What An Agent Is
Agents are computer programs that can autonomously perform tasks, make decisions and interact with humans or other computers. There are many different types of agents, and they are designed to achieve specific goals spanning our lives and nearly every industry, making them an integral and unstoppable part of our future.
Learning: AI agents will transform education by providing personalized learning experiences such as one-to-one tutoring. ChatGPT and other large language models (LLMs) are providing access to all digital knowledge now. An “agent” would act as a more personalized version of an LLM.
The hacking and control of an AI agent could lead to disastrous consequences, affecting privacy, security, the economy and societal stability. Proactive and comprehensive security strategies are essential to mitigate these risks in the future.
LearnLM is our new family of models fine-tuned for learning, and grounded in educational research to make teaching and learning experiences more active, personal and engaging.
We often talk about what Generative AI will do for coders, healthcare, science or even finance, but what about the benefits for the next generation? Permit me if you will, here I’m thinking about teachers and students.
It’s no secret that some of the most active users of ChatGPT in its heyday, were students. But how are other major tech firms thinking about this?
I actually think one of the best products with the highest ceiling from Google I/O 2024 is LearnLM. It has to be way more than a chatbot, it has to feel like a multimodal tutor. I can imagine frontier model agents (H) doing this fairly well.
What if everyone, everywhere could have their own personal AI tutor, on any topic?
ChatGPT4o Is the TikTok of AI Models — from nickpotkalitsky.substack.com by Nick Potkalitsky In Search of Better Tools for AI Access in K-12 Classrooms
Nick makes the case that we should pause on the use of OpenAI in the classrooms:
In light of these observations, it’s clear that we must pause and rethink the use of OpenAI products in our classrooms, except for rare cases where accessibility needs demand it. The rapid consumerization of AI, epitomized by GPT4o’s transformation into an AI salesperson, calls for caution.
Hello GPT-4o — from openai.com We’re announcing GPT-4o, our new flagship model that can reason across audio, vision, and text in real time.
GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.
Providing inflection, emotions, and a human-like voice
Understanding what the camera is looking at and integrating it into the AI’s responses
Providing customer service
With GPT-4o, we trained a single new model end-to-end across text, vision, and audio, meaning that all inputs and outputs are processed by the same neural network. Because GPT-4o is our first model combining all of these modalities, we are still just scratching the surface of exploring what the model can do and its limitations.
This demo is insane.
A student shares their iPad screen with the new ChatGPT + GPT-4o, and the AI speaks with them and helps them learn in *realtime*.
Imagine giving this to every student in the world.
Since AI in education has been moving at the speed of light, we built this AI Tools in Education database to keep track of the most recent AI tools in education and the changes that are happening every day. This database is intended to be a community resource for educators, researchers, students, and other edtech specialists looking to stay up to date. This is a living document, so be sure to come back for regular updates.
The day started out with a short talk about AI (slides). Some of it is my usual schtick where I do a bit of Q&A with folks around myths and misunderstandings of generative AI in order to establish some common ground. These are often useful both in setting the tone and giving folks a sense of how I come to explore generative AI: with a mixture of humor, concern, curiosity, and of course, cat pics.
From there, we launched into a series of mini-workshops where folks had time to first play around with some previously created prompts around teaching and learning before moving onto prompts for administrative work. The prompts and other support materials are in this Workshop Resource Document. The goal was to just get them into using one or more AI tools with some useful prompts so they can learn more about its capabilities.
The Edtech Insiders Rundown of ASU+GSV 2024 — from edtechinsiders.substack.com by by Sarah Morin, Alex Sarlin, and Ben Kornell And more on Edtech Insiders+, upcoming events, Gauth, AI Reading Tutors, The Artificial Intelligence Interdisciplinary Institute, and TeachAI Policy Resources
Alex Sarlin
4. Everyone is Edtech Now This year, in addition to investors, entrepreneurs, educators, school leaders, university admins, non-profits, publishers, and operators from countless edtech startups and incumbents, there were some serious big tech companies in attendance like Meta, Google, OpenAI, Microsoft, Amazon, Tiktok, and Canva. Additionally, a horde of management consultancies, workforce organizations, mental health orgs, and filmmakers were in attendance.
Edtech continues to expand as an industry category and everyone is getting involved.
It was such a delight to chat with Ana. She’s brilliant and passionate, a talented educator, and an advocate for better ways of learning for children and adults. We cover ways to transform schools so that students get real-world skills, learn resilience and how to embrace challenges, and are prepared for an unpredictable future. And we go hard on why we must keep learning no matter our age, become generalists, and leverage technology in order to adapt to the fast-changing world.
