productivity impacts.
The U.S. still leads in producing top AI models—but China is closing the performance gap.
The responsible AI ecosystem evolves—unevenly.
Global AI optimism is rising—but deep regional divides remain.
…and several more

Also see:

12 Graphs That Explain the State of AI in 2025 — from by Eliza Strickland; item via The Neuron
Stanford’s AI Index tracks performance, investment, public opinion, and more

The Neuron’s take on this:

So, what should you do? You really need to start trying out these AI tools. They’re getting cheaper and better, and they can genuinely help save time or make work easier—ignoring them is like ignoring smartphones ten years ago.

Just keep two big things in mind:

Making the next super-smart AI costs a crazy amount of money and uses tons of power (seriously, they’re buying nuclear plants and pushing coal again!).
Companies are still figuring out how to make AI perfectly safe and fair—cause it still makes mistakes.

So, use the tools, find what helps you, but don’t trust them completely.

We’re building this plane mid-flight, and Stanford’s report card is just another confirmation that we desperately need better safety checks before we hit major turbulence.

Addendum on 4/16:

Is collaboration the key to digital accessibility? [Jarvis & Rhodes]

On 04/08/2025, in accessibility / UDL, assistive technologies, Bias | Diversity Equity & Inclusion (DE&I), collaboration, communications, consortiums, neurodivergent/special needs, UK, universities, web design and production, by Daniel Christian

Is collaboration the key to digital accessibility? — from timeshighereducation.com by Sal Jarvis and George Rhodes
Digital accessibility is ethically important, and a legal requirement, but it’s also a lot of work. Here’s how universities can collaborate and pool their expertise to make higher education accessible for all

How easy do you find it to navigate your way around your university’s virtual estate – its websites, virtual learning environment and other digital aspects? If the answer is “not very”, we suspect you may not be alone. And for those of us who might access it differently – without a mouse, for example, or through a screen reader or keyboard emulator – the challenge is multiplied. Digital accessibility is the wide-ranging work to make these challenges a thing of the past for everyone. It is a legal requirement and a moral imperative.

Make Things Accessible is the outcome of a collaboration, initially between the University of Westminster and UCL, but now incorporating many other universities. It is a community of practice, a website and an archive of resources. It aims to make things accessible for all.

Essential AI tools for better work — from wondertools.substack.com by Jeremy Caplan
My favorite tactics for making the most of AI — a podcast conversation

AI tools I consistently rely on (areas covered mentioned below)

Research and analysis
Communication efficiency
Multimedia creation

AI tactics that work surprisingly well

1. Reverse interviews
Instead of just querying AI, have it interview you. Get the AI to interview you, rather than interviewing it. Give it a little context and what you’re focusing on and what you’re interested in, and then you ask it to interview you to elicit your own insights.”

This approach helps extract knowledge from yourself, not just from the AI. Sometimes we need that guide to pull ideas out of ourselves.

OpenAI’s Deep Research Agent Is Coming for White-Collar Work — from wired.com by Will Knight
The research-focused agent shows how a new generation of more capable AI models could automate some office tasks.

Isla Fulford, a researcher at OpenAI, had a hunch that Deep Research would be a hit even before it was released.

Fulford had helped build the artificial intelligence agent, which autonomously explores the web, deciding for itself what links to click, what to read, and what to collate into an in-depth report. OpenAI first made Deep Research available internally; whenever it went down, Fulford says, she was inundated with queries from colleagues eager to have it back. “The number of people who were DMing me made us pretty excited,” says Fulford.

Since going live to the public on February 2, Deep Research has proven to be a hit with many users outside the company too.

Nvidia to open quantum computing research center in Boston — from seekingalpha.com by Ravikash Bakolia

Nvidia (NASDAQ:NVDA) will open a quantum computing research lab in Boston which is expected to start operations later this year.

The Nvidia Accelerated Quantum Research Center, or NVAQC, will integrate leading quantum hardware with AI supercomputers, enabling what is known as accelerated quantum supercomputing, said the company in a March 18 press release.

Nvidia’s CEO Jensen Huang also made this announcement on Thursday at the company’s first-ever Quantum Day at its annual GTC event.

