productivity / tips and tricks

1-800-CHAT-GPT—12 Days of OpenAI: Day 10

Per The Rundown: OpenAI just launched a surprising new way to access ChatGPT — through an old-school 1-800 number & also rolled out a new WhatsApp integration for global users during Day 10 of the company’s livestream event.

How Agentic AI is Revolutionizing Customer Service — from customerthink.com by Devashish Mamgain

Agentic AI represents a significant evolution in artificial intelligence, offering enhanced autonomy and decision-making capabilities beyond traditional AI systems. Unlike conventional AI, which requires human instructions, agentic AI can independently perform complex tasks, adapt to changing environments, and pursue goals with minimal human intervention.

This makes it a powerful tool across various industries, especially in the customer service function. To understand it better, let’s compare AI Agents with non-AI agents.
…
Characteristics of Agentic AI

- Autonomy: Achieves complex objectives without requiring human collaboration.
- Language Comprehension: Understands nuanced human speech and text effectively.
- Rationality: Makes informed, contextual decisions using advanced reasoning engines.
- Adaptation: Adjusts plans and goals in dynamic situations.
- Workflow Optimization: Streamlines and organizes business workflows with minimal oversight.

Clio: A system for privacy-preserving insights into real-world AI use — from anthropic.com

How, then, can we research and observe how our systems are used while rigorously maintaining user privacy?

Claude insights and observations, or “Clio,” is our attempt to answer this question. Clio is an automated analysis tool that enables privacy-preserving analysis of real-world language model use. It gives us insights into the day-to-day uses of claude.ai in a way that’s analogous to tools like Google Trends. It’s also already helping us improve our safety measures. In this post—which accompanies a full research paper—we describe Clio and some of its initial results.

Evolving tools redefine AI video — from heatherbcooper.substack.com by Heather Cooper
Google’s Veo 2, Kling 1.6, Pika 2.0 & more

AI video continues to surpass expectations
The AI video generation space has evolved dramatically in recent weeks, with several major players introducing groundbreaking tools.

Here’s a comprehensive look at the current landscape:

Veo 2…
Pika 2.0…
Runway’s Gen-3…
Luma AI Dream Machine…
Hailuo’s MiniMax…
OpenAI’s Sora…
Hunyuan Video by Tencent…

There are several other video models and platforms, including …

Jeremy Caplan: 12 of my favorite tools this year

On 12/21/2024, in Artificial Intelligence/Agents/LLMs/and Related, creativity, design, digital audio, digital video, experimentation, graphics, productivity / tips and tricks, programming, tools, United States, vendors, videoconferencing, workplace, by Daniel Christian

Best of 2024 — from wondertools.substack.com by Jeremy Caplan
12 of my favorites this year

I tested hundreds of new tools this year. Many were duplicative. A few stuck with me because they’re so useful. The dozen noted below are helping me mine insights from notes, summarize meetings, design visuals— even code a little, without being a developer. You can start using any of these in minutes — no big budget or prompt engineering PhD required.

Incorporating Financial Literacy into Your Classroom Curriculum [edcircuit.com]

On 12/21/2024, in content development, aggregation, repositories, curriculum, education, education technology, productivity / tips and tricks, real-world assignments, student-related, surviving, teachers, youth, by Daniel Christian

Incorporating Financial Literacy into Your Classroom Curriculum — from edcircuit.com by EdCircuit Staff
Teaching Beyond the Textbook

Table of Contents

The Importance of Teaching Financial Literacy
Incorporating Financial Literacy into Your CurriculumUse Real-Life Examples
Integrate it into Other Subjects
Use Technology
Make it Interactive
Start Early
Conclusion

“Your Map To The Future lays out tools and techniques futurists have been using for decades” [Dr. Bertalan Mesko, PhD]

On 12/17/2024, in Daniel S. Christian, future, future of higher education, game-changing environment, health, productivity / tips and tricks, by Daniel Christian

Your Map to the Future: New Book! — from medicalfuturist.com by Dr. Bertalan Mesko, PhD
Your Map To The Future lays out tools and techniques futurists have been using for decades so you can start using them immediately to shape your personal and professional futures.

