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“Leadership & Generative AI: Hard-Earned Lessons That Matter” [Klitgaard Stricker] + other items re: AI in our learning ecosystems

On 01/22/2025, in 21st century, 24x7x365 access, adjunct faculty, adult learning, Artificial Intelligence/Agents/LLMs/and Related, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, leadership, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, library / librarians, lifelong learning, Michigan, microlearning, multimedia, Natural Language Processing (NLP), personalized/customized learning, platforms, productivity / tips and tricks, reading, research, strategy, student-related, teachers, teaching & learning, technologies for your home, tools, training / L&D, trends, United States, universities, vendors, writing, by Daniel Christian

Your AI Writing Partner: The 30-Day Book Framework — from aidisruptor.ai by Alex McFarland and Kamil Banc
How to Turn Your “Someday” Manuscript into a “Shipped” Project Using AI-Powered Prompts

With that out of the way, I prefer Claude.ai for writing. For larger projects like a book, create a Claude Project to keep all context in one place.

  • Copy [the following] prompts into a document
  • Use them in sequence as you write
  • Adjust the word counts and specifics as needed
  • Keep your responses for reference
  • Use the same prompt template for similar sections to maintain consistency

Each prompt builds on the previous one, creating a systematic approach to helping you write your book.

Using NotebookLM to Boost College Reading Comprehension — from michellekassorla.substack.com by Michelle Kassorla and Eugenia Novokshanova
This semester, we are using NotebookLM to help our students comprehend and engage with scholarly texts

We were looking hard for a new tool when Google released NotebookLM. Not only does Google allow unfettered use of this amazing tool, it is also a much better tool for the work we require in our courses. So, this semester, we have scrapped our “old” tools and added NotebookLM as the primary tool for our English Composition II courses (and we hope, fervently, that Google won’t decide to severely limit its free tier before this semester ends!)

If you know next-to-nothing about NotebookLM, that’s OK. What follows is the specific lesson we present to our students. We hope this will help you understand all you need to know about NotebookLM, and how to successfully integrate the tool into your own teaching this semester.

Leadership & Generative AI: Hard-Earned Lessons That Matter — from jeppestricker.substack.com by Jeppe Klitgaard Stricker
Actionable Advice for Higher Education Leaders in 2025

AFTER two years of working closely with leadership in multiple institutions, and delivering countless workshops, I’ve seen one thing repeatedly: the biggest challenge isn’t the technology itself, but how we lead through it. Here is some of my best advice to help you navigate generative AI with clarity and confidence:

  1. Break your own AI policies before you implement them. …
  2. Fund your failures. …
  3. Resist the pilot program. …
  4. Host Anti-Tech Tech Talks …
  5. …+ several more tips

While generative AI in higher education obviously involves new technology, it’s much more about adopting a curious and human-centric approach in your institution and communities. It’s about empowering learners in new, human-oriented and innovative ways. It is, in a nutshell, about people adapting to new ways of doing things.

Maria Anderson responded to Clay’s posting with this idea:

Here’s an idea: […] the teacher can use the [most advanced] AI tool to generate a complete solution to “the problem” — whatever that is — and demonstrate how to do that in class. Give all the students access to the document with the results.

And then grade the students on a comprehensive followup activity / presentation of executing that solution (no notes, no more than 10 words on a slide). So the students all have access to the same deep AI result, but have to show they comprehend and can iterate on that result.

Grammarly just made it easier to prove the sources of your text in Google Docs — from zdnet.com by Jack Wallen
If you want to be diligent about proving your sources within Google Documents, Grammarly has a new feature you’ll want to use.

In this age of distrust, misinformation, and skepticism, you may wonder how to demonstrate your sources within a Google Document. Did you type it yourself, copy and paste it from a browser-based source, copy and paste it from an unknown source, or did it come from generative AI?

You may not think this is an important clarification, but if writing is a critical part of your livelihood or life, you will definitely want to demonstrate your sources.

That’s where the new Grammarly feature comes in.

The new feature is called Authorship, and according to Grammarly, “Grammarly Authorship is a set of features that helps users demonstrate their sources of text in a Google doc. When you activate Authorship within Google Docs, it proactively tracks the writing process as you write.”

AI Agents Are Coming to Higher Education — from govtech.com
AI agents are customizable tools with more decision-making power than chatbots. They have the potential to automate more tasks, and some schools have implemented them for administrative and educational purposes.

Custom GPTs are on the rise in education. Google’s version, Gemini Gems, includes a premade version called Learning Coach, and Microsoft announced last week a new agent addition to Copilot featuring use cases at educational institutions.

Generative Artificial Intelligence and Education: A Brief Ethical Reflection on Autonomy — from er.educause.edu by Vicki Strunk and James Willis
Given the widespread impacts of generative AI, looking at this technology through the lens of autonomy can help equip students for the workplaces of the present and of the future, while ensuring academic integrity for both students and instructors.

The principle of autonomy stresses that we should be free agents who can govern ourselves and who are able to make our own choices. This principle applies to AI in higher education because it raises serious questions about how, when, and whether AI should be used in varying contexts. Although we have only begun asking questions related to autonomy and many more remain to be asked, we hope that this serves as a starting place to consider the uses of AI in higher education.

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‘Lazy and Mediocre’ HR Team Fired After Manager’s Own CV Gets Auto-Rejected in Seconds, Exposing System Failure

On 01/21/2025, in Artificial Intelligence/Agents/LLMs/and Related, Bias | Diversity Equity & Inclusion (DE&I), business, career development, corporate / business world, Daniel S. Christian, intelligent systems, IT in HE, UK, United States, workplace, by Daniel Christian

‘Lazy and Mediocre’ HR Team Fired After Manager’s Own CV Gets Auto-Rejected in Seconds, Exposing System Failure — from ibtimes.co.uk by Vinay Patel
The automated system’s error highlights the potential for bias and inefficiency in technology-driven HR practices

An entire HR team was terminated after their manager discovered and confirmed that their system automatically rejected all candidates — including his own application.

The manager wrote in their comment, “Auto rejection systems from HR make me angry.” They explained that while searching for a new employee, their HR department could not find a single qualified candidate in three months. As expected, the suspicious manager decided to investigate.

“I created myself a new email and sent them a modified version of my CV with a fake name to see what was going on with the process,” they wrote. “And guess what, I got auto-rejected. HR didn’t even look at my CV.”

When the manager reported the issue to upper management, “half of the HR department was fired in the following weeks.” A typographical error with significant consequences caused the entire problem.

The manager works in the tech industry and was trying to hire developers. However, HR had set up the system to search for developers with expertise in the wrong development software and one that no longer exists.