The Texas Tribune reports an “automated scoring engine” that utilizes natural language processing — the technology that enables chatbots like OpenAI’s ChatGPT to understand and communicate with users — is being rolled out by the Texas Education Agency (TEA) to grade open-ended questions on the State of Texas Assessments of Academic Readiness (STAAR) exams. The agency is expecting the system to save $15–20 million per year by reducing the need for temporary human scorers, with plans to hire under 2,000 graders this year compared to the 6,000 required in 2023.
Debating About AI: An Easy Path to AI Awareness and Basic Literacy — from stefanbauschard.substack.com by Stefan Bauschard If you are an organization committed to AI literacy, consider sponsoring some debate topics and/or debates next year and expose thousands of students to AI literacy.
Resolved: Teachers should integrate generative AI in their teaching and learning.
The topic is simple but raises an issue that students can connect with.
While helping my students prepare and judging debates, I saw students demonstrate an understanding of many key issues and controversies.
These included—
*AI writing assessment/grading
*Bias
*Bullying
*Cognitive load
*Costs of AI systems
*Declining test scores
*Deep fakes
*Differentiation
*Energy consumption
*Hallucinations
*Human-to-human connection
*Inequality and inequity in access
*Neurodiversity
*Personalized learning
*Privacy
*Regulation (lack thereof)
*The future of work and unemployment
*Saving teachers time
*Soft skills
*Standardized testing
*Student engagement
*Teacher awareness and AI training; training resource trade-offs
*Teacher crowd-out
*Transparency and explainability
*Writing detectors (students had an exaggerated sense of the workability of these tools).
What if, for example, the corporate learning system knew who you were and you could simply ask it a question and it would generate an answer, a series of resources, and a dynamic set of learning objects for you to consume? In some cases you’ll take the answer and run. In other cases you’ll pour through the content. And in other cases you’ll browse through the course and take the time to learn what you need.
And suppose all this happened in a totally personalized way. So you didn’t see a “standard course” but a special course based on your level of existing knowledge?
This is what AI is going to bring us. And yes, it’s already happening today.
From DSC: This would be huge for all of our learning ecosystems, as the learning agents could remember where a particular student or employee is at in terms of their learning curve for a particular topic.
Healthcare High Schools — from the-job.beehiiv.com by Paul Fain Bloomberg and hospitals back dual-enrollment path from K-12 to high-demand jobs.
More career exploration in high school is needed to help Americans make better-informed choices about their education and job options, experts agree. And serious, employer-backed efforts to tighten connections between school and work are likely to emerge first in healthcare, given the industry’s severe staffing woes.
A new $250M investment by Bloomberg Philanthropies could be an important step in this direction. The money will seed the creation of healthcare-focused high schools in 10 U.S. locations, with a plan to enroll 6K students who will graduate directly from the early-college high schools into high-demand healthcare jobs that pay family-sustaining wages.
Last year, the landscape of K-12 education transformed as a record-breaking 20 states expanded school choice options. However, that is not the only school choice story to come out of 2023. As the nation steps into 2024, a fresh emphasis on innovation has emerged, along with new options for families. This is particularly true within the realm of microschooling.
Microschooling is an education model that is small by design — typically with 15 or fewer students of varying ages per class. It fosters a personalized and community-centric approach to learning that is especially effective in addressing the unique educational needs of diverse student populations. Programs like Education Savings Accounts are helping to fuel these microschools.
Large classes create more distractions for students who struggle to focus, and they inevitably get less attention and support as there are more students for teachers to work with. High numbers of students make it more difficult to plan for individual needs and force teachers to teach to an imaginary middle. A rigid schedule makes it easy to schedule adults and services, but it is a challenge for kids who need time to get engaged and prefer to keep working at a challenge once they are locked in.
…
Now that I know what can engage and motivate these students, I can imagine creating more opportunities that allow them to harness their talents and grow their skills and knowledge. But we’re already a third of the way through the school year, and my curriculum requires me to teach certain topics for certain lengths of time, which doesn’t leave room for many of the types of experiences these kids need. Soon, June will come and I’ll pass them along to the next teacher, who won’t know what I know and will need another four months to learn it, wasting valuable time in these students’ educations.
From DSC: We need teachers and professors to be able to contribute to learners’ records. Each student can review and decide whether they want to allow access to other teachers– or even to employers. Educators could insert what they’ve found to work with a particular student, what passions/interests that student has, or what to avoid (if possible). For example, has this student undergone some trauma, and therefore trauma-informed teaching should be employed.
