The TLDR here is that, as useful as popular AI tools are for learners, as things stand they only enable us to take the very first steps on what is a long and complex journey of learning.
AI tools like ChatGPT 4o, Claude 3.5 & NotebookLM can help to give us access to information but (for now at least) the real work of learning remains in our – the humans’ – hands.
To which Anna Mills had a solid comment:
It might make a lot of sense to regulate generated audio to require some kind of watermark and/or metadata. Instructors who teach online and assign voice recordings, we need to recognize that these are now very easy and free to auto-generate. In some cases we are assigning this to discourage students from using AI to just autogenerate text responses, but audio is not immune.
The Adobe Firefly Video Model (beta) expands Adobe’s family of creative generative AI models and is the first publicly available video model designed to be safe for commercial use
Enhancements to Firefly models include 4x faster image generation and new capabilities integrated into Photoshop, Illustrator, Adobe Express and now Premiere Pro
Firefly has been used to generate 13 billion images since March 2023 and is seeing rapid adoption by leading brands and enterprises
Add sound to your video via text — Project Super Sonic:
New Dream Weaver — from aisecret.us Explore Adobe’s New Firefly Video Generative Model
Cybercriminals exploit voice cloning to impersonate individuals, including celebrities and authority figures, to commit fraud. They create urgency and trust to solicit money through deceptive means, often utilizing social media platforms for audio samples.
Norway law decrees: Let childhood be childhood — from hechingerreport.org by Jackie Mader In the Scandinavian country, early childhood education is a national priority, enshrined in law
Ullmann’s conclusion embodies one of Norway’s goals for its citizens: to build a nation of thriving adults by providing childhoods that are joyful, secure and inclusive. Perhaps nowhere is this belief manifested more clearly than in the nation’s approach to early child care. (In Norway, all education for children 5 and under is referred to as “barnehagen,” the local translation of “kindergarten.”) To an American, the Norwegian philosophy, both in policy and in practice, could feel alien. The government’s view isn’t that child care is a place to put children so parents can work, or even to prepare children for the rigors of elementary school. It’s about protecting childhood.
“A really important pillar of Norway’s early ed philosophy is the value of childhood in itself,” said Henrik D. Zachrisson, a professor at the Centre for Research on Equality in Education at the University of Oslo. “Early ed is supposed to be a place where children can be children and have the best childhood possible.”
1. Using AI to Scale Exceptional Instructional Design Practice
Imagine a bonification system that doesn’t just automate tasks, but scales best practices in instructional design:
2. Surfacing AI’s Instructional Design Thinking
Instead of hiding AI’s decision-making process, what if we built an AI system which invites instructional designers to probe, question, and learn from an expert trained AI?
Explain This Design…
Show Me Alternatives…
Challenge My Assumptions…
Learning Science Insights…
By reimagining the role of AI in this way, we would…
OpenAI’s Education Forum was eye-opening for a number of reasons, but the one that stood out the most was Leah Belsky acknowledging what many of us in education had known for nearly two years—the majority of the active weekly users of ChatGPT are students. OpenAI has internal analytics that track upticks in usage during the fall and then drops off in the spring. Later that evening, OpenAI’s new CFO, Sarah Friar, further drove the point home with an anecdote about usage in the Philippines jumping nearly 90% at the start of the school year.
I had hoped to gain greater insight into OpenAI’s business model and how it related to education, but the Forum left me with more questions than answers. What app has the majority of users active 8 to 9 months out of the year and dormant for the holidays and summer breaks? What business model gives away free access and only converts 1 out of every 20-25 users to paid users? These were the initial thoughts that I hoped the Forum would address. But those questions, along with some deeper and arguably more critical ones, were skimmed over to drive home the main message of the Forum—Universities have to rapidly adopt AI and become AI-enabled institutions.
As we embrace these technologies, we must also consider the experiences we need to discover and maintain our connections—and our humanity. In a world increasingly shaped by AI, I find myself asking: What are the experiences that define us, and how do they influence the relationships we build, both professionally and personally?
This concept of “off-loading” has become central to my thinking. In simple terms, off-loading is the act of delegating tasks to AI that we would otherwise do ourselves. As AI systems advance, we’re increasingly confronted with a question: Which tasks should we off-load to AI?
Students need clarity on their postsecondary pathways— from eschoolnews.com by Laura Ascione When it comes to planning for life after high school, a lack of career exposure is hindering many students’ abilities to envision a future
Key points:
Students require guidance and career exposure to plan for the future
Much emphasis is placed on college and career readiness, but too often, K-12 students aren’t exposed to career possibilities or career resources to form an idea of what their future may look like.