From DSC:
Back in 2017, I had survived several rounds of layoffs at the then Calvin College (now Calvin University) but I didn’t survive the layoff of 12 people in the spring of 2017. I hadn’t needed to interview for a new job in quite a while. So boy, did I get a wake-up call with discovering that Applicant Tracking Systems existed and could be tough to get past. (Also, the old-school job replacement firm that Calvin hired wasn’t much help in dealing with them either.)

I didn’t like these ATSs then, and I still have my concerns about them now. The above article points out that my concerns were/are at least somewhat founded. And if you take the entire day to research and apply for a position — only to get an instant reply back from the ATS — it’s very frustrating and discouraging. 

Plus the ATSs may not pick up on nuances. An experienced human being might be able to see that a candidate’s skills are highly relevant and/or transferable to the position that they’re hiring for. 

Networking is key of course. But not everyone has been taught about networking and not everyone gets past the ATS to get their resume viewed by a pair of human eyes. HR, IT, and any other relevant groups here need to be very careful with programming their ATSs.

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“AI tutoring shows stunning results” [World Bank] + “AI Is Unavoidable, Not Inevitable.” [Watkins]

On 01/17/2025, in 21st century, adjunct faculty, adult learning, Africa, Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, faculty/staff, future, game-changing environment, higher education, human-computer interaction (HCI), innovation, intelligent systems, intelligent tutoring, K-12 related, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, lifelong learning, teachers, teaching & learning, United States, universities, by Daniel Christian

AI Is Unavoidable, Not Inevitable — from marcwatkins.substack.com by Marc Watkins

I had the privilege of moderating a discussion between Josh Eyler and Robert Cummings about the future of AI in education at the University of Mississippi’s recent AI Winter Institute for Teachers. I work alongside both in faculty development here at the University of Mississippi. Josh’s position on AI sparked a great deal of debate on social media:
…
To make my position clear about the current AI in education discourse I want to highlight several things under an umbrella of “it’s very complicated.”

Most importantly, we all deserve some grace here. Dealing with generative AI in education isn’t something any of us asked for. It isn’t normal. It isn’t fixable by purchasing a tool or telling faculty to simply ‘prefer not to’ use AI. It is and will remain unavoidable for virtually every discipline taught at our institutions.

If one good thing happens because of generative AI let it be that it helps us clearly see how truly complicated our existing relationships with machines are now. As painful as this moment is, it might be what we need to help prepare us for a future where machines that mimic reasoning and human emotion refuse to be ignored.

“AI tutoring shows stunning results.”
See below article.

From chalkboards to chatbots: Transforming learning in Nigeria, one prompt at a time — from blogs.worldbank.org by Martín E. De Simone, Federico Tiberti, Wuraola Mosuro, Federico Manolio, Maria Barron, and Eliot Dikoru

Learning gains were striking
The learning improvements were striking—about 0.3 standard deviations. To put this into perspective, this is equivalent to nearly two years of typical learning in just six weeks. When we compared these results to a database of education interventions studied through randomized controlled trials in the developing world, our program outperformed 80% of them, including some of the most cost-effective strategies like structured pedagogy and teaching at the right level. This achievement is particularly remarkable given the short duration of the program and the likelihood that our evaluation design underestimated the true impact.
…
Our evaluation demonstrates the transformative potential of generative AI in classrooms, especially in developing contexts. To our knowledge, this is the first study to assess the impact of generative AI as a virtual tutor in such settings, building on promising evidence from other contexts and formats; for example, on AI in coding classes, AI and learning in one school in Turkey, teaching math with AI (an example through WhatsApp in Ghana), and AI as a homework tutor.

Comments on this article from The Rundown AI:

Why it matters: This represents one of the first rigorous studies showing major real-world impacts in a developing nation. The key appears to be using AI as a complement to teachers rather than a replacement — and results suggest that AI tutoring could help address the global learning crisis, particularly in regions with teacher shortages.

Other items re: AI in our learning ecosystems:

  • Will AI revolutionise marking? — from timeshighereducation.com by Rohim Mohammed
    Artificial intelligence has the potential to improve speed, consistency and detail in feedback for educators grading students’ assignments, writes Rohim Mohammed. Here he lists the pros and cons based on his experience
  • Marty the Robot: Your Classroom’s AI Companion — from rdene915.com by Dr. Rachelle Dené Poth
  • Generative Artificial Intelligence: Cautiously Recognizing Educational Opportunities — from scholarlyteacher.com by Todd Zakrajsek, University of North Carolina at Chapel Hill
  • Personal AI — from michelleweise.substack.com by Dr. Michelle Weise
    “Personalized” Doesn’t Have To Be a Buzzword
    Today, however, is a different kind of moment. GenAI is now rapidly evolving to the point where we may be able to imagine a new way forward. We can begin to imagine solutions truly tailored for each of us as individuals, our own personal AI (pAI). pAI could unify various silos of information to construct far richer and more holistic and dynamic views of ourselves as long-life learners. A pAI could become our own personal career navigator, skills coach, and storytelling agent. Three particular areas emerge when we think about tapping into the richness of our own data:

    • Personalized Learning Pathways & Dynamic Skill Assessment: …
    • Storytelling for Employers:…
    • Ongoing Mentorship and Feedback: …
  • Speak — a language learning app — via The Neuron

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At least seven items re: AI within our learning ecosystems

On 01/14/2025, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, bots, collaboration, colleges, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, education technology, emerging technologies, ethics, experimentation, faculty/staff, future, game-changing environment, generational differences, Google, India, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, morals/values, NVIDIA, platforms, policy, research, student-related, teachers, teaching & learning, tools, training / L&D, trends, United States, universities, vendors, voice recognition / voice enabled interfaces, by Daniel Christian

Students Pushback on AI Bans, India Takes a Leading Role in AI & Education & Growing Calls for Teacher Training in AI — from learningfuturesdigest.substack.com by Dr. Philippa Hardman
Key developments in the world of AI & Education at the turn of 2025

At the end of 2024 and start of 2025, we’ve witnessed some fascinating developments in the world of AI and education, from from India’s emergence as a leader in AI education and Nvidia’s plans to build an AI school in Indonesia to Stanford’s Tutor CoPilot improving outcomes for underserved students.

Other highlights include Carnegie Learning partnering with AI for Education to train K-12 teachers, early adopters of AI sharing lessons about implementation challenges, and AI super users reshaping workplace practices through enhanced productivity and creativity.

Also mentioned by Philippa:

ElevenLabs AI Voice Tool Review for Educators — from aiforeducation.io with Amanda Bickerstaff and Mandy DePriest

AI for Education reviewed the ElevenLabs AI Voice Tool through an educator lens, digging into the new autonomous voice agent functionality that facilitates interactive user engagement. We showcase the creation of a customized vocabulary bot, which defines words at a 9th-grade level and includes options for uploading supplementary material. The demo includes real-time testing of the bot’s capabilities in defining terms and quizzing users.