French quantum computer firm Pasqal links up with NVIDIA — from reuters.com

PARIS, March 21 (Reuters) – Pasqal, a fast-growing French quantum computer start-up company, announced on Friday a partnership with chip giant Nvidia (NVDA.O), opens new tab whereby Pasqal’s customers would gain access to more tools to develop quantum applications.

Pasqal said it would connect its quantum computing units and cloud platform onto NVIDIA’s open-source platform called CUDA-Q.

Introducing next-generation audio models in the API — from openai.com
A new suite of audio models to power voice agents, now available to developers worldwide.

Today, we’re launching new speech-to-text and text-to-speech audio models in the API—making it possible to build more powerful, customizable, and intelligent voice agents that offer real value. Our latest speech-to-text models set a new state-of-the-art benchmark, outperforming existing solutions in accuracy and reliability—especially in challenging scenarios involving accents, noisy environments, and varying speech speeds. These improvements increase transcription reliability, making the models especially well-suited for use cases like customer call centers, meeting note transcription, and more.

AI Can’t Fix Bad Learning — from nafez.substack.com by Nafez Dakkak
Why pedagogy and good learning design still come first, and why faster isn’t always better.

I’ve followed Dr. Philippa Hardman’s work for years, and every time I engage with her work, I find it both refreshing and deeply grounded.

As one of the leading voices in learning design, Philippa has been able to cut through the noise and focus on what truly matters: designing learning experiences that actually work.

In an era where AI promises speed and scale, Philippa is making a different argument: faster isn’t always better. As the creator of Epiphany AI—figma for learning designers—Philippa is focused on closing the gap between what great learning design should look like and what’s actually being delivered.

While many AI tools optimize for the average, she believes the future belongs to those who can leverage AI without compromising on expertise or quality. Philippa wants learning designers to be more ambitious using AI to achieve what wasn’t possible before.

In this conversation, we explore why pedagogy must lead technology, how the return on expertise is only increasing in an AI-driven world, and why building faster doesn’t always mean building better.

An excerpted graphic:

Pearson, AWS Collaborate to Enhance AI-Powered Learning Functionality — from cloudwars.com

Pearson, the global educational publisher, and AWS have expanded their existing partnership to enhance AI-driven learning. AWS will help Pearson to deliver AI-powered lesson generation and more for educators, support workforce skilling initiatives, and continue an ongoing collaboration with Pearson VUE for AWS certification.

Introducing NextGenAI: A consortium to advance research and education with AI — from openai.com; via Claire Zau
OpenAI commits $50M in funding and tools to leading institutions.

Today, we’re launching NextGenAI, a first-of-its-kind consortium with 15 leading research institutions dedicated to using AI to accelerate research breakthroughs and transform education.

AI has the power to drive progress in research and education—but only when people have the right tools to harness it. That’s why OpenAI is committing $50M in research grants, compute funding, and API access to support students, educators, and researchers advancing the frontiers of knowledge.

Uniting institutions across the U.S. and abroad, NextGenAI aims to catalyze progress at a rate faster than any one institution would alone. This initiative is built not only to fuel the next generation of discoveries, but also to prepare the next generation to shape AI’s future.

‘I want him to be prepared’: why parents are teaching their gen Alpha kids to use AI — from theguardian.com by Aaron Mok; via Claire Zau
As AI grows increasingly prevalent, some are showing their children tools from ChatGPT to Dall-E to learn and bond

“My goal isn’t to make him a generative AI wizard,” White said. “It’s to give him a foundation for using AI to be creative, build, explore perspectives and enrich his learning.”

White is part of a growing number of parents teaching their young children how to use AI chatbots so they are prepared to deploy the tools responsibly as personal assistants for school, work and daily life when they’re older.

ABA Tech Survey Finds Growing Adoption of AI in Legal Practice, with Efficiency Gains as Primary Driver [Ambrogi]

On 03/08/2025, in Artificial Intelligence/Agents/LLMs/and Related, change, changing business models, collaboration, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, new business models, productivity / tips and tricks, United States, by Daniel Christian

ABA Tech Survey Finds Growing Adoption of AI in Legal Practice, with Efficiency Gains as Primary Driver — from lawnext.com by Bob Ambrogi

There has been a significant increase in the adoption of artificial intelligence-based tools among law firms, with 30% of respondents now using AI technology compared to just 11% in 2023, according to the just-released 2024 edition of the American Bar Association’s Legal Technology Survey Report.