IEPs could be a part of learners’ records/profiles. The teams working on implementing these IEP’s could share important, searchable information.
Washington state issued new guidelines for K-12 public schools last week based on the principle of “embracing a human-centered approach to AI,” which also embraces the use of AI in the education process. The state’s Superintendent of Public Instruction, Chris Reykdal, commented in a letter accompanying the new guidelines:
Everyone is empowered to access learning and earning opportunities based on what they know and can do, whether those skills and abilities are obtained through degrees, work experiences, or independent learning.
People can capture and communicate the skills and competencies they’ve acquired across their entire learning journey — from education, experience and service — with more ease, confidence, and clarity than a traditional resume.
Learners and earners control their information and can curate their skills to take advantage of every opportunity they are truly qualified to pursue, opening up pathways that help address systemic inequities.
Employers can tap into a wider talent pool and better match applicants to opportunities with verifiable credentials that represent skills, competencies, and achievements.
This is the world that we believe can be created by Learning and Employment Records (LERs), i.e. digital records of learning and work experiences that are linked to and controlled by learners and earners. An interoperable, well-governed LER ecosystem has the potential to transform the future of work so that it is more equitable, efficient, and effective for everyone involved— individuals, training and education providers, employers, and policymakers.
Mark Zuckerberg, CEO, Meta, took part in the first-ever Metaverse interview using photo-realistic virtual avatars, demonstrating the Metaverse’s capability for virtual communication.
Zuckerberg appeared on the Lex Fridman podcast, using scans of both Fridman and Zuckerberg to create realistic avatars instead of using a live video feed. A computer model of the avatar’s faces and bodies are put into a Codec, using a headset to send an encoded version of the avatar.
The interview explored the future of AI in the metaverse, as well as the Quest 3 headset and the future of humanity.
What if you could have a conversation with your notes?That question has consumed a corner of the internet recently, as companies like Dropbox, Box, Notion, and others have built generative AI tools that let you interact with and create new things from the data you already have in their systems.
Google’s version of this is called NotebookLM. It’s an AI-powered research tool that is meant to help you organize and interact with your own notes.
That got me to thinking…
What if the presenter/teacher/professor/trainer/preacher provided a set of notes for the AI to compare to the readers’ notes?
That way, the AI could see the discrepancies between what the presenter wanted their audience to learn/hear and what was actually being learned/heard. In a sort of digital Socratic Method, the AI could then generate some leading questions to get the audience member to check their thinking/understanding of the topic.
The end result would be that the main points were properly communicated/learned/received.
Why it matters: The best AI assistants will be the ones that require the least prompting. They’ll get to know who you are, what you need, and your modus operandi. Profiles are a good starting point, but we believe the game-changer will be larger context windows (that’s nerd-speak for the amount of context ChatGPT can handle). .
From DSC: And how about taking this a step further and remembering — or being able to access — our constantly updated Cloud-Based Learning Profiles?
My hypothesis and research suggest that as bar associations and the ABA begin to recognize the on-going systemic issues of high-cost legal education, growing legal deserts (where no lawyer serves a given population), on-going and pervasive access to justice issues, and a public that is already weary of the legal system – alternative options that are already in play might become more supported.
What might that look like?
The combination of AI-assisted education with traditional legal apprenticeships has the potential to create a rich, flexible, and engaging learning environment. Here are three scenarios that might illustrate what such a combination could look like:
Scenario One – Personalized Curriculum Development
Scenario Two – On-Demand Tutoring and Mentoring
Scenario Three – AI-assisted Peer Networks and Collaborative Learning:
We know that there are challenges – a threat to human jobs, the potential implications for cyber security and data theft, or perhaps even an existential threat to humanity as a whole. But we certainly don’t yet have a full understanding of all of the implications. In fact, a World Economic Forum report recently stated that organizations “may currently underappreciate AI-related risks,” with just four percent of leaders considering the risk level to be “significant.”
A survey carried out by analysts Baker McKenzie concluded that many C-level leaders are over-confident in their assessments of organizational preparedness in relation to AI. In particular, it exposed concerns about the potential implications of biased data when used to make HR decisions.
AI & lawyer training: How law firms can embrace hybrid learning & development — thomsonreuters.com A big part of law firms’ successful adaptation to the increased use of ChatGPT and other forms of generative AI, may depend upon how firmly they embrace online learning & development tools designed for hybrid work environments
Excerpt:
As law firms move forward in using of advanced artificial intelligence such as ChatGPT and other forms of generative AI, their success may hinge upon how they approach lawyer training and development and what tools they enlist for the process.