The discussion also explored the AI tool’s potential for aiding language learners and neurodivergent individuals, and Mandy presented a phone conversation coach bot to help her 13-year-old son, highlighting the tool’s ability to provide patient, repetitive practice opportunities.

While acknowledging the technology’s potential, particularly in accessibility and language learning, we also want to emphasize the importance of supervised use and privacy considerations. Right now the tool is currently free, this likely won’t always remain the case, so we encourage everyone to explore and test it out now as it continues to develop.

How to Use Google’s Deep Research, Learn About and NotebookLM Together — from ai-supremacy.com by Michael Spencer and Nick Potkalitsky
Supercharging your research with Google Deepmind’s new AI Tools.

Why Combine Them?
Faster Onboarding: Start broad with Deep Research, then refine and clarify concepts through Learn About. Finally, use NotebookLM to synthesize everything into a cohesive understanding.

Deeper Clarity: Unsure about a concept uncovered by Deep Research? Head to Learn About for a primer. Want to revisit key points later? Store them in NotebookLM and generate quick summaries on demand.

Adaptive Exploration: Create a feedback loop. Let new terms or angles from Learn About guide more targeted Deep Research queries. Then, compile all findings in NotebookLM for future reference.
.

Getting to an AI Policy Part 1: Challenges — from aiedusimplified.substack.com by Lance Eaton, PH.D.
Why institutional policies are slow to emerge in higher education

There are several challenges to making policy that make institutions hesitant to or delay their ability to produce it. Policy (as opposed to guidance) is much more likely to include a mixture of IT, HR, and legal services. This means each of those entities has to wrap their heads around GenAI—not just for their areas but for the other relevant areas such as teaching & learning, research, and student support. This process can definitely extend the time it takes to figure out the right policy.

That’s naturally true with every policy. It does not often come fast enough and is often more reactive than proactive.

Still, in my conversations and observations, the delay derives from three additional intersecting elements that feel like they all need to be in lockstep in order to actually take advantage of whatever possibilities GenAI has to offer.

  1. Which Tool(s) To Use
  2. Training, Support, & Guidance, Oh My!
  3. Strategy: Setting a Direction…

Prophecies of the Flood — from oneusefulthing.org by Ethan Mollick
What to make of the statements of the AI labs?

What concerns me most isn’t whether the labs are right about this timeline – it’s that we’re not adequately preparing for what even current levels of AI can do, let alone the chance that they might be correct. While AI researchers are focused on alignment, ensuring AI systems act ethically and responsibly, far fewer voices are trying to envision and articulate what a world awash in artificial intelligence might actually look like. This isn’t just about the technology itself; it’s about how we choose to shape and deploy it. These aren’t questions that AI developers alone can or should answer. They’re questions that demand attention from organizational leaders who will need to navigate this transition, from employees whose work lives may transform, and from stakeholders whose futures may depend on these decisions. The flood of intelligence that may be coming isn’t inherently good or bad – but how we prepare for it, how we adapt to it, and most importantly, how we choose to use it, will determine whether it becomes a force for progress or disruption. The time to start having these conversations isn’t after the water starts rising – it’s now.

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AI educators are coming to this school [Hal Schwartz] + other items re: AI in our learning ecosystems

On 01/07/2025, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, experimentation, faculty/staff, future, future of higher education, game-changing environment, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning spaces, liberal arts, library / librarians, research, society, teachers, teaching & learning, training / L&D, United States, universities, vision/possibilities, by Daniel Christian

AI educators are coming to this school – and it’s part of a trend — from techradar.com by Eric Hal Schwartz
Two hours of lessons, zero teachers

  • An Arizona charter school will use AI instead of human teachers for two hours a day on academic lessons.
  • The AI will customize lessons in real-time to match each student’s needs.
  • The company has only tested this idea at private schools before but claims it hugely increases student academic success.

One school in Arizona is trying out a new educational model built around AI and a two-hour school day. When Arizona’s Unbound Academy opens, the only teachers will be artificial intelligence algorithms in a perfect utopia or dystopia, depending on your point of view.

AI in Instructional Design: reflections on 2024 & predictions for 2025 — from drphilippahardman.substack.com by Dr. Philippa Hardman
Aka, four new year’s resolutions for the AI-savvy instructional designer.

Debating About AI: A Free Comprehensive Guide to the Issues — from stefanbauschard.substack.com by Stefan Bauschard

In order to encourage and facilitate debate on key controversies related to AI, I put together this free 130+ page guide to the main arguments and ideas related to the controversies.

Universities need to step up their AGI game — from futureofbeinghuman.com by Andrew Maynard
As Sam Altman and others push toward a future where AI changes everything, universities need to decide if they’re going to be leaders or bystanders in helping society navigate advanced AI transitions

And because of this, I think there’s a unique opportunity for universities (research universities in particular) to up their game and play a leadership role in navigating the coming advanced AI transition.

Of course, there are already a number of respected university-based initiatives that are working on parts of the challenge. Stanford HAI (Human-centered Artificial Intelligence) is one that stands out, as does the Leverhulm Center for the Future of Intelligence at the University of Cambridge, and the Center for Governance of AI at the University of Oxford. But these and other initiatives are barely scratching the surface of what is needed to help successfully navigate advanced AI transitions.

If universities are to be leaders rather than bystanders in ensuring human flourishing in an age of AI, there’s an urgent need for bolder and more creative forward-looking initiatives that support research, teaching, thought leadership, and knowledge mobilization, at the intersection of advanced AI and all aspects of what it means to thrive and grow as a species.

 

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“5 Ways Teachers Can Use NotebookLM Today” [Burns} + other items re: AI in our learning ecosystems

On 12/29/2024, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, Australia, change, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital audio, digital learning, digital video, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, liberal arts, library / librarians, lifelong learning, Open AI, personalized/customized learning, platforms, productivity / tips and tricks, skills, student-related, teachers, teaching & learning, technologies for your home, the downsides of how people use tech, tools, training / L&D, United States, universities, vendors, vision/possibilities, by Daniel Christian

How AI Is Changing Education: The Year’s Top 5 Stories — from edweek.org by Alyson Klein

Ever since a new revolutionary version of chat ChatGPT became operable in late 2022, educators have faced several complex challenges as they learn how to navigate artificial intelligence systems.
…
Education Week produced a significant amount of coverage in 2024 exploring these and other critical questions involving the understanding and use of AI.

Here are the five most popular stories that Education Week published in 2024 about AI in schools.