It finds that time savings and increased efficiency remain the dominant perceived benefits of AI implementation in legal practice.

The report, published Wednesday by the ABA’s Legal Technology Resource Center, is based on a survey that gathered responses from 512 attorneys in private practice across various firm sizes.

Also re: the legal world:

Why The GC-Legal Ops Partnership Is More Critical Than Ever — from abovethelaw.com by Stephanie Corey
The future of in-house legal isn’t about working in silos — it’s about working together.

AI is rapidly changing the way legal work gets done. Legal Ops can help GCs navigate this shift — identifying the right tools, ensuring responsible AI adoption, and optimizing processes so legal teams can focus on high-value work.

Several items re: teaching and learning within K-12 [edutopia.org]

On 03/08/2025, in collaboration, education, Emotion, engagement / engaging students, ideas, instructional design, K-12 related, learning, learning ecosystem, Learning Experience Design, participation, pedagogy, student-related, teachers, teaching & learning, United States, youth, by Daniel Christian

All of the articles listed below are from edutopia.org

4 Ways to Boost Students’ Self-Efficacy — by Tyler Rablin
These strategies help students see what they have learned so they believe they can be successful in school in the future.

Self-efficacy, on the other hand, focuses on outcomes to drive beliefs. In essence, self-efficacy involves intentionally providing students with evidence of early success to help them build the belief that they can be successful in the future.

Self-efficacy has been a powerful focus for me because it helps me to be more intentional as a teacher. It requires me to be mindful of how I structure assessments, feedback, etc., to provide students with evidence of their successes early on to help them see potential future successes.

Maintaining Students’ Focus in the Spring — by Miriam Plotinsky
Teachers can use these small ‘upgrades’ or tweaks to their regular practices to help keep students focused and involved.

As a recent MindShift article notes, “The second semester brings a lot of potential challenges to teachers’ regularly scheduled programming because of standardized testing, graduation events, and student burnout.” These challenges may be complex, but they are not insurmountable. With subtle shifts in practice, classrooms can remain safe and productive spaces—even in the spring.

She recommends a “coping jar” to help students identify moments of angst and manage their feelings. Fagell explains that when students find an effective coping mechanism, they write their idea on one side of a Popsicle stick and explain how it works on the other side. As students add ideas to the jar, they have an increased awareness of coping strategies and the importance of helping one another.

10 Picture Books That Showcase Collaboration — by Kristin Rydholm
These entertaining stories feature collaboration and social-emotional skills to highlight the benefit of working together to accomplish a goal.

Are you an early childhood teacher in search of relationship-building resources to help unify your classroom? Have I got a book list for you! In the verbiage of 1970s infomercials: “This collection has everything!” The main characters are early childhood students, the setting is the school, and each plot requires the class to work collaboratively. The characters are united in curiosity, determination, and mission to work on accomplishing projects together that they couldn’t possibly do alone.

What a 30-Day Break From AI Taught Me About My Teaching — by James Bedford
Using AI became second nature for this educator. A month without the tools gave him an opportunity to pause, reflect, and recalibrate.

My goal is to try to preserve the messy, creative core of what it means to be an educator: curiosity, critical thinking, and the grit and energy to solve problems without always resorting to shortcuts—technological or otherwise. My hope is that my students will do the same.

Unplug and reconnect: Challenge yourself and your students to embark on an AI detox. Step away from AI tools where possible, and rediscover the power of human creativity and independent thought. Start a journal to document the journey, exploring questions like “How does it feel to rely solely on my own intellect?” or “What challenges arise when AI isn’t there to assist?” This activity can foster resilience, raise self-awareness, and cultivate a deeper appreciation for the human capacity to think, create, problem-solve, and innovate.

Learning Ecosystems

Organizing Teams for Continuous Learning: A Complete Guide [intelligentHQ]

Is collaboration the key to digital accessibility? [Jarvis & Rhodes]

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