One of the tools that some law firms use to deliver a new, multi-modal learning environment is an online, video-based learning platform, Hotshot, that delivers more than 250 on-demand courses on corporate, litigation, and business skills.
Ian Nelson, co-founder of Hotshot, says he has seen a dramatic change in how law firms are approaching learning & development (L&D) in the decade or so that Hotshot has been active. He believes the biggest change is that 10 years ago, firms hadn’t yet embraced the need to focus on training and development.
From DSC: Heads up law schools. Are you seeing/hearing this!?
Are we moving more towards a lifelong learning model within law schools?
If not, shouldn’t we be doing that?
Are LLM programs expanding quickly enough? Is more needed?
A few current categories of AI in Edtech particularly jump out:
Teacher Productivity and Joy: Tools to make educators’ lives easier (and more fun?) by removing some of the more rote tasks of teaching, like lesson planning (we counted at least 8 different tools for lesson planning), resource curation and data collection.
Personalization and Learning Delivery: Tools to tailor instruction to the particular interests, learning preferences and preferred media consumption of students. This includes tools that convert text to video, video to text, text to comic books, Youtube to notes, and many more.
Study and Course Creation Tools: Tools for learners to automatically make quizzes, flashcards, notes or summaries of material, or even to automatically create full courses from a search term.
AI Tutors, Chatbots and Teachers: There will be no shortage of conversational AI “copilots” (which may take many guises) to support students in almost any learning context. Many Edtech companies launched their own during the conference. Possible differentiators here could be personality, safety, privacy, access to a proprietary or specific data set, or bots built on proprietary LLMs.
Simplifying Complex Processes: One of the most inspiring conversations of the conference for me was with Tiffany Green, founder of Uprooted Academy, about how AI can and should be used to remove bureaucratic barriers to college for underrepresented students (for example, used to autofill FAFSA forms, College Applications, to search for schools and access materials, etc). This is not the only complex bureaucratic process in education.
Educational LLMs: The race is on to create usable large language models for education that are safe, private, appropriate and classroom-ready. Merlyn Mind is working on this, and companies that make LLMs are sprouting up in other sectors…
This week I spent a few days at the ASU/GSV conference and ran into 7,000 educators, entrepreneurs, and corporate training people who had gone CRAZY for AI.
No, I’m not kidding. This community, which makes up people like training managers, community college leaders, educators, and policymakers is absolutely freaked out about ChatGPT, Large Language Models, and all sorts of issues with AI. Now don’t get me wrong: I’m a huge fan of this. But the frenzy is unprecedented: this is bigger than the excitement at the launch of the i-Phone.
Second, the L&D market is about to get disrupted like never before. I had two interactive sessions with about 200 L&D leaders and I essentially heard the same thing over and over. What is going to happen to our jobs when these Generative AI tools start automatically building content, assessments, teaching guides, rubrics, videos, and simulations in seconds?
The answer is pretty clear: you’re going to get disrupted. I’m not saying that L&D teams need to worry about their careers, but it’s very clear to me they’re going to have to swim upstream in a big hurry. As with all new technologies, it’s time for learning leaders to get to know these tools, understand how they work, and start to experiment with them as fast as you can.
Speaking of the ASU+GSV Summit, see this posting from Michael Moe:
Last week, the 14th annual ASU+GSV Summit hosted over 7,000 leaders from 70+ companies well as over 900 of the world’s most innovative EdTech companies. Below are some of our favorite speeches from this year’s Summit…
High-quality tutoring is one of the most effective educational interventions we have – but we need both humans and technology for it to work. In a standing-room-only session, GSE Professor Susanna Loeb, a faculty lead at the Stanford Accelerator for Learning, spoke alongside school district superintendents on the value of high-impact tutoring. The most important factors in effective tutoring, she said, are (1) the tutor has data on specific areas where the student needs support, (2) the tutor has high-quality materials and training, and (3) there is a positive, trusting relationship between the tutor and student. New technologies, including AI, can make the first and second elements much easier – but they will never be able to replace human adults in the relational piece, which is crucial to student engagement and motivation.
ChatGPT, Bing Chat, Google’s Bard—AI is infiltrating the lives of billions.
The 1% who understand it will run the world.
Here’s a list of key terms to jumpstart your learning:
Being “good at prompting” is a temporary state of affairs.The current AI systems are already very good at figuring out your intent, and they are getting better. Prompting is not going to be that important for that much longer. In fact, it already isn’t in GPT-4 and Bing. If you want to do something with AI, just ask it to help you do the thing. “I want to write a novel, what do you need to know to help me?” will get you surprisingly far.