What’s next with AI in higher education? — from msn.com by Science X Staff

Dr. Lodge said there are five key areas the higher education sector needs to address to adapt to the use of AI:

1. Teach ‘people’ skills as well as tech skills
2. Help all students use new tech
3. Prepare students for the jobs of the future
4. Learn to make sense of complex information
5. Universities to lead the tech change

5 Ways Teachers Can Use NotebookLM Today — from classtechtips.com by Dr. Monica Burns

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“AI in 2024: Insights From our 5 Million Readers” [Generative AI] + some other items re: AI in general

On 12/29/2024, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, communities of practice, digital audio, digital video, emerging technologies, ethics, future, game-changing environment, Google, human-computer interaction (HCI), innovation, intelligent systems, intelligent tutoring, IT in HE, Microsoft, morals/values, Natural Language Processing (NLP), Open AI, platforms, productivity / tips and tricks, tools, United States, vendors, voice recognition / voice enabled interfaces, by Daniel Christian

AI in 2024: Insights From our 5 Million Readers — from linkedin.com by Generative AI

Checking the Pulse: The Impact of AI on Everyday Lives
So, what exactly did our users have to say about how AI transformed their lives this year?
.

Top 2024 Developments in AI

  1. Video Generation…
  2. AI Employees…
  3. Open Source Advancements…

Getting ready for 2025: your AI team members (Gift lesson 3/3) — from flexos.com by Daan van Rossum

And that’s why today, I’ll tell you exactly which AI tools I’ve recommended for the top 5 use cases to almost 200 business leaders who took the Lead with AI course.

1. Email Management: Simplifying Communication with AI

  • Microsoft Copilot for Outlook. …
  • Gemini AI for Gmail. …
  • Grammarly. …

2. Meeting Management: Maximize Your Time

  • Otter.ai. …
  • Copilot for Microsoft Teams. …
  • Other AI Meeting Assistants. Zoom AI Companion, Granola, and Fathom

3. Research: Streamlining Information Gathering

  • ChatGPT. …
  • Perplexity. …
  • Consensus. …

…plus several more items and tools that were mentioned by Daan.

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“An AI tutor for every student” + numerous other items re: AI in our learning ecosystems

On 12/21/2024, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, corporate / business world, corporate universities / corporate training, education, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, generational differences, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, leadership, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, lifelong learning, Open AI, personalized/customized learning, strategy, student-related, teachers, teaching & learning, teaching online, tools, training / L&D, United States, vendors, virtual tutoring, youth, by Daniel Christian

60 Minutes Overtime
Sal Khan wants an AI tutor for every student: here’s how it’s working at an Indiana high school — from cbsnews.com by Anderson Cooper, Aliza Chasan, Denise Schrier Cetta, and Katie Brennan

“I mean, that’s what I’ll always want for my own children and, frankly, for anyone’s children,” Khan said. “And the hope here is that we can use artificial intelligence and other technologies to amplify what a teacher can do so they can spend more time standing next to a student, figuring them out, having a person-to-person connection.”
…
“After a week you start to realize, like, how you can use it,” Brockman said. “That’s been one of the really important things about working with Sal and his team, to really figure out what’s the right way to sort of bring this to parents and to teachers and to classrooms and to do that in a way…so that the students really learn and aren’t just, you know, asking for the answers and that the parents can have oversight and the teachers can be involved in that process.”

Nectir lets teachers tailor AI chatbots to provide their students with 24/7 educational support — from techcrunch.com by Lauren Forristal

More than 100 colleges and high schools are turning to a new AI tool called Nectir, allowing teachers to create a personalized learning partner that’s trained on their syllabi, textbooks, and assignments to help students with anything from questions related to their coursework to essay writing assistance and even future career guidance.
…
With Nectir, teachers can create an AI assistant tailored to their specific needs, whether for a single class, a department, or the entire campus. There are various personalization options available, enabling teachers to establish clear boundaries for the AI’s interactions, such as programming the assistant to assist only with certain subjects or responding in a way that aligns with their teaching style.

“It’ll really be that customized learning partner. Every single conversation that a student has with any of their assistants will then be fed into that student profile for them to be able to see based on what the AI thinks, what should I be doing next, not only in my educational journey, but in my career journey,” Ghai said. 

How Will AI Influence Higher Ed in 2025? — from insidehighered.com by Kathryn Palmer
No one knows for sure, but Inside Higher Ed asked seven experts for their predictions.

As the technology continues to evolve at a rapid pace, no one knows for sure how AI will influence higher education in 2025. But several experts offered Inside Higher Ed their predictions—and some guidance—for how colleges and universities will have to navigate AI’s potential in the new year.

How A.I. Can Revive a Love of Learning — from nytimes.com by Anant Agarwal
Modern technology offers new possibilities for transforming teaching.

In the short term, A.I. will help teachers create lesson plans, find illustrative examples and generate quizzes tailored to each student. Customized problem sets will serve as tools to combat cheating while A.I. provides instant feedback.
…
In the longer term, it’s possible to imagine a world where A.I. can ingest rich learner data and create personalized learning paths for students, all within a curriculum established by the teacher. Teachers can continue to be deeply involved in fostering student discussions, guiding group projects and engaging their students, while A.I. handles grading and uses the Socratic method to help students discover answers on their own. Teachers provide encouragement and one-on-one support when needed, using their newfound availability to give students some extra care.

Let’s be clear: A.I. will never replace the human touch that is so vital to education. No algorithm can replicate the empathy, creativity and passion a teacher brings to the classroom. But A.I. can certainly amplify those qualities. It can be our co-pilot, our chief of staff helping us extend our reach and improve our effectiveness.

Dancing with the Devil We Know: OpenAI and the Future of Education — from nickpotkalitsky.substack.com by Nick Potkalitsky
Analyzing OpenAI’s Student Writing Guide and Latest AI Tools

Today, I want to reflect on two recent OpenAI developments that highlight this evolution: their belated publication of advice for students on integrating AI into writing workflows, and last week’s launch of the full GPTo1 Pro version. When OpenAI released their student writing guide, there were plenty of snarky comments about how this guidance arrives almost a year after they thoroughly disrupted the educational landscape. Fair enough – I took my own side swipes initially. But let’s look at what they’re actually advising, because the details matter more than the timing.

Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise — from studentsupportaccelerator.org by Rose E.Wang, Ana T. Ribeiro, Carly D. Robinson, Susanna Loeb, and Dora Demszky

Pandemic, Politics, Pre-K & More: 12 Charts That Defined Education in 2024 — from the74million.org
From the spread of AI to the limits of federal COVID aid, these research findings captured the world of education this year.

Tutoring programs exploded in the last five years as states and school districts searched for ways to counter plummeting achievement during COVID. But the cost of providing supplemental instruction to tens of millions of students can be eye-watering, even as the results seem to taper off as programs serve more students.