Futures thinking shouldn’t be reserved for experts. Whether you’re a leader, a professional, or simply someone striving to make sense of a complex world, this book is for you.
…
The futures methods I’ve used as The Medical Futurist for decades in analyzing the future of medicine and healthcare have, for some reason, not become widely accessible.

However, everyone can obtain these methods to approach the future with confidence, clarity, and control.

While the future is believed to be a fixed, singular path, in fact, multiple futures exist, and Your Map To The Future gives you the science-based tools to explore and prepare for them. With fresh perspectives, I illustrate why looking forward is crucial in addressing today’s most pressing issues, from climate change to artificial intelligence.

From DSC:
I haven’t read this book and I hesitate to post this…as it leans heavily into an advertisement for this particular book. But I DO post it because I also believe that future thinking shouldn’t be reserved for experts. In fact, I assert that all K-12 students — and college/vocational students as well — should have some exposure to futures thinking. We need to be looking up and around and pulse-checking the trends. We need to posit future scenarios and our plans to address those potential scenarios.

Also, I have read Dr. Mesko’s postings for years and he’s solid.

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.

Introducing Gemini 2.0: our new AI model for the agentic era — from blog.google by Sundar Pichai, Demis Hassabis, and Koray Kavukcuoglu

Today we’re excited to launch our next era of models built for this new agentic era: introducing Gemini 2.0, our most capable model yet. With new advances in multimodality — like native image and audio output — and native tool use, it will enable us to build new AI agents that bring us closer to our vision of a universal assistant.

We’re getting 2.0 into the hands of developers and trusted testers today. And we’re working quickly to get it into our products, leading with Gemini and Search. Starting today our Gemini 2.0 Flash experimental model will be available to all Gemini users. We’re also launching a new feature called Deep Research, which uses advanced reasoning and long context capabilities to act as a research assistant, exploring complex topics and compiling reports on your behalf. It’s available in Gemini Advanced today.

Over the last year, we have been investing in developing more agentic models, meaning they can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision.

.

Try Deep Research and our new experimental model in Gemini, your AI assistant — from blog.google by Dave Citron
Deep Research rolls out to Gemini Advanced subscribers today, saving you hours of time. Plus, you can now try out a chat optimized version of 2.0 Flash Experimental in Gemini on the web.

Today, we’re sharing the latest updates to Gemini, your AI assistant, including Deep Research — our new agentic feature in Gemini Advanced — and access to try Gemini 2.0 Flash, our latest experimental model.

Deep Research uses AI to explore complex topics on your behalf and provide you with findings in a comprehensive, easy-to-read report, and is a first look at how Gemini is getting even better at tackling complex tasks to save you time.1

Google Unveils A.I. Agent That Can Use Websites on Its Own — from nytimes.com by Cade Metz and Nico Grant (NOTE: This is a GIFTED article for/to you.)
The experimental tool can browse spreadsheets, shopping sites and other services, before taking action on behalf of the computer user.

Google on Wednesday unveiled a prototype of this technology, which artificial intelligence researchers call an A.I. agent.
…
Google’s new prototype, called Mariner, is based on Gemini 2.0, which the company also unveiled on Wednesday. Gemini is the core technology that underpins many of the company’s A.I. products and research experiments. Versions of the system will power the company’s chatbot of the same name and A.I. Overviews, a Google search tool that directly answers user questions.

Gemini 2.0 is the next chapter for Google AI — from axios.com by Ina Fried

Google Gemini 2.0 — a major upgrade to the core workings of Google’s AI that the company launched Wednesday — is designed to help generative AI move from answering users’ questions to taking action on its own…
…
The big picture: Hassabis said building AI systems that can take action on their own has been DeepMind’s focus since its early days teaching computers to play games such as chess and Go.

“We were always working towards agent-based systems,” Hassabis said. “From the beginning, they were able to plan and then carry out actions and achieve objectives.”
Hassabis said AI systems that can act as semi-autonomous agents also represent an important intermediate step on the path toward artificial general intelligence (AGI) — AI that can match or surpass human capabilities.
“If we think about the path to AGI, then obviously you need a system that can reason, break down problems and carry out actions in the world,” he said.

AI Agents vs. AI Assistants: Know the Key Differences — from aithority.com by Rishika Patel

The same paradigm applies to AI systems. AI assistants function as reactive tools, completing tasks like answering queries or managing workflows upon request. Think of chatbots or scheduling tools. AI agents, however, work autonomously to achieve set objectives, making decisions and executing tasks dynamically, adapting as new information becomes available.

Together, AI assistants and agents can enhance productivity and innovation in business environments. While assistants handle routine tasks, agents can drive strategic initiatives and problem-solving. This powerful combination has the potential to elevate organizations, making processes more efficient and professionals more effective.

Discover how to accelerate AI transformation with NVIDIA and Microsoft — from ignite.microsoft.com

Meet NVIDIA – The Engine of AI. From gaming to data science, self-driving cars to climate change, we’re tackling the world’s greatest challenges and transforming everyday life. The Microsoft and NVIDIA partnership enables Startups, ISVs, and Partners global access to the latest NVIDIA GPUs on-demand and comprehensive developer solutions to build, deploy and scale AI-enabled products and services.

Google + Meta + Apple New AI — from theneurondaily.com by Grant Harve

What else Google announced:

Deep Research: New feature that can explore topics and compile reports.
Project Astra: AI agent that can use Google Search, Lens, and Maps, understands multiple languages, and has 10-minute conversation memory.
Project Mariner: A browser control agent that can complete web tasks (83.5% success rate on WebVoyager benchmark). Read more about Mariner here.
Agents to help you play (or test) video games.

AI Agents: Easier To Build, Harder To Get Right — from forbes.com by Andres Zunino

The swift progress of artificial intelligence (AI) has simplified the creation and deployment of AI agents with the help of new tools and platforms. However, deploying these systems beneath the surface comes with hidden challenges, particularly concerning ethics, fairness and the potential for bias.

The history of AI agents highlights the growing need for expertise to fully realize their benefits while effectively minimizing risks.

“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.

“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!

NotebookLM: The Start of an AI Operating System
Google is Serious About AI and Learning
Google’s LearnLM Now Available in AI Studio
Collaboration is King
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

AI-Powered Analysis: Creating Detailed Learner Personas…
AI-Powered Design: Optimising Instructional Strategies…
AI-Powered Development & Implementation: Quality Assurance…
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.

VLOG: Learning in Medical School [The Learning Scientists]

On 12/07/2024, in Emotion, experimentation, faculty/staff, health, higher education, instructional design, learning, learning ecosystem, Learning Experience Design, memory, productivity / tips and tricks, student-related, teaching & learning, United States, universities, vendors, by Daniel Christian

VLOG: Learning in Medical School — from learningscientists.org by The Learning Scientists

NOTE:

This vlog is for anyone in medical school, interested in medical school, or just curious about what learning is like in medical school!

In this vlog Althea and Cindy talk about their work with medical student learners. They discuss common learning challenges in medical school, efficient learning strategies, learning in the context of attentional disorders and anxiety, and what it means to prepare future healers.

What We Talk about When We Talk about Networking — from michelleweise.substack.com by Dr. Michelle Weise, Julia Freeland Fisher, and Nitzan Pelman
Networking, Social Capital & the Goldilocks Ask

I recently had a chance to sit down with Julia Freeland Fisher, Director of Education at the Christensen Institute, and Nitzan Pelman, CEO of Climb Together and founder of Climb Hire, for a live CGN webinar on tapping into our networks (some of you may recall, I wrote about these two phenomenal women in my post, “Who You Know … A Little Bit: The Power of Weak Ties”).

I love getting to learn from their constantly evolving thinking on cultivating and mobilizing social capital. And in this episode, we get super tactical on the how-to’s of networking for young people.

From DSC:
Tell your kids or grandkids to watch this. I didn’t have a CLUE about networking when I graduated from high school — and even from college. It took me years to get an accurate understanding of the place and power of networking. And that it’s not all about looking out for #1 and taking from/manipulating/exploiting others. But it’s about sharing resources, learning and connecting with others, helping others connect with relevant others, and more.

I hope that we can produce more items like this to help the next generation get started and navigate their careers.

How AI is transforming learning for dyslexic students — from eschoolnews.com by Samay Bhojwani, University of Nebraska–Lincoln
As schools continue to adopt AI-driven tools, educators can close the accessibility gap and help dyslexic students thrive

Many traditional methods lack customization and don’t empower students to fully engage with content on their terms. Every dyslexic student experiences challenges differently, so a more personalized approach is essential for fostering comprehension, engagement, and academic growth.
…
Artificial intelligence is increasingly recognized for its potential to transform educational accessibility. By analyzing individual learning patterns, AI-powered tools can tailor content to meet each student’s specific needs. For dyslexic students, this can mean summarizing complex texts, providing auditory support, or even visually structuring information in ways that aid comprehension.

NotebookLM How-to Guide 2024 — from ai-supremacy.com by Michael Spencer and Alex McFarland
With Audio Version | A popular guide reloaded.

In this guide, I’ll show you:

How to use the new advanced audio customization features
Two specific workflows for synthesizing information (research papers and YouTube videos)
Pro tips for maximizing results with any type of content
Common pitfalls to avoid (learned these the hard way)

The State of Instructional Design 2024: A Field on the Brink of Disruption? — from drphilippahardman.substack.com by Dr. Philippa Hardman
My hot takes from a global survey I ran with Synthesia

As I mentioned on LinkedIn, earlier this week Synthesia published the results of a global survey that we ran together the state of instructional design in 2024.

Boundless Socratic Learning: Google DeepMind’s Vision for AI That Learns Without Limits — from by Giorgio Fazio

Google DeepMind researchers have unveiled a groundbreaking framework called Boundless Socratic Learning (BSL), a paradigm shift in artificial intelligence aimed at enabling systems to self-improve through structured language-based interactions. This approach could mark a pivotal step toward the elusive goal of artificial superintelligence (ASI), where AI systems drive their own development with minimal human input.

The promise of Boundless Socratic Learning lies in its ability to catalyze a shift from human-supervised AI to systems that evolve and improve autonomously. While significant challenges remain, the introduction of this framework represents a step toward the long-term goal of open-ended intelligence, where AI is not just a tool but a partner in discovery.

5 courses to take when starting out a career in Agentic AI — from techloy.com by David Adubiina
This will help you join the early train of experts who are using AI agents to solve real world problems.

This surge in demand is creating new opportunities for professionals equipped with the right skills. If you’re considering a career in this innovative field, the following five courses will provide a solid foundation when starting a career in Agentic AI.

A New Era for Law Firm Learning and Development [Kubicki]

On 12/04/2024, in Artificial Intelligence/Agents/LLMs/and Related, career development, human-computer interaction (HCI), ideas, law schools, Legal operations, legislatures / government / legal, productivity / tips and tricks, professional development, skills, by Daniel Christian

(An excerpt from Brainyacts #253 12/3/24)

A New Era for Law Firm Learning and Development — from brainyacts.beehiiv.com by Josh Kubicki

By becoming early adopters, law firms can address two critical challenges in professional development:

1. Empowering Educators and Mentors
Generative AI equips legal educators, practice group leaders, and mentors with tools to amplify their impact. It assists with:

Content generation: …
Research facilitation: …
Skill-building frameworks: …

…
2. Cracking the Personalized Learning Code
Every lawyer’s learning needs are unique. Generative AI delivers hyper-personalized educational experiences that adapt to an individual’s role, practice area, and career stage. This addresses the “Two Sigma Problem” (the dramatic performance gains of one-on-one tutoring) by making tailored learning scalable and actionable. Imagine:

AI-driven tutors: …
Instant feedback loops: …
Adaptive learning models: …

Case Study: Building AI Tutors in Legal Education
…
Moving Beyond CLEs: A New Vision for Professional Development…

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…

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:

Nvidia unveils AI model for music, audio that can modify voices, generate new sounds — from seekingalpha.com

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.

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: …

Learning Ecosystems

“Your Map To The Future lays out tools and techniques futurists have been using for decades” [Dr. Bertalan Mesko, PhD]

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