1. Record audio from class on your phone
2. Keep laptop closed. Just jot down short phrases to describe most important points
3. Upload audio and PDF scan of notes to NotebookLM
4. Ask Notebook to expand your notes with details from recording… pic.twitter.com/wfmCTJfRba
Unlock deeper insights with NotebookLM: Now analyze YouTube videos & audio files alongside your docs. Plus, easily share your Audio Overview with a new sharing option!
I. Introduction (0:00 – 6:16): …
II. Historical Contextualization (6:16 – 11:30): …
III. The Role of Product Fit in AI’s Impact (11:30 – 17:10): …
IV. AI and the Future of Knowledge Work (17:10 – 24:03): …
V. Teaching About AI in Higher Ed: A Measured Approach (24:03 – 34:20): …
VI. AI & the Evolving Skills Landscape (34:20 – 44:35): …
VII. Ethical & Pedagogical Considerations in an AI-Driven World (44:35 – 54:03):…
VIII. AI Beyond the Classroom: Administrative Applications & the Need for Intuition (54:03 – 1:04:30): …
IX. Reflections & Future Directions (1:04:30 – 1:11:15): ….
Part 2: Administrative Impacts & Looking Ahead
X. Bridging the Conversation: From Classroom to Administration (1:11:15 – 1:16:45): …
XI. The Administrative Potential of AI: A Looming Transformation (1:16:45 – 1:24:42): …
XII. The Need for Intuitiveness & the Importance of Real-World Applications (1:24:42 – 1:29:45): …
XIII. Looking Ahead: From Hype to Impactful Integration (1:29:45 – 1:34:25): …
XIV. Conclusion and Call to Action (1:34:25 – 1:36:03): …
Most language learners do not have access to affordable 1:1 tutoring, which is also proven to be the most effective way to learn (short of moving to a specific country for complete immersion). Meanwhile, language learning is a huge market, and with an estimated 60% of this still dominated by “offline” solutions, meaning it is prime for disruption and never more so than with the opportunities unlocked through AI powered language learning. Therefore — we believe this presents huge opportunities for new startups creating AI native products to create the next language learning unicorns.
I never imagined I’d learn so much without paying for a course.
It’s not that AI is inherently biased, but in its current state, it favors those who can afford it. The wealthy districts continue to pull ahead, leaving schools without resources further behind. Students in these underserved areas aren’t just being deprived of technology—they’re being deprived of the future.
But imagine a different world—one where AI doesn’t deepen the divide, but helps to bridge it. Technology doesn’t have to be the luxury of the wealthy. It can be a tool for every student, designed to meet them where they are. Adaptive AI systems, integrated into schools regardless of their budget, can provide personalized learning experiences that help students catch up and push forward, all while respecting the limits of their current infrastructure. This is where AI’s true potential lies—not in widening the gap, but in leveling the field.
But imagine if, instead of replacing teachers, AI helped to support them. Picture a world where teachers are freed from the administrative burdens that weigh them down. Where AI systems handle the logistics, so teachers can focus on what they do best—teaching, mentoring, and inspiring the next generation. Professional development could be personalized, helping teachers integrate AI into their classrooms in ways that enhance their teaching, without adding to their workload. This is the future we should be striving toward—one where technology serves to lift up educators, not push them out.
Duolingo’s new Video Call feature represents a leap forward in language practice for learners. This AI-powered tool allows Duolingo Max subscribers to engage in spontaneous, realistic conversations with Lily, one of Duolingo’s most popular characters. The technology behind Video Call is designed to simulate natural dialogue and provides a personalized, interactive practice environment. Even beginner learners can converse in a low-pressure environment because Video Call is designed to adapt to their skill level. By offering learners the opportunity to converse in real-time,Video Call builds the confidence needed to communicate effectively in real-world situations. Video Call is available for Duolingo Max subscribers learning English, Spanish, and French.
Ello, the AI reading companion that aims to support kids struggling to read, launched a new product on Monday that allows kids to participate in the story-creation process.
Called “Storytime,” the new AI-powered feature helps kids generate personalized stories by picking from a selection of settings, characters, and plots. For instance, a story about a hamster named Greg who performed in a talent show in outer space.
We emerged with two guiding principles. First, we had learned that certain environments—in particular, those that cause sensory distraction—can more significantly impact neurodivergent users. Therefore, our design should diminish distractions by mitigating, when possible, noise, visual contrast, reflective surfaces and crowds. Second, we understood that we needed a design that gave neurodivergent users the agency of choice.
The importance of those two factors—a dearth of distraction and an abundance of choice—was bolstered in early workshops with the classroom committee and other stakeholders, which occurred at the same time we were conducting our research. Some things didn’t come up in our research but were made quite clear in our conversations with faculty members, students from the neurodivergent community and other stakeholders. That feedback greatly influenced the design of the Young Classroom.
We ended up blending the two concepts. The main academic space utilizes traditional tables and chairs, albeit in a variety of heights and sizes, while the peripheral classroom spaces use an array of less traditional seating and table configurations, similar to the radical approach.
This post summarises a fascinating webinar I had with Rachel Higginson discussing the elements of building belonging in our settings.
We know that belonging is important and one of the ways to make this explicit in our settings is to consider what it takes to cultivate an inclusive environment where each individual feels valued and understood.
Rachel has spent several years working with young people, particularly those on the periphery of education to help them back into mainstream education and participating in class, along with their peers.
Rachel’s work helping young people to integrate back into education resulted in schools requesting support and resources to embed inclusion within their settings. As a result, Finding My Voice has evolved into a broader curriculum development framework.
Giving ELA Lessons a Little Edtech Boost — from edutopia.org by Julia Torres Common activities in English language arts classes such as annotation and note-taking can be improved through technology.
6 ELA Practices That Can Be Enhanced by EdTech
Book clubs.
Collective note-taking.
Comprehension checks.
Video lessons.
..and more
Using Edtech Tools to Differentiate Learning— from edutopia.org by Katie Novak and Mary E. Pettit Teachers can use tech tools to make it easier to give students choice about their learning, increasing engagement.
The core problem, witnesses at the hearing said, is that teacher-preparation programs treat all teachers—and, by extension, students—the same, asking teachers to be “everything to everybody.”
“The current model of teaching where one teacher works individually with a group of learners in a classroom—or a small box inside of a larger box that we call school—promotes unrealistic expectations by assuming individual teachers working in isolation can meet the needs of all students,” said Greg Mendez, the principal of Skyline High School in Mesa, Ariz.
From DSC: I’ve long thought teacher education programs could and should evolve (that’s why I have a “student teacher/teacher education” category on this blog). For example, they should inform their future teachers about the science of learning and how to leverage edtech/emerging technologies into their teaching methods.
But regardless of what happens in our teacher prep programs, the issues about the current PreK-12 learning ecosystem remain — and THOSE things are what we need to address. Or we will continue to see teachers leave the profession.
Are we straight-jacketing our teachers and administrators by having them give so many standardized tests and then having to teach to those tests? (We should require our legislators to teach in a classroom before they can draft any kind of legislation.)
Do teachers have the joy they used to have? The flexibility they used to have? Do students?
Do students have choice and voice?
etc.
Also, I highlighted the above excerpt because we can’t expect a teacher to do it all. They can’t be everything to everybody. It’s a recipe for burnout and depression. There are too many agendas coming at them.
We need to empower our current teachers and listen very carefully to the changes that they recommend. We should also listen very carefully to what our STUDENTS are recommending as well!
The XQ Institute shares this mindset as part of our mission to reimagine the high school learning experience so it’s more relevant and engaging for today’s learners, while better preparing them for the future.We see AI as a tool with transformative potential for educators and makers to leverage — but only if it’s developed and implemented with ethics, transparency and equity at the forefront. That’s why we’re building partnerships between educators and AI developers to ensure that products are shaped by the real needs and challenges of students, teachers and schools. Here’s how we believe all stakeholders can embrace the Department’s recommendations through ongoing collaborations with tech leaders, educators and students alike.
…lead me to the XQ Institute, and I very much like what I’m initially seeing! Here are some excerpts from their website:
Transforming high school isn’t easy, but it is possible. ? Educator @nwallacecxh from XQ’s @CrosstownHigh shares real-world strategies to make learning relevant and meaningful. Ready to see how it’s done? ? https://t.co/xD8hkP33TH
AI researcher Jim Fan has had a charmed career. He was OpenAI’s first intern before he did his PhD at Stanford with “godmother of AI,” Fei-Fei Li. He graduated into a research scientist position at Nvidia and now leads its Embodied AI “GEAR” group. The lab’s current work spans foundation models for humanoid robots to agents for virtual worlds. Jim describes a three-pronged data strategy for robotics, combining internet-scale data, simulation data and real world robot data. He believes that in the next few years it will be possible to create a “foundation agent” that can generalize across skills, embodiments and realities—both physical and virtual. He also supports Jensen Huang’s idea that “Everything that moves will eventually be autonomous.”
Runway Partners with Lionsgate — from runwayml.com via The Rundown AI Runway and Lionsgate are partnering to explore the use of AI in film production.
Lionsgate and Runway have entered into a first-of-its-kind partnership centered around the creation and training of a new AI model, customized on Lionsgate’s proprietary catalog. Fundamentally designed to help Lionsgate Studios, its filmmakers, directors and other creative talent augment their work, the model generates cinematic video that can be further iterated using Runway’s suite of controllable tools.
Per The Rundown:Lionsgate, the film company behind The Hunger Games, John Wick, and Saw, teamed up with AI video generation company Runway to create a custom AI model trained on Lionsgate’s film catalogue.
The details:
The partnership will develop an AI model specifically trained on Lionsgate’s proprietary content library, designed to generate cinematic video that filmmakers can further manipulate using Runway’s tools.
Lionsgate sees AI as a tool to augment and enhance its current operations, streamlining both pre-production and post-production processes.
Runway is considering ways to offer similar custom-trained models as templates for individual creators, expanding access to AI-powered filmmaking tools beyond major studios.
Why it matters: As many writers, actors, and filmmakers strike against ChatGPT, Lionsgate is diving head-first into the world of generative AI through its partnership with Runway. This is one of the first major collabs between an AI startup and a major Hollywood company — and its success or failure could set precedent for years to come.
Each prompt on ChatGPT flows through a server that runs thousands of calculations to determine the best words to use in a response.
In completing those calculations, these servers, typically housed in data centers, generate heat. Often, water systems are used to cool the equipment and keep it functioning. Water transports the heat generated in the data centers into cooling towers to help it escape the building, similar to how the human body uses sweat to keep cool, according to Shaolei Ren, an associate professor at UC Riverside.
Where electricity is cheaper, or water comparatively scarce, electricity is often used to cool these warehouses with large units resembling air-conditioners, he said. That means the amount of water andelectricity an individual query requires can depend on a data center’s location and vary widely.
AI, Humans and Work: 10 Thoughts.— from rishad.substack.com by Rishad Tobaccowala The Future Does Not Fit in the Containers of the Past. Edition 215.
10 thoughts about AI, Humans and Work in 10 minutes:
AI is still Under-hyped.
AI itself will be like electricity and is unlikely to be a differentiator for most firms.
AI is not alive but can be thought of as a new species.
Knowledge will be free and every knowledge workers job will change in 2025.
The key about AI is not to ask what AI will do to us but what AI can do for us.
As we navigate the rapidly evolving landscape of artificial intelligence in education, a troubling trend has emerged. What began as cautious skepticism has calcified into rigid opposition. The discourse surrounding AI in classrooms has shifted from empirical critique to categorical rejection, creating a chasm between the potential of AI and its practical implementation in education.
This hardening of attitudes comes at a significant cost. While educators and policymakers debate, students find themselves caught in the crossfire. They lack safe, guided access to AI tools that are increasingly ubiquitous in the world beyond school walls. In the absence of formal instruction, many are teaching themselves to use these tools, often in less than productive ways. Others live in a state of constant anxiety, fearing accusations of AI reliance in their work. These are just a few symptoms of an overarching educational culture that has become resistant to change, even as the world around it transforms at an unprecedented pace.
Yet, as this calcification sets in, I find myself in a curious position: the more I thoughtfully integrate AI into my teaching practice, the more I witness its potential to enhance and transform education
The urgency to integrate AI competencies into education is about preparing students not just to adapt to inevitable changes but to lead the charge in shaping an AI-augmented world. It’s about equipping them to ask the right questions, innovate responsibly, and navigate the ethical quandaries that come with such power.
AI in education should augment and complement their aptitude and expertise, to personalize and optimize the learning experience, and to support lifelong learning and development. AI in education should be a national priority and a collaborative effort among all stakeholders, to ensure that AI is designed and deployed in an ethical, equitable, and inclusive way that respects the diversity and dignity of all learners and educators and that promotes the common good and social justice. AI in education should be about the production of AI, not just the consumption of AI, meaning that learners and educators should have the opportunity to learn about AI, to participate in its creation and evaluation, and to shape its impact and direction.
Horizon Three Learning — from gettingsmart.com How might we build the nation’s new learning ecosystem together?
America’s education system was a groundbreaking effort to help a growing nation thrive in the 19th century. Now, 200 years later, the world has changed; the horizon looks drastically different. Collectively, we need to redesign our education system to enable all of our children — and, by extension, our nation — to thrive today and tomorrow.
“Horizon Three” or “H3” names the future-ready system we need, one that is grounded in equity serving learners’ individual strengths and needs as well as the common good. This series provides a glimpse of where H3 is already being designed and built. It also includes provocations about how we might fundamentally reimagine learning for the future ahead.