That’s where artificial intelligence could prove a decisive advantage. A report circulated in October by the National Student Support Accelerator found that an AI-powered tutoring assistant significantly improved the performance of hundreds of tutors by prompting them with new ways to explain concepts to students. With the help of the tool, dubbed Tutor CoPilot, students assigned to the weakest tutors began posting academic results nearly equal to those assigned to the strongest. And the cost to run the program was just $20 per pupil.

On Capacity, Sustainability, And Attention — from marcwatkins.substack.com by Marc Watkins

Faculty must have the time and support necessary to come to terms with this new technology and that requires us to change how we view professional development in higher education and K-12. We cannot treat generative AI as a one-off problem that can be solved by a workshop, an invited talk, or a course policy discussion. Generative AI in education has to be viewed as a continuum. Faculty need a myriad of support options each semester:

  • Course buyouts
  • Fellowships
  • Learning communities
  • Reading groups
  • AI Institutes and workshops
  • Funding to explore the scholarship of teaching and learning around generative AI

New in 2025 and What Edleaders Should Do About It — from gettingsmart.com by Tom Vander Ark and Mason Pashia

Key Points

  • Education leaders should focus on integrating AI literacy, civic education, and work-based learning to equip students for future challenges and opportunities.
  • Building social capital and personalized learning environments will be crucial for student success in a world increasingly influenced by AI and decentralized power structures.
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Three recent items re: AI in our learning ecosystems

On 12/12/2024, in Artificial Intelligence/Agents/LLMs/and Related, change, corporate / business world, corporate universities / corporate training, digital learning, education, education technology, emerging technologies, Emotion, ethics, experimentation, faculty/staff, future, game-changing environment, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, K-12 related, learning, learning ecosystem, Learning Experience Design, morals/values, pedagogy, productivity / tips and tricks, student-related, teachers, teaching & learning, tools, training / L&D, United States, universities, vendors, vision/possibilities, writing, by Daniel Christian

Episode 302: A Practical Roadmap for AI in K-12 Education with Mike Kentz & Nick Potkalitsky, PhD

In this episode of My EdTech Life, I had the pleasure of interviewing Mike Kentz and Nick Potkalitsky, PhD, to discuss their new book, AI in Education: The K-12 Roadmap to Teacher-Led Transformation. We dive into the transformative power of AI in education, exploring its potential for personalization, its impact on traditional teaching practices, and the critical need for teacher-driven experimentation.

Striking a Balance: Navigating the Ethical Dilemmas of AI in Higher Education — from er.educause.edu by Katalin Wargo and Brier Anderson
Navigating the complexities of artificial intelligence (AI) while upholding ethical standards requires a balanced approach that considers the benefits and risks of AI adoption.

As artificial intelligence (AI) continues to transform the world—including higher education—the need for responsible use has never been more critical. While AI holds immense potential to enhance teaching and learning, ethical considerations around social inequity, environmental concerns, and dehumanization continue to emerge. College and university centers for teaching and learning (CTLs), tasked with supporting faculty in best instructional practices, face growing pressure to take a balanced approach to adopting new technologies. This challenge is compounded by an unpredictable and rapidly evolving landscape. New AI tools surface almost daily. With each new tool, the educational possibilities and challenges increase exponentially. Keeping up is virtually impossible for CTLs, which historically have been institutional hubs for innovation. In fact, as of this writing, the There’s an AI for That website indicates that there are 23,208 AIs for 15,636 tasks for 4,875 jobs—with all three numbers increasing daily.

To support college and university faculty and, by extension, learners in navigating the complexities of AI integration while upholding ethical standards, CTLs must prioritize a balanced approach that considers the benefits and risks of AI adoption. Teaching and learning professionals need to expand their resources and support pathways beyond those solely targeting how to leverage AI or mitigate academic integrity violations. They need to make a concerted effort to promote critical AI literacy, grapple with issues of social inequity, examine the environmental impact of AI technologies, and promote human-centered design principles.1

5 Free AI Tools For Learning & Exploration — from whytryai.com by Daniel Nest
Have fun exploring new topics with these interactive sites.

We’re truly spoiled for choice when it comes to AI learning tools.

In principle, any free LLM can become an endlessly patient tutor or an interactive course-maker.

If that’s not enough, tools like NotebookLM’s “Audio Overviews” and ElevenLabs’ GenFM can turn practically any material into a breezy podcast.

But what if you’re looking to explore new topics in a way that’s more interactive than vanilla chatbots and more open-ended than source-grounded NotebookLM?

Well, then you might want to give one of these free-to-try learning tools a go.

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“What Is Agentic AI?” [Nvidia’s Pounds] + other items re: AI in general

On 12/09/2024, in 21st century, 24x7x365 access, A/V -- audio/visual, Adobe, analytics, art, Artificial Intelligence/Agents/LLMs/and Related, bots, business, cloud-based computing / apps / other cloud-related, communications, communities of practice, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, creativity, data related items, design, digital audio, digital learning, digital photography, digital storytelling, digital video, education technology, emerging technologies, engagement / engaging students, experimentation, Google, graphics, human-computer interaction (HCI), innovation, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning ecosystem, legislatures / government / legal, marketing/social marketing, media/film, Microsoft, multimedia, music, Natural Language Processing (NLP), new media literacies, NVIDIA, online media, Open AI, platforms, podcasting, presentations, productivity / tips and tricks, professional development, programming, skills, social media, strategy, student-related, technologies for your home, technology (general), tools, United States, vendors, videoconferencing, workplace, by Daniel Christian

Where to start with AI agents: An introduction for COOs — from fortune.com by Ganesh Ayyar

Picture your enterprise as a living ecosystem, where surging market demand instantly informs staffing decisions, where a new vendor’s onboarding optimizes your emissions metrics, where rising customer engagement reveals product opportunities. Now imagine if your systems could see these connections too! This is the promise of AI agents — an intelligent network that thinks, learns, and works across your entire enterprise.

Today, organizations operate in artificial silos. Tomorrow, they could be fluid and responsive. The transformation has already begun. The question is: will your company lead it?

The journey to agent-enabled operations starts with clarity on business objectives. Leaders should begin by mapping their business’s critical processes. The most pressing opportunities often lie where cross-functional handoffs create friction or where high-value activities are slowed by system fragmentation. These pain points become the natural starting points for your agent deployment strategy.

Create podcasts in minutes — from elevenlabs.io by Eleven Labs
Now anyone can be a podcast producer

Top AI tools for business — from theneuron.ai

This week in AI: 3D from images, video tools, and more — from heatherbcooper.substack.com by Heather Cooper
From 3D worlds to consistent characters, explore this week’s AI trends

Another busy AI news week, so I organized it into categories:

  • Image to 3D
  • AI Video
  • AI Image Models & Tools
  • AI Assistants / LLMs
  • AI Creative Workflow: Luma AI Boards

Want to speak Italian? Microsoft AI can make it sound like you do. — this is a gifted article from The Washington Post;
A new AI-powered interpreter is expected to simulate speakers’ voices in different languages during Microsoft Teams meetings.