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The best way to use AI systems is not to craft the perfect prompt, but rather to use it interactively. Try asking for something. Then ask the AI to modify or adjust its output. Work with the AI, rather than trying to issue a single command that does everything you want. The more you experiment, the better off you are. Just use the AI a lot, and it will make a big difference – a lesson my class learned as they worked with the AI to create essays.
From DSC: Agreed –> “Being “good at prompting” is a temporary state of affairs.” The User Interfaces that are/will be appearing will help greatly in this regard.
From DSC: Bizarre…at least for me in late April of 2023:
FaceTiming live with AI… This app came across the @ElunaAI Discord and I was very impressed with its responsiveness, natural expression and language, etc…
Feels like the beginning of another massive wave in consumer AI products.
The rise of AI-generated music has ignited legal and ethical debates, with record labels invoking copyright law to remove AI-generated songs from platforms like YouTube.
Tech companies like Google face a conundrum: should they take down AI-generated content, and if so, on what grounds?
Some artists, like Grimes, are embracing the change, proposing new revenue-sharing models and utilizing blockchain-based smart contracts for royalties.
The future of AI-generated music presents both challenges and opportunities, with the potential to create new platforms and genres, democratize the industry, and redefine artist compensation.
The Need for AI PD — from techlearning.com by Erik Ofgang Educators need training on how to effectively incorporate artificial intelligence into their teaching practice, says Lance Key, an award-winning educator.
“School never was fun for me,” he says, hoping that as an educator he could change that with his students. “I wanted to make learning fun.” This ‘learning should be fun’ philosophy is at the heart of the approach he advises educators take when it comes to AI.
At its 11th annual conference in 2023, educational company Coursera announced it is adding ChatGPT-powered interactive ed tech tools to its learning platform, including a generative AI coach for students and an AI course-building tool for teachers. It will also add machine learning-powered translation, expanded VR immersive learning experiences, and more.
Coursera Coach will give learners a ChatGPT virtual coach to answer questions, give feedback, summarize video lectures and other materials, give career advice, and prepare them for job interviews. This feature will be available in the coming months.
From DSC: Yes…it will be very interesting to see how tools and platforms interact from this time forth. The term “integration” will take a massive step forward, at least in my mind.
A New Era for Education — from linkedin.com by Amit Sevak, CEO of ETS and Timothy Knowles, President of the Carnegie Foundation for the Advancement of Teaching
Excerpt (emphasis DSC):
It’s not every day you get to announce a revolution in your sector. But today, we’re doing exactly that. Together, we are setting out to overturn 117 years of educational tradition. … The fundamental assumption [of the Carnegie Unit] is that time spent in a classroom equals learning. This formula has the virtue of simplicity. Unfortunately, a century of research tells us that it’s woefully inadequate.
From DSC: It’s more than interesting to think that the Carnegie Unit has outlived its usefulness and is breaking apart. In fact, the thought is very profound.
If that turns out to be the case, the ramifications will be enormous and we will have the opportunity to radically reinvent/rethink/redesign what our lifelong learning ecosystems will look like and provide.
So I appreciate what Amit and Timothy are saying here and I appreciate their relaying what the new paradigm might look like. It goes with the idea of using design thinking to rethink how we build/reinvent our learning ecosystems. They assert:
It’s time to change the paradigm. That’s why ETS and the Carnegie Foundation have come together to design a new future of assessment.
Whereas the Carnegie Unit measures seat time, the new paradigm willmeasureskills—with a focus on the ones we know are most important for success in career and in life.
Whereas the Carnegie Unit never leaves the classroom, the new paradigm willcapture learning wherever it takes place—whether that is in after-school activities, during a work-experience placement, in an internship, on an apprenticeship, and so on.
Whereas the Carnegie Unit offers only one data point—pass or fail—the new paradigm willgenerate insights throughout the learning process, the better to guide students, families, educators, and policymakers.
I could see this type of information being funneled into peoples’ cloud-based learner profiles — which we as individuals will own and determine who else can access them. I diagrammed this back in January of 2017 using blockchain as the underlying technology. That may or may not turn out to be the case. But the concept will still hold I think — regardless of the underlying technology(ies).
For example, we are seeing a lot more articles regarding things like Comprehensive Learner Records (CLR) or Learning and Employment Records (LER; examplehere), and similar items.
Speaking of reinventing our learning ecosystems, also see:
