Miscommunication Leads AI-Based Hiring Tools Astray — from adigaskell.org

Nearly every Fortune 500 company now uses artificial intelligence (AI) to screen resumes and assess test scores to find the best talent. However, new research from the University of Florida suggests these AI tools might not be delivering the results hiring managers expect.

The problem stems from a simple miscommunication between humans and machines: AI thinks it’s picking someone to hire, but hiring managers only want a list of candidates to interview.

Without knowing about this next step, the AI might choose safe candidates. But if it knows there will be another round of screening, it might suggest different and potentially stronger candidates.


AI agents explained: Why OpenAI, Google and Microsoft are building smarter AI agents — from digit.in by Jayesh Shinde

In the last two years, the world has seen a lot of breakneck advancement in the Generative AI space, right from text-to-text, text-to-image and text-to-video based Generative AI capabilities. And all of that’s been nothing short of stepping stones for the next big AI breakthrough – AI agents. According to Bloomberg, OpenAI is preparing to launch its first autonomous AI agent, which is codenamed ‘Operator,’ as soon as in January 2025.

Apparently, this OpenAI agent – or Operator, as it’s codenamed – is designed to perform complex tasks independently. By understanding user commands through voice or text, this AI agent will seemingly do tasks related to controlling different applications in the computer, send an email, book flights, and no doubt other cool things. Stuff that ChatGPT, Copilot, Google Gemini or any other LLM-based chatbot just can’t do on its own.


2025: The year ‘invisible’ AI agents will integrate into enterprise hierarchies  — from venturebeat.com by Taryn Plumb

In the enterprise of the future, human workers are expected to work closely alongside sophisticated teams of AI agents.

According to McKinsey, generative AI and other technologies have the potential to automate 60 to 70% of employees’ work. And, already, an estimated one-third of American workers are using AI in the workplace — oftentimes unbeknownst to their employers.

However, experts predict that 2025 will be the year that these so-called “invisible” AI agents begin to come out of the shadows and take more of an active role in enterprise operations.

“Agents will likely fit into enterprise workflows much like specialized members of any given team,” said Naveen Rao, VP of AI at Databricks and founder and former CEO of MosaicAI.


State of AI Report 2024 Summary — from ai-supremacy.com by Michael Spencer
Part I, Consolidation, emergence and adoption. 


Which AI Image Model Is the Best Speller? Let’s Find Out! — from whytryai.com by Daniel Nest
I test 7 image models to find those that can actually write.

The contestants
I picked 7 participants for today’s challenge:

  1. DALL-E 3 by OpenAI (via Microsoft Designer)
  2. FLUX1.1 [pro] by Black Forest Labs (via Glif)
  3. Ideogram 2.0 by Ideogram (via Ideogram)
  4. Imagen 3 by Google (via Image FX)
  5. Midjourney 6.1 by Midjourney (via Midjourney)
  6. Recraft V3 by Recraft (via Recraft)
  7. Stable Diffusion 3.5 Large by Stability AI (via Hugging Face)

How to get started with AI agents (and do it right) — from venturebeat.com by Taryn Plumb

So how can enterprises choose when to adopt third-party models, open source tools or build custom, in-house fine-tuned models? Experts weigh in.


OpenAI, Google and Anthropic Are Struggling to Build More Advanced AI — from bloomberg.com (behind firewall)
Three of the leading artificial intelligence companies are seeing diminishing returns from their costly efforts to develop newer models.


OpenAI and others seek new path to smarter AI as current methods hit limitations — from reuters.com by Krystal Hu and Anna Tong

Summary

  • AI companies face delays and challenges with training new large language models
  • Some researchers are focusing on more time for inference in new models
  • Shift could impact AI arms race for resources like chips and energy

NVIDIA Advances Robot Learning and Humanoid Development With New AI and Simulation Tools — from blogs.nvidia.com by Spencer Huang
New Project GR00T workflows and AI world model development technologies to accelerate robot dexterity, control, manipulation and mobility.


How Generative AI is Revolutionizing Product Development — from intelligenthq.com

A recent report from McKinsey predicts that generative AI could unlock up to $2.6 to $4.4 annually trillion in value within product development and innovation across various industries. This staggering figure highlights just how significantly generative AI is set to transform the landscape of product development. Generative AI app development is driving innovation by using the power of advanced algorithms to generate new ideas, optimize designs, and personalize products at scale. It is also becoming a cornerstone of competitive advantage in today’s fast-paced market. As businesses look to stay ahead, understanding and integrating technologies like generative AI app development into product development processes is becoming more crucial than ever.


What are AI Agents: How To Create a Based AI Agent — from ccn.com by Lorena Nessi

Key Takeaways

  • AI agents handle complex, autonomous tasks beyond simple commands, showcasing advanced decision-making and adaptability.
  • The Based AI Agent template by Coinbase and Replit provides an easy starting point for developers to build blockchain-enabled AI agents.
  • AI based agents specifically integrate with blockchain, supporting crypto wallets and transactions.
  • Securing API keys in development is crucial to protect the agent from unauthorized access.

What are AI Agents and How Are They Used in Different Industries? — from rtinsights.com by Salvatore Salamone
AI agents enable companies to make smarter, faster, and more informed decisions. From predictive maintenance to real-time process optimization, these agents are delivering tangible benefits across industries.

 

Three items re: accessibility from boia.org


How Important Are Fonts for Digital Accessibility?

With that said, simple sans-serif fonts are generally easier to read and understand. That includes popular fonts like:

    • Times New Roman
    • Arial
    • Tahoma
    • Helvetica
    • Calibri
    • Verdana

If you decide to use serif fonts, use them sparingly. For most body text, you should use a sans serif font with appropriate spacing and weight.

Follow these tips:


Why Web Accessibility Frustrates Developers (And How to Fix It) 

When developers view accessibility as an integral part of their work, the process of building inclusive websites becomes less of a chore and more of a rewarding challenge. By embracing tools like semantic HTML and incorporating user feedback from people with disabilities, developers can create solutions that enhance real user experiences while conforming with WCAG.

Starting with accessibility in mind from day one streamlines workflows, reduces the need for extensive remediation later on, and ultimately leads to more robust and inclusive digital products. To learn more, download our free eBook: Developing the Accessibility Mindset.


How to Respond to an ADA Web Accessibility Demand Letter

An excerpt from the “Learn the basics of digital accessibility” section:

We realize that we just threw a bunch of information at you — but we promise, the principles of WCAG aren’t too complicated. Here are some resources to help you learn the basics:

As you learn about digital accessibility, you’ll feel more comfortable reviewing your own content for potential barriers. The W3C’s Understanding WCAG 2.2 documents are an extremely useful resource for learning about specific barriers (and techniques for fixing them).

 

10 Graphic Design Trends to Pay Attention to in 2025 — from graphicmama.com by Al Boicheva

We’ll go on a hunt for bold, abstract, and naturalist designs, cutting-edge AI tools, and so much more, all pushing boundaries and rethinking what we already know about design. In 2025, we will see new ways to animate ideas, revisit retro styles with a modern twist, and embrace clean, but sophisticated aesthetics. For designers and design enthusiasts alike, these trends are set to bring a new level of excitement to the world of design.

Here are the Top 10 Graphic Design Trends in 2025:

 

Opening Keynote – GS1

Bringing generative AI to video with Adobe Firefly Video Model

Adobe Launches Firefly Video Model and Enhances Image, Vector and Design Models

  • 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

Photoshop delivers powerful innovation for image editing, ideation, 3D design, and more

Even more speed, precision, and power: Get started with the latest Illustrator and InDesign features for creative professionals

Adobe Introduces New Global Initiative Aimed at Helping 30 Million Next-Generation Learners Develop AI Literacy, Content Creation and Digital Marketing Skills by 2030

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.

 

AI’s Trillion-Dollar Opportunity — from bain.com by David Crawford, Jue Wang, and Roy Singh
The market for AI products and services could reach between $780 billion and $990 billion by 2027.

At a Glance

  • The big cloud providers are the largest concentration of R&D, talent, and innovation today, pushing the boundaries of large models and advanced infrastructure.
  • Innovation with smaller models (open-source and proprietary), edge infrastructure, and commercial software is reaching enterprises, sovereigns, and research institutions.
  • Commercial software vendors are rapidly expanding their feature sets to provide the best use cases and leverage their data assets.

Accelerated market growth. Nvidia’s CEO, Jensen Huang, summed up the potential in the company’s Q3 2024 earnings call: “Generative AI is the largest TAM [total addressable market] expansion of software and hardware that we’ve seen in several decades.”


And on a somewhat related note (i.e., emerging technologies), also see the following two postings:

Surgical Robots: Current Uses and Future Expectations — from medicalfuturist.com by Pranavsingh Dhunnoo
As the term implies, a surgical robot is an assistive tool for performing surgical procedures. Such manoeuvres, also called robotic surgeries or robot-assisted surgery, usually involve a human surgeon controlling mechanical arms from a control centre.

Key Takeaways

  • Robots’ potentials have been a fascination for humans and have even led to a booming field of robot-assisted surgery.
  • Surgical robots assist surgeons in performing accurate, minimally invasive procedures that are beneficial for patients’ recovery.
  • The assistance of robots extend beyond incisions and includes laparoscopies, radiosurgeries and, in the future, a combination of artificial intelligence technologies to assist surgeons in their craft.

Proto hologram tech allows cancer patients to receive specialist care without traveling large distances — from inavateonthenet.net

“Working with the team from Proto to bring to life, what several years ago would have seemed impossible, is now going to allow West Cancer Center & Research Institute to pioneer options for patients to get highly specialized care without having to travel to large metro areas,” said West Cancer’s CEO, Mitch Graves.




Clone your voice in minutes: The AI trick 95% don’t know about — from aidisruptor.ai by Alex McFarland
Warning: May cause unexpected bouts of talking to yourself

Now that you’ve got your voice clone, what can you do with it?

  1. Content Creation:
    • Podcast Production: Record episodes in half the time. Your listeners won’t know the difference, but your schedule will thank you.
    • Audiobook Narration: Always wanted to narrate your own book? Now you can, without spending weeks in a recording studio.
    • YouTube Videos: Create voiceovers for your videos in multiple languages. World domination, here you come!
  2. Business Brilliance:
    • Customer Service: Personalized automated responses that actually sound personal.
    • Training Materials: Create engaging e-learning content in your own voice, minus the hours of recording.
    • Presentations: Never worry about losing your voice before a big presentation again. Your clone’s got your back.

185 real-world gen AI use cases from the world’s leading organizations — from blog.google by Brian Hall; via Daniel Nest’s Why Try AI

In a matter of months, organizations have gone from AI helping answer questions, to AI making predictions, to generative AI agents. What makes AI agents unique is that they can take actions to achieve specific goals, whether that’s guiding a shopper to the perfect pair of shoes, helping an employee looking for the right health benefits, or supporting nursing staff with smoother patient hand-offs during shifts changes.

In our work with customers, we keep hearing that their teams are increasingly focused on improving productivity, automating processes, and modernizing the customer experience. These aims are now being achieved through the AI agents they’re developing in six key areas: customer service; employee empowerment; code creation; data analysis; cybersecurity; and creative ideation and production.

Here’s a snapshot of how 185 of these industry leaders are putting AI to use today, creating real-world use cases that will transform tomorrow.


AI Data Drop: 3 Key Insights from Real-World Research on AI Usage — from microsoft.com; via Daniel Nest’s Why Try AI
One of the largest studies of Copilot usage—at nearly 60 companies—reveals how AI is changing the way we work.

  1. AI is starting to liberate people from email
  2. Meetings are becoming more about value creation
  3. People are co-creating more with AI—and with one another


*** Dharmesh has been working on creating agent.ai — a professional network for AI agents.***


Speaking of agents, also see:

Onboarding the AI workforce: How digital agents will redefine work itself — from venturebeat.com by Gary Grossman

AI in 2030: A transformative force

  1. AI agents are integral team members
  2. The emergence of digital humans
  3. AI-driven speech and conversational interfaces
  4. AI-enhanced decision-making and leadership
  5. Innovation and research powered by AI
  6. The changing nature of job roles and skills

AI Video Tools You Can Use Today — from heatherbcooper.substack.com by Heather Cooper
The latest AI video models that deliver results

AI video models are improving so quickly, I can barely keep up! I wrote about unreleased Adobe Firefly Video in the last issue, and we are no closer to public access to Sora.

No worries – we do have plenty of generative AI video tools we can use right now.

  • Kling AI launched its updated v1.5 and the quality of image or text to video is impressive.
  • Hailuo MiniMax text to video remains free to use for now, and it produces natural and photorealistic results (with watermarks).
  • Runway added the option to upload portrait aspect ratio images to generate vertical videos in Gen-3 Alpha & Turbo modes.
  • …plus several more

 

Helping Neurodiverse Students Learn Through New Classroom Design — from insidehighered.com by Michael Tyre
Michael Tyre offers some insights into how architects and administrators can work together to create better learning environments for everyone.

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.


On a somewhat related note, also see:

Unpacking Fingerprint Culture — from marymyatt.substack.com by Mary Myatt

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.

 

Some very creative artwork!

 

When A.I.’s Output Is a Threat to A.I. Itself — from nytimes.com by Aatish Bhatia
As A.I.-generated data becomes harder to detect, it’s increasingly likely to be ingested by future A.I., leading to worse results.

All this A.I.-generated information can make it harder for us to know what’s real. And it also poses a problem for A.I. companies. As they trawl the web for new data to train their next models on — an increasingly challenging task — they’re likely to ingest some of their own A.I.-generated content, creating an unintentional feedback loop in which what was once the output from one A.I. becomes the input for another.

In the long run, this cycle may pose a threat to A.I. itself. Research has shown that when generative A.I. is trained on a lot of its own output, it can get a lot worse.


Per The Rundown AI:

The Rundown: Elon Musk’s xAI just launched “Colossus“, the world’s most powerful AI cluster powered by a whopping 100,000 Nvidia H100 GPUs, which was built in just 122 days and is planned to double in size soon.

Why it matters: xAI’s Grok 2 recently caught up to OpenAI’s GPT-4 in record time, and was trained on only around 15,000 GPUs. With now more than six times that amount in production, the xAI team and future versions of Grok are going to put a significant amount of pressure on OpenAI, Google, and others to deliver.


Google Meet’s automatic AI note-taking is here — from theverge.com by Joanna Nelius
Starting [on 8/28/24], some Google Workspace customers can have Google Meet be their personal note-taker.

Google Meet’s newest AI-powered feature, “take notes for me,” has started rolling out today to Google Workspace customers with the Gemini Enterprise, Gemini Education Premium, or AI Meetings & Messaging add-ons. It’s similar to Meet’s transcription tool, only instead of automatically transcribing what everyone says, it summarizes what everyone talked about. Google first announced this feature at its 2023 Cloud Next conference.


The World’s Call Center Capital Is Gripped by AI Fever — and Fear — from bloomberg.com by Saritha Rai [behind a paywall]
The experiences of staff in the Philippines’ outsourcing industry are a preview of the challenges and choices coming soon to white-collar workers around the globe.


[Claude] Artifacts are now generally available — from anthropic.com

[On 8/27/24], we’re making Artifacts available for all Claude.ai users across our Free, Pro, and Team plans. And now, you can create and view Artifacts on our iOS and Android apps.

Artifacts turn conversations with Claude into a more creative and collaborative experience. With Artifacts, you have a dedicated window to instantly see, iterate, and build on the work you create with Claude. Since launching as a feature preview in June, users have created tens of millions of Artifacts.


MIT's AI Risk Repository -- a comprehensive database of risks from AI systems

What are the risks from Artificial Intelligence?
A comprehensive living database of over 700 AI risks categorized by their cause and risk domain.

What is the AI Risk Repository?
The AI Risk Repository has three parts:

  • The AI Risk Database captures 700+ risks extracted from 43 existing frameworks, with quotes and page numbers.
  • The Causal Taxonomy of AI Risks classifies how, when, and why these risks occur.
  • The Domain Taxonomy of AI Risks classifies these risks into seven domains (e.g., “Misinformation”) and 23 subdomains (e.g., “False or misleading information”).

California lawmakers approve legislation to ban deepfakes, protect workers and regulate AI — from newsday.com by The Associated Press

SACRAMENTO, Calif. — California lawmakers approved a host of proposals this week aiming to regulate the artificial intelligence industry, combat deepfakes and protect workers from exploitation by the rapidly evolving technology.

Per Oncely:

The Details:

  • Combatting Deepfakes: New laws to restrict election-related deepfakes and deepfake pornography, especially of minors, requiring social media to remove such content promptly.
  • Setting Safety Guardrails: California is poised to set comprehensive safety standards for AI, including transparency in AI model training and pre-emptive safety protocols.
  • Protecting Workers: Legislation to prevent the replacement of workers, like voice actors and call center employees, with AI technologies.

New in Gemini: Custom Gems and improved image generation with Imagen 3 — from blog.google
The ability to create custom Gems is coming to Gemini Advanced subscribers, and updated image generation capabilities with our latest Imagen 3 model are coming to everyone.

We have new features rolling out, [that started on 8/28/24], that we previewed at Google I/O. Gems, a new feature that lets you customize Gemini to create your own personal AI experts on any topic you want, are now available for Gemini Advanced, Business and Enterprise users. And our new image generation model, Imagen 3, will be rolling out across Gemini, Gemini Advanced, Business and Enterprise in the coming days.


Cut the Chatter, Here Comes Agentic AI — from trendmicro.com

Major AI players caught heat in August over big bills and weak returns on AI investments, but it would be premature to think AI has failed to deliver. The real question is what’s next, and if industry buzz and pop-sci pontification hold any clues, the answer isn’t “more chatbots”, it’s agentic AI.

Agentic AI transforms the user experience from application-oriented information synthesis to goal-oriented problem solving. It’s what people have always thought AI would do—and while it’s not here yet, its horizon is getting closer every day.

In this issue of AI Pulse, we take a deep dive into agentic AI, what’s required to make it a reality, and how to prevent ‘self-thinking’ AI agents from potentially going rogue.

Citing AWS guidance, ZDNET counts six different potential types of AI agents:

    • Simple reflex agents for tasks like resetting passwords
    • Model-based reflex agents for pro vs. con decision making
    • Goal-/rule-based agents that compare options and select the most efficient pathways
    • Utility-based agents that compare for value
    • Learning agents
    • Hierarchical agents that manage and assign subtasks to other agents

Ask Claude: Amazon turns to Anthropic’s AI for Alexa revamp — from reuters.com by Greg Bensinger

Summary:

  • Amazon developing new version of Alexa with generative AI
  • Retailer hopes to generate revenue by charging for its use
  • Concerns about in-house AI prompt Amazon to turn to Anthropic’s Claude, sources say
  • Amazon says it uses many different technologies to power Alexa

Alibaba releases new AI model Qwen2-VL that can analyze videos more than 20 minutes long — from venturebeat.com by Carl Franzen


Hobbyists discover how to insert custom fonts into AI-generated images — from arstechnica.com by Benj Edwards
Like adding custom art styles or characters, in-world typefaces come to Flux.


200 million people use ChatGPT every week – up from 100 million last fall, says OpenAI — from zdnet.com by Sabrina Ortiz
Nearly two years after launching, ChatGPT continues to draw new users. Here’s why.

 
 

Augmented Course Design: Using AI to Boost Efficiency and Expand Capacity — from er.educause.edu by Berlin Fang and Kim Broussard
The emerging class of generative AI tools has the potential to significantly alter the landscape of course development.

Using generative artificial intelligence (GenAI) tools such as ChatGPT, Gemini, or CoPilot as intelligent assistants in instructional design can significantly enhance the scalability of course development. GenAI can significantly improve the efficiency with which institutions develop content that is closely aligned with the curriculum and course objectives. As a result, institutions can more effectively meet the rising demand for flexible and high-quality education, preparing a new generation of future professionals equipped with the knowledge and skills to excel in their chosen fields.1 In this article, we illustrate the uses of AI in instructional design in terms of content creation, media development, and faculty support. We also provide some suggestions on the effective and ethical uses of AI in course design and development. Our perspectives are rooted in medical education, but the principles can be applied to any learning context.

Table 1 summarizes a few low-hanging fruits in AI usage in course development.
.

Table 1. Types of Use of GenAI in Course Development
Practical Use of AI Use Scenarios and Examples
Inspiration
  • Exploring ideas for instructional strategies
  • Exploring ideas for assessment
  • Course mapping
  • Lesson or unit content planning
Supplementation
  • Text to audio
  • Transcription for audio
  • Alt text auto-generation
  • Design optimization (e.g., using Microsoft PPT Design)
Improvement
  • Improving learning objectives
  • Improving instructional materials
  • Improving course content writing (grammar, spelling, etc.)
Generation
  • Creating a PowerPoint draft using learning objectives
  • Creating peripheral content materials (introductions, conclusions)
  • Creating decorative images for content
Expansion
  • Creating a scenario based on learning objectives
  • Creating a draft of a case study
  • Creating a draft of a rubric

.


Also see:

10 Ways Artificial Intelligence Is Transforming Instructional Design — from er.educause.edu by Rob Gibson
Artificial intelligence (AI) is providing instructors and course designers with an incredible array of new tools and techniques to improve the course design and development process. However, the intersection of AI and content creation is not new.

I have been telling my graduate instructional design students that AI technology is not likely to replace them any time soon because learning and instruction are still highly personalized and humanistic experiences. However, as these students embark on their careers, they will need to understand how to appropriately identify, select, and utilize AI when developing course content. Examples abound of how instructional designers are experimenting with AI to generate and align student learning outcomes with highly individualized course activities and assessments. Instructional designers are also using AI technology to create and continuously adapt the custom code and power scripts embedded into the learning management system to execute specific learning activities.Footnote1 Other useful examples include scripting and editing videos and podcasts.

Here are a few interesting examples of how AI is shaping and influencing instructional design. Some of the tools and resources can be used to satisfy a variety of course design activities, while others are very specific.


Taking the Lead: Why Instructional Designers Should Be at the Forefront of Learning in the Age of AI — from medium.com by Rob Gibson
Education is at a critical juncture and needs to draw leaders from a broader pool, including instructional designers

The world of a medieval stone cutter and a modern instructional designer (ID) may seem separated by a great distance, but I wager any ID who upon hearing the story I just shared would experience an uneasy sense of déjà vu. Take away the outward details, and the ID would recognize many elements of the situation: the days spent in projects that fail to realize the full potential of their craft, the painful awareness that greater things can be built, but are unlikely to occur due to a poverty of imagination and lack of vision among those empowered to make decisions.

Finally, there is the issue of resources. No stone cutter could ever hope to undertake a large-scale enterprise without a multitude of skilled collaborators and abundant materials. Similarly, instructional designers are often departments of one, working in scarcity environments, with limited ability to acquire resources for ambitious projects and — just as importantly — lacking the authority or political capital needed to launch significant initiatives. For these reasons, instructional design has long been a profession caught in an uncomfortable stasis, unable to grow, evolve and achieve its full potential.

That is until generative AI appeared on the scene. While the discourse around AI in education has been almost entirely about its impact on teaching and assessment, there has been a dearth of critical analysis regarding AI’s potential for impacting instructional design.

We are at a critical juncture for AI-augmented learning. We can either stagnate, missing opportunities to support learners while educators continue to debate whether the use of generative AI tools is a good thing, or we can move forward, building a transformative model for learning akin to the industrial revolution’s impact.

Too many professional educators remain bound by traditional methods. The past two years suggest that leaders of this new learning paradigm will not emerge from conventional educational circles. This vacuum of leadership can be filled, in part, by instructional designers, who are prepared by training and experience to begin building in this new learning space.

 

Very creative architecture!


From DSC:
I thought this was very creative! Nice work.


A Curtain-Like Facade Wraps a Seoul Textile Maker in Billowing Brick — from thisiscolossal.com by Kate Mothes and German architecture firm behet bondzio lin architekten

A South Korea fashion brand and textile manufacturer’s headquarters in Seoul gets a stunning new look thanks to German architecture firm behet bondzio lin architekten. Located in Seongsu-dong, a neighborhood historically known for its red brick factory buildings, the new multistory structure defies the material’s traditionally angular application by incorporating an undulating, drapery-like facade.

The architects conceived of a design inspired both by the flow and flexibility of textiles and the consistent rhythm of ocean waves.
.

 

In ‘Old Growth,’ Mitch Epstein Travels the U.S. to Capture Monumental Ancient Relics — from thisiscolossal.com by Kate Mothes and Mitch Epstein

 

Designing your classroom — from edutopia.org

Resources for designing your classroom/learning space

As back-to-school season approaches, we know you’re gearing up to design your next classroom. It can be daunting to craft a space that does it all: boosts academic achievement, fosters collaboration, *and* makes students feel welcome and included.

That’s why we’ve curated a brand-new collection of 25 articles and videos—packed with research-backed insights and actionable strategies—to help find a layout that works best for you and your students. Topics range from optimizing your classroom walls to creating an environment that supports a wide range of executive functioning skills. Whether you’re a teacher or an administrator, these essential resources are designed to guide you through every stage of classroom setup.

Also from edutopia.org, see:

A Starter Pack of Resources for New Teachers — from edutopia.org
We’ve pulled together articles and videos in which educators—both veteran and new—share what they wish they knew on day one about classroom design, assessment, working with parents, and more.

A Starter Pack of Resources for New Teachers


Also re: the K-12 learning ecosystem, see:

 

Free Sites for Back to School — from techlearning.com by Diana Restifo
Top free and freemium sites for learning

An internet search for free learning resources will likely return a long list that includes some useful sites amid a sea of not-really-free and not-very-useful sites.

To help teachers more easily find the best free and freemium sites they can use in their classrooms and curricula, I’ve curated a list that describes the top free/freemium sites for learning.

In some cases, Tech & Learning has reviewed the site in detail, and those links are included so readers can find out more about how to make the best use of the online materials. In all cases, the websites below provide valuable educational tools, lessons, and ideas, and are worth exploring further.


Two bonus postings here! 🙂 

 

Daniel Christian: My slides for the Educational Technology Organization of Michigan’s Spring 2024 Retreat

From DSC:
Last Thursday, I presented at the Educational Technology Organization of Michigan’s Spring 2024 Retreat. I wanted to pass along my slides to you all, in case they are helpful to you.

Topics/agenda:

  • Topics & resources re: Artificial Intelligence (AI)
    • Top multimodal players
    • Resources for learning about AI
    • Applications of AI
    • My predictions re: AI
  • The powerful impact of pursuing a vision
  • A potential, future next-gen learning platform
  • Share some lessons from my past with pertinent questions for you all now
  • The significant impact of an organization’s culture
  • Bonus material: Some people to follow re: learning science and edtech

 

Education Technology Organization of Michigan -- ETOM -- Spring 2024 Retreat on June 6-7

PowerPoint slides of Daniel Christian's presentation at ETOM

Slides of the presentation (.PPTX)
Slides of the presentation (.PDF)

 


Plus several more slides re: this vision.

 
© 2024 | Daniel Christian