Artificial intelligence has already proved that it can sound like a human, impersonate individuals and even produce recordings of someone speaking different languages. Now, a new feature from Microsoft will allow video meeting attendees to hear speakers “talk” in a different language with help from AI.

What Is Agentic AI?  — from blogs.nvidia.com by Erik Pounds
Agentic AI uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems.

The next frontier of artificial intelligence is agentic AI, which uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems. And it’s set to enhance productivity and operations across industries.

Agentic AI systems ingest vast amounts of data from multiple sources to independently analyze challenges, develop strategies and execute tasks like supply chain optimization, cybersecurity vulnerability analysis and helping doctors with time-consuming tasks.

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“OpenAI wants to pair online courses with chatbots” [Wiggers] + other items re: AI in our learning ecosytems

On 12/07/2024, in adjunct faculty, Artificial Intelligence/Agents/LLMs/and Related, Australia, business, career development, change, changing business models, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, education, education technology, emerging technologies, experimentation, faculty/staff, future, future of higher education, game-changing environment, Google, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, new business models, online learning, Open AI, platforms, productivity / tips and tricks, professional development, research, skills, society, sociology, student-related, teachers, teaching & learning, the downsides of how people use tech, tools, training / L&D, trends, United States, universities, vendors, workplace, writing, youth, by Daniel Christian

What Students Are Saying About Teachers Using A.I. to Grade — from nytimes.com by The Learning Network; via Claire Zau
Teenagers and educators weigh in on a recent question from The Ethicist.

Is it unethical for teachers to use artificial intelligence to grade papers if they have forbidden their students from using it for their assignments?

That was the question a teacher asked Kwame Anthony Appiah in a recent edition of The Ethicist. We posed it to students to get their take on the debate, and asked them their thoughts on teachers using A.I. in general.

While our Student Opinion questions are usually reserved for teenagers, we also heard from a few educators about how they are — or aren’t — using A.I. in the classroom. We’ve included some of their answers, as well.

OpenAI wants to pair online courses with chatbots — from techcrunch.com by Kyle Wiggers; via James DeVaney on LinkedIn

If OpenAI has its way, the next online course you take might have a chatbot component.

Speaking at a fireside on Monday hosted by Coeus Collective, Siya Raj Purohit, a member of OpenAI’s go-to-market team for education, said that OpenAI might explore ways to let e-learning instructors create custom “GPTs” that tie into online curriculums.

“What I’m hoping is going to happen is that professors are going to create custom GPTs for the public and let people engage with content in a lifelong manner,” Purohit said. “It’s not part of the current work that we’re doing, but it’s definitely on the roadmap.”

15 Times to use AI, and 5 Not to — from oneusefulthing.org by Ethan Mollick
Notes on the Practical Wisdom of AI Use

There are several types of work where AI can be particularly useful, given the current capabilities and limitations of LLMs. Though this list is based in science, it draws even more from experience. Like any form of wisdom, using AI well requires holding opposing ideas in mind: it can be transformative yet must be approached with skepticism, powerful yet prone to subtle failures, essential for some tasks yet actively harmful for others. I also want to caveat that you shouldn’t take this list too seriously except as inspiration – you know your own situation best, and local knowledge matters more than any general principles. With all that out of the way, below are several types of tasks where AI can be especially useful, given current capabilities—and some scenarios where you should remain wary.

Learning About Google Learn About: What Educators Need To Know — from techlearning.com by Ray Bendici
Google’s experimental Learn About platform is designed to create an AI-guided learning experience

Google Learn About is a new experimental AI-driven platform available that provides digestible and in-depth knowledge about various topics, but showcases it all in an educational context. Described by Google as a “conversational learning companion,” it is essentially a Wikipedia-style chatbot/search engine, and then some.

In addition to having a variety of already-created topics and leading questions (in areas such as history, arts, culture, biology, and physics) the tool allows you to enter prompts using either text or an image. It then provides a general overview/answer, and then suggests additional questions, topics, and more to explore in regard to the initial subject.

The idea is for student use is that the AI can help guide a deeper learning process rather than just provide static answers.

What OpenAI’s PD for Teachers Does—and Doesn’t—Do — from edweek.org by Olina Banerji
What’s the first thing that teachers dipping their toes into generative artificial intelligence should do?

They should start with the basics, according to OpenAI, the creator of ChatGPT and one of the world’s most prominent artificial intelligence research companies. Last month, the company launched an hour-long, self-paced online course for K-12 teachers about the definition, use, and harms of generative AI in the classroom. It was launched in collaboration with Common Sense Media, a national nonprofit that rates and reviews a wide range of digital content for its age appropriateness.

…the above article links to:

ChatGPT Foundations for K–12 Educators — from commonsense.org

This course introduces you to the basics of artificial intelligence, generative AI, ChatGPT, and how to use ChatGPT safely and effectively. From decoding the jargon to responsible use, this course will help you level up your understanding of AI and ChatGPT so that you can use tools like this safely and with a clear purpose.

Learning outcomes:

  • Understand what ChatGPT is and how it works.
  • Demonstrate ways to use ChatGPT to support your teaching practices.
  • Implement best practices for applying responsible AI principles in a school setting.

Takeaways From Google’s Learning in the AI Era Event — from edtechinsiders.substack.com by Sarah Morin, Alex Sarlin, and Ben Kornell
Highlights from Our Day at Google + Behind-the-Scenes Interviews Coming Soon!

  1. NotebookLM: The Start of an AI Operating System
  2. Google is Serious About AI and Learning
  3. Google’s LearnLM Now Available in AI Studio
  4. Collaboration is King
  5. If You Give a Teacher a Ferrari

Rapid Responses to AI — from the-job.beehiiv.com by Paul Fain
Top experts call for better data and more short-term training as tech transforms jobs.

AI could displace middle-skill workers and widen the wealth gap, says landmark study, which calls for better data and more investment in continuing education to help workers make career pivots.
…
Ensuring That AI Helps Workers
Artificial intelligence has emerged as a general purpose technology with sweeping implications for the workforce and education. While it’s impossible to precisely predict the scope and timing of looming changes to the labor market, the U.S. should build its capacity to rapidly detect and respond to AI developments.
That’s the big-ticket framing of a broad new report from the National Academies of Sciences, Engineering, and Medicine. Congress requested the study, tapping an all-star committee of experts to assess the current and future impact of AI on the workforce.

“In contemplating what the future holds, one must approach predictions with humility,” the study says…

“AI could accelerate occupational polarization,” the committee said, “by automating more nonroutine tasks and increasing the demand for elite expertise while displacing middle-skill workers.”
…
The Kicker: “The education and workforce ecosystem has a responsibility to be intentional with how we value humans in an AI-powered world and design jobs and systems around that,” says Hsieh.

AI Predators: What Schools Should Know and Do — from techlearning.com by Erik Ofgang
AI is increasingly be used by predators to connect with underage students online. Yasmin London, global online safety expert at Qoria and a former member of the New South Wales Police Force in Australia, shares steps educators can take to protect students.

The threat from AI for students goes well beyond cheating, says Yasmin London, global online safety expert at Qoria and a former member of the New South Wales Police Force in Australia.

Increasingly at U.S. schools and beyond, AI is being used by predators to manipulate children. Students are also using AI generate inappropriate images of other classmates or staff members. For a recent report, Qoria, a company that specializes in child digital safety and wellbeing products, surveyed 600 schools across North America, UK, Australia, and New Zealand.

Why We Undervalue Ideas and Overvalue Writing — from aiczar.blogspot.com by Alexander “Sasha” Sidorkin

A student submits a paper that fails to impress stylistically yet approaches a worn topic from an angle no one has tried before. The grade lands at B minus, and the student learns to be less original next time. This pattern reveals a deep bias in higher education: ideas lose to writing every time.

This bias carries serious equity implications. Students from disadvantaged backgrounds, including first-generation college students, English language learners, and those from under-resourced schools, often arrive with rich intellectual perspectives but struggle with academic writing conventions. Their ideas – shaped by unique life experiences and cultural viewpoints – get buried under red ink marking grammatical errors and awkward transitions. We systematically undervalue their intellectual contributions simply because they do not arrive in standard academic packaging.

Google Scholar’s New AI Outline Tool Explained By Its Founder — from techlearning.com by Erik Ofgang
Google Scholar PDF reader uses Gemini AI to read research papers. The AI model creates direct links to the paper’s citations and a digital outline that summarizes the different sections of the paper.

Google Scholar has entered the AI revolution. Google Scholar PDF reader now utilizes generative AI powered by Google’s Gemini AI tool to create interactive outlines of research papers and provide direct links to sources within the paper. This is designed to make reading the relevant parts of the research paper more efficient, says Anurag Acharya, who co-founded Google Scholar on November 18, 2004, twenty years ago last month.

The Four Most Powerful AI Use Cases in Instructional Design Right Now — from drphilippahardman.substack.com by Dr. Philippa Hardman
Insights from ~300 instructional designers who have taken my AI & Learning Design bootcamp this year

  1. AI-Powered Analysis: Creating Detailed Learner Personas…
  2. AI-Powered Design: Optimising Instructional Strategies…
  3. AI-Powered Development & Implementation: Quality Assurance…
  4. AI-Powered Evaluation: Predictive Impact Assessment…

How Are New AI Tools Changing ‘Learning Analytics’? — from edsurge.com by Jeffrey R. Young
For a field that has been working to learn from the data trails students leave in online systems, generative AI brings new promises — and new challenges.

In other words, with just a few simple instructions to ChatGPT, the chatbot can classify vast amounts of student work and turn it into numbers that educators can quickly analyze.

Findings from learning analytics research is also being used to help train new generative AI-powered tutoring systems.
…
Another big application is in assessment, says Pardos, the Berkeley professor. Specifically, new AI tools can be used to improve how educators measure and grade a student’s progress through course materials. The hope is that new AI tools will allow for replacing many multiple-choice exercises in online textbooks with fill-in-the-blank or essay questions.

Increasing AI Fluency Among Enterprise Employees, Senior Management & Executives — from learningguild.com by Bill Brandon

This article attempts, in these early days, to provide some specific guidelines for AI curriculum planning in enterprise organizations.

The two reports identified in the first paragraph help to answer an important question. What can enterprise L&D teams do to improve AI fluency in their organizations?

You could be surprised how many software products have added AI features. Examples (to name a few) are productivity software (Microsoft 365 and Google Workspace); customer relationship management (Salesforce and Hubspot); human resources (Workday and Talentsoft); marketing and advertising (Adobe Marketing Cloud and Hootsuite); and communication and collaboration (Slack and Zoom). Look for more under those categories in software review sites.

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DC: This is a great posting! “AI Tutors: Hype or Hope for Education?” [Bailey & Warner]

On 12/04/2024, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, content development, aggregation, repositories, education, education reform, education technology, emerging technologies, engagement / engaging students, experimentation, future, game-changing environment, Google, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, mathematics, multimedia, new media literacies, Open AI, personalized/customized learning, relationships, science, skills, student-related, teachers, the downsides of how people use tech, United States, vendors, vision/possibilities, writing, by Daniel Christian

AI Tutors: Hype or Hope for Education? — from educationnext.org by John Bailey and John Warner
In a new book, Sal Khan touts the potential of artificial intelligence to address lagging student achievement. Our authors weigh in.

In Salman Khan’s new book, Brave New Words: How AI Will Revolutionize Education (and Why That’s a Good Thing) (Viking, 2024), the Khan Academy founder predicts that AI will transform education by providing every student with a virtual personalized tutor at an affordable cost. Is Khan right? Is radically improved achievement for all students within reach at last? If so, what sorts of changes should we expect to see, and when? If not, what will hold back the AI revolution that Khan foresees? John Bailey, a visiting fellow at the American Enterprise Institute, endorses Khan’s vision and explains the profound impact that AI technology is already making in education. John Warner, a columnist for the Chicago Tribune and former editor for McSweeney’s Internet Tendency, makes the case that all the hype about AI tutoring is, as Macbeth quips, full of sound and fury, signifying nothing.

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Two items re: AI in our learning ecosystems

On 11/27/2024, in Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, future, future of higher education, game-changing environment, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, platforms, productivity / tips and tricks, research, skills, student-related, teaching & learning, tools, training / L&D, United States, universities, vendors, by Daniel Christian

From DSC:
Notebook LM continues to make waves…

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“2024: The State of Generative AI in the Enterprise” [Menlo Ventures] + other items re: AI in general

On 11/27/2024, in Amazon, Artificial Intelligence/Agents/LLMs/and Related, business, computer science, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, data related items, emerging technologies, experimentation, future, Google, graphics, human-computer interaction (HCI), innovation, intelligent systems, languages and translation, Open AI, productivity / tips and tricks, programming, United States, vendors, videoconferencing, workplace, by Daniel Christian

2024: The State of Generative AI in the Enterprise — from menlovc.com (Menlo Ventures)
The enterprise AI landscape is being rewritten in real time. As pilots give way to production, we surveyed 600 U.S. enterprise IT decision-makers to reveal the emerging winners and losers.

This spike in spending reflects a wave of organizational optimism; 72% of decision-makers anticipate broader adoption of generative AI tools in the near future. This confidence isn’t just speculative—generative AI tools are already deeply embedded in the daily work of professionals, from programmers to healthcare providers.

Despite this positive outlook and increasing investment, many decision-makers are still figuring out what will and won’t work for their businesses. More than a third of our survey respondents do not have a clear vision for how generative AI will be implemented across their organizations. This doesn’t mean they’re investing without direction; it simply underscores that we’re still in the early stages of a large-scale transformation. Enterprise leaders are just beginning to grasp the profound impact generative AI will have on their organizations.

Business spending on AI surged 500% this year to $13.8 billion, says Menlo Ventures — from cnbc.com by Hayden Field

Key Points

  • Business spending on generative AI surged 500% this year, hitting $13.8 billion — up from just $2.3 billion in 2023, according to data from Menlo Ventures released Wednesday.
  • OpenAI ceded market share in enterprise AI, declining from 50% to 34%, per the report.
  • Amazon-backed Anthropic doubled its market share from 12% to 24%.

Microsoft quietly assembles the largest AI agent ecosystem—and no one else is close — from venturebeat.com by Matt Marshall

Microsoft has quietly built the largest enterprise AI agent ecosystem, with over 100,000 organizations creating or editing AI agents through its Copilot Studio since launch – a milestone that positions the company ahead in one of enterprise tech’s most closely watched and exciting  segments.
…
The rapid adoption comes as Microsoft significantly expands its agent capabilities. At its Ignite conference [that started on 11/19/24], the company announced it will allow enterprises to use any of the 1,800 large language models (LLMs) in the Azure catalog within these agents – a significant move beyond its exclusive reliance on OpenAI’s models. The company also unveiled autonomous agents that can work independently, detecting events and orchestrating complex workflows with minimal human oversight.

Now Hear This: World’s Most Flexible Sound Machine Debuts — from
Using text and audio as inputs, a new generative AI model from NVIDIA can create any combination of music, voices and sounds.

Along these lines, also see:

AI Agents Versus Human Agency: 4 Ways To Navigate Our AI-Driven World — from forbes.com by Cornelia C. Walther

To understand the implications of AI agents, it’s useful to clarify the distinctions between AI, generative AI, and AI agents and explore the opportunities and risks they present to our autonomy, relationships, and decision-making.
…
AI Agents: These are specialized applications of AI designed to perform tasks or simulate interactions. AI agents can be categorized into:

    • Tool Agents…
    • Simulation Agents..

While generative AI creates outputs from prompts, AI agents use AI to act with intention, whether to assist (tool agents) or emulate (simulation agents). The latter’s ability to mirror human thought and action offers fascinating possibilities — and raises significant risks.

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“Skill-Based Training: Embrace the Benefits; Stay Wary of the Hype” + “5 Key EdTech Innovations to Watch” [Yousey]

On 11/25/2024, in adult learning, content development, aggregation, repositories, corporate / business world, corporate universities / corporate training, curriculum, data related items, education technology, emerging technologies, ethics, ideas, immersion, innovation, instructional design, intelligent systems, leadership, learning ecosystem, Learning Experience Design, productivity / tips and tricks, skills, strategy, training / L&D, trends, United States, vendors, workplace, by Daniel Christian

Skill-Based Training: Embrace the Benefits; Stay Wary of the Hype — from learningguild.com by Paige Yousey

1. Direct job relevance
One of the biggest draws of skill-based training is its direct relevance to employees’ daily roles. By focusing on teaching job-specific skills, this approach helps workers feel immediately empowered to apply what they learn, leading to a quick payoff for both the individual and the organization. Yet, while this tight focus is a major benefit, it’s important to consider some potential drawbacks that could arise from an overly narrow approach.

Be wary of:

  • Overly Narrow Focus: Highly specialized training might leave employees with little room to apply their skills to broader challenges, limiting versatility and growth potential.
  • Risk of Obsolescence: Skills can quickly become outdated, especially in fast-evolving industries. L&D leaders should aim for regular updates to maintain relevance.
  • Neglect of Soft Skills: While technical skills are crucial, ignoring soft skills like communication and problem-solving may lead to a lack of balanced competency.

2. Enhanced job performance…
3. Addresses skill gaps…
…and several more areas to consider

Another item from Paige Yousey

5 Key EdTech Innovations to Watch — from learningguild.com by Paige Yousey

AI-driven course design
…
Strengths

  • Content creation and updates: AI streamlines the creation of training materials by identifying resource gaps and generating tailored content, while also refreshing existing materials based on industry trends and employee feedback to maintain relevance.
  • Data-driven insights: Use AI tools to provide valuable analytics to inform course development and instructional strategies, helping learner designers identify effective practices and improve overall learning outcomes.
  • Efficiency: Automating repetitive tasks, such as learner assessments and administrative duties, enables L&D professionals to concentrate on developing impactful training programs and fostering learner engagement.

Concerns

  • Limited understanding of context: AI may struggle to understand the specific educational context or the unique needs of diverse learner populations, potentially hindering effectiveness.
  • Oversimplification of learning: AI may reduce complex educational concepts to simple metrics or algorithms, oversimplifying the learning process and neglecting deeper cognitive development.
  • Resistance to change: Learning leaders may face resistance from staff who are skeptical about integrating AI into their training practices.

Also from the Learning Guild, see:

Use Twine to Easily Create Engaging, Immersive Scenario-Based Learning — from learningguild.com by Bill Brandon

Scenario-based learning immerses learners in realistic scenarios that mimic real-world challenges they might face in their roles. These learning experiences are highly relevant and relatable. SBL is active learning. Instead of passively consuming information, learners actively engage with the content by making decisions and solving problems within the scenario. This approach enhances critical thinking and decision-making skills.

SBL can be more effective when storytelling techniques create a narrative that guides learners through the scenario to maintain engagement and make the learning memorable. Learners receive immediate feedback on their decisions and learn from their mistakes. Reflection can deepen their understanding. Branching scenarios add simulated complex decision-making processes and show the outcome of various actions through interactive scenarios where learner choices lead to different outcomes.

Embrace the Future: Why L&D Leaders Should Prioritize AI Digital Literacy — from learningguild.com by Dr. Erica McCaig

The role of L&D leaders in AI digital literacy
For L&D leaders, developing AI digital literacy within an organization requires a well-structured curriculum and development plan that equips employees with the knowledge, skills, and ethical grounding needed to thrive in an AI-augmented workplace. This curriculum should encompass a range of competencies that enhance technical understanding and foster a mindset ready for innovation and responsible use of AI. Key areas to focus on include:

  • Understanding AI Fundamentals: …
  • Proficiency with AI Tools: …
  • Ethical Considerations: …
  • Cultivating Critical Thinking: …
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