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)
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.
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.
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.
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).
In 2024, digital accessibility lawsuits pose a growing legal risk, particularly for consumer goods and services businesses. With increasing attention to web accessibility compliance and shifting legal trends, legal departments must stay informed and proactively protect their organizations.
*While ADA lawsuits are a significant concern in the U.S., companies serving customers in the EU via their websites will soon face additional requirements under the European Accessibility Act (EAA). Compliance with the EAA will be crucial to avoiding legal risks in Europe. … Below, we explore critical insights into the current landscape of digital accessibility lawsuits and strategies for mitigating these risks.
This week, as I kick off the 20th cohort of my AI-Learning Design bootcamp, I decided to do some analysis of the work habits of the hundreds of amazing AI-embracing instructional designers who I’ve worked with over the last year or so.
My goal was to answer the question: which AI tools do we use most in the instructional design process, and how do we use them?
Here’s where we are in September, 2024:
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Developing Your Approach to Generative AI — from scholarlyteacher.com by Caitlin K. Kirby, Min Zhuang, Imari Cheyne Tetu, & Stephen Thomas (Michigan State University)
As generative AI becomes integrated into workplaces, scholarly work, and students’ workflows, we have the opportunity to take a broad view of the role of generative AI in higher education classrooms. Our guiding questions are meant to serve as a starting point to consider, from each educator’s initial reaction and preferences around generative AI, how their discipline, course design, and assessments may be impacted, and to have a broad view of the ethics of generative AI use.
AI technology tools hold remarkable promise for providing more accessible, equitable, and inclusive learning experiences for students with disabilities.
Accessibility and AI— from teaching.virginia.edu; via Derek Bruff This collection explores the intersection of AI and accessibility, highlighting how AI can both support and pose challenges to students with disabilities. It offers practical insights, strategies, and tools for fostering inclusive, accessible learning environments.
86% of students globally are regularly using AI in their studies, with 54% of them using AI on a weekly basis, the recent Digital Education Council Global AI Student Survey found.
ChatGPT was found to be the most widely used AI tool, with 66% of students using it, and over 2 in 3 students reported using AI for information searching.
Despite their high rates of AI usage, 1 in 2 students do not feel AI ready. 58% reported that they do not feel that they had sufficient AI knowledge and skills, and 48% do not feel adequately prepared for an AI-enabled workplace.
The Post-AI Instructional Designer— from drphilippahardman.substack.com by Dr. Philippa Hardman How the ID role is changing, and what this means for your key skills, roles & responsibilities
Specifically, the study revealed that teachers who reported most productivity gains were those who used AI not just for creating outputs (like quizzes or worksheets) but also for seeking input on their ideas, decisions and strategies.
Those who engaged with AI as a thought partner throughout their workflow, using it to generate ideas, define problems, refine approaches, develop strategies and gain confidence in their decisions gained significantly more from their collaboration with AI than those who only delegated functional tasks to AI.
Leveraging Generative AI for Inclusive Excellence in Higher Education — from er.educause.edu by Lorna Gonzalez, Kristi O’Neil-Gonzalez, Megan Eberhardt-Alstot, Michael McGarry and Georgia Van Tyne Drawing from three lenses of inclusion, this article considers how to leverage generative AI as part of a constellation of mission-centered inclusive practices in higher education.
The hype and hesitation about generative artificial intelligence (AI) diffusion have led some colleges and universities to take a wait-and-see approach.Footnote1 However, AI integration does not need to be an either/or proposition where its use is either embraced or restricted or its adoption aimed at replacing or outright rejecting existing institutional functions and practices. Educators, educational leaders, and others considering academic applications for emerging technologies should consider ways in which generative AI can complement or augment mission-focused practices, such as those aimed at accessibility, diversity, equity, and inclusion. Drawing from three lenses of inclusion—accessibility, identity, and epistemology—this article offers practical suggestions and considerations that educators can deploy now. It also presents an imperative for higher education leaders to partner toward an infrastructure that enables inclusive practices in light of AI diffusion.
An example way to leverage AI:
How to Leverage AI for Identity Inclusion Educators can use the following strategies to intentionally design instructional content with identity inclusion in mind.
Provide a GPT or AI assistant with upcoming lesson content (e.g., lecture materials or assignment instructions) and ask it to provide feedback (e.g., troublesome vocabulary, difficult concepts, or complementary activities) from certain perspectives. Begin with a single perspective (e.g., first-time, first-year student), but layer in more to build complexity as you interact with the GPT output.
Gen AI’s next inflection point: From employee experimentation to organizational transformation — from mckinsey.com by Charlotte Relyea, Dana Maor, and Sandra Durth with Jan Bouly As many employees adopt generative AI at work, companies struggle to follow suit. To capture value from current momentum, businesses must transform their processes, structures, and approach to talent.
To harness employees’ enthusiasm and stay ahead, companies need a holistic approach to transforming how the whole organization works with gen AI; the technology alone won’t create value.
Our research shows that early adopters prioritize talent and the human side of gen AI more than other companies (Exhibit 3). Our survey shows that nearly two-thirds of them have a clear view of their talent gaps and a strategy to close them, compared with just 25 percent of the experimenters. Early adopters focus heavily on upskilling and reskilling as a critical part of their talent strategies, as hiring alone isn’t enough to close gaps and outsourcing can hinder strategic-skills development.Finally, 40 percent of early-adopter respondents say their organizations provide extensive support to encourage employee adoption, versus 9 percent of experimenter respondents.
Change blindness — from oneusefulthing.org by Ethan Mollick 21 months later
I don’t think anyone is completely certain about where AI is going, but we do know that things have changed very quickly, as the examples in this post have hopefully demonstrated. If this rate of change continues, the world will look very different in another 21 months. The only way to know is to live through it.
Over the subsequent weeks, I’ve made other adjustments, but that first one was the one I asked myself:
What are you doing?
Why are you doing it that way?
How could you change that workflow with AI?
Applying the AI to the workflow, then asking, “Is this what I was aiming for? How can I improve the prompt to get closer?”
Documenting what worked (or didn’t). Re-doing the work with AI to see what happened, and asking again, “Did this work?”
So, something that took me WEEKS of hard work, and in some cases I found impossible, was made easy. Like, instead of weeks, it takes 10 minutes. The hard part? Building the prompt to do what I want, fine-tuning it to get the result. But that doesn’t take as long now.
AI is welcomed by those with dyslexia, and other learning issues, helping to mitigate some of the challenges associated with reading, writing, and processing information. Those who want to ban AI want to destroy the very thing that has helped most on accessibility. Here are 10 ways dyslexics, and others with issues around text-based learning, can use AI to support their daily activities and learning.
Are U.S. public schools lagging behind other countries like Singapore and South Korea in preparing teachers and students for the boom of generative artificial intelligence? Or are our educators bumbling into AI half-blind, putting students’ learning at risk?
Or is it, perhaps, both?
Two new reports, coincidentally released on the same day last week, offer markedly different visions of the emerging field: One argues that schools need forward-thinking policies for equitable distribution of AI across urban, suburban and rural communities. The other suggests they need something more basic: a bracing primer on what AI is and isn’t, what it’s good for and how it can all go horribly wrong.
Bite-Size AI Content for Faculty and Staff— from aiedusimplified.substack.com by Lance Eaton Another two 5-tips videos for faculty and my latest use case: creating FAQs!
Despite possible drawbacks, an exciting wondering has been—What if AI was a tipping point helping us finally move away from a standardized, grade-locked, ranking-forced, batched-processing learning model based on the make believe idea of “the average man” to a learning model that meets every child where they are at and helps them grow from there?
I get that change is indescribably hard and there are risks. But the integration of AI in education isn’t a trend. It’s a paradigm shift that requires careful consideration, ongoing reflection, and a commitment to one’s core values. AI presents us with an opportunity—possibly an unprecedented one—to transform teaching and learning, making it more personalized, efficient, and impactful. How might we seize the opportunity boldly?
California and NVIDIA Partner to Bring AI to Schools, Workplaces — from govtech.com by Abby Sourwine The latest step in Gov. Gavin Newsom’s plans to integrate AI into public operations across California is a partnership with NVIDIA intended to tailor college courses and professional development to industry needs.
California Gov. Gavin Newsom and tech company NVIDIA joined forces last week to bring generative AI (GenAI) to community colleges and public agencies across the state. The California Community Colleges Chancellor’s Office (CCCCO), NVIDIA and the governor all signed a memorandum of understanding (MOU) outlining how each partner can contribute to education and workforce development, with the goal of driving innovation across industries and boosting their economic growth.
Listen to anything on the go with the highest-quality voices — from elevenlabs.io; via The Neuron
The ElevenLabs Reader App narrates articles, PDFs, ePubs, newsletters, or any other text content. Simply choose a voice from our expansive library, upload your content, and listen on the go.
Per The Neuron
Some cool use cases:
Judy Garland can teach you biology while walking to class.
James Dean can narrate your steamy romance novel.
Sir Laurence Olivier can read you today’s newsletter—just paste the web link and enjoy!
Why it’s important: ElevenLabs shared how major Youtubers are using its dubbing services to expand their content into new regions with voices that actually sound like them (thanks to ElevenLabs’ ability to clone voices).
Oh, and BTW, it’s estimated that up to 20% of the population may have dyslexia. So providing people an option to listen to (instead of read) content, in their own language, wherever they go online can only help increase engagement and communication.
How Generative AI Improves Parent Engagement in K–12 Schools — from edtechmagazine.com by Alexadner Slagg With its ability to automate and personalize communication, generative artificial intelligence is the ideal technological fix for strengthening parent involvement in students’ education.
As generative AI tools populate the education marketplace, the technology’s ability to automate complex, labor-intensive tasks and efficiently personalize communication may finally offer overwhelmed teachers a way to effectively improve parent engagement.
… These personalized engagement activities for students and their families can include local events, certification classes and recommendations for books and videos. “Family Feed might suggest courses, such as an Adobe certification,” explains Jackson. “We have over 14,000 courses that we have vetted and can recommend. And we have books and video recommendations for students as well.”
Including personalized student information and an engagement opportunity makes it much easier for parents to directly participate in their children’s education.
Will AI Shrink Disparities in Schools, or Widen Them? — edsurge.com by Daniel Mollenkamp Experts predict new tools could boost teaching efficiency — or create an “underclass of students” taught largely through screens.
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)
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.
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.
In a busy classroom, it can be daunting to meet the varied learning needs of all your students. Knowing you’re also responsible for implementing instructional accommodations and modifications in students’ IEPs and 504 plans can make it feel even more challenging. But with the right information, you can provide these important supports to help all students thrive.
Here are key concepts to keep in mind and steps you can take to implement accommodations and modifications for your students.
BALTIMORE — What if your child didn’t go to school?
Believe it or not, some parents don’t send their children to school five days a week, and it’s called unschooling.
It is a growing and sometimes controversial approach to homeschooling.
Rather than using a defined curriculum, unschooling parents trust their kids to learn organically. Unschoolers are focused more on the experimental process of learning and becoming educated, rather than with “doing or going to school.”
Public schools are particularly vulnerable to pressure, Cuban said on a call with EdSurge. That’s because national problems tend to become school ones, Cuban says. Schools have to walk a “tightrope,” striking a balance that is both stable for students and able to adapt to changes in the broader society, he says.
Pressure on schools to respond to new issues often ends up altering curricula or introducing new courses, because that’s the easiest part of the public education system to change, Cuban argues. But classrooms are isolated from the superintendent’s office, the school board and other “policy elites” who push change, he says.
Every teacher at her school, the Health Sciences High and Middle College, in San Diego, shares in the responsibility of teaching students literacy skills, regardless of the subject they teach. That’s because so many students, even incoming ninth graders, arrive at the school without basic reading skills, according to Douglas Fisher, an administrator at the school. While some students also receive one-on-one remediation, Fisher said that research shows those interventions aren’t enough to close the gap.
“We have kids that on our benchmark knowledge assessments are scoring what is the equivalent of second grade, first grade, fourth grade,” said Fisher, who is also a professor and chair of educational leadership at San Diego State University. Yet, by the time students graduate, he said, the goal at the secondary school is that they have “reading levels ready for college.”
Some of the nation’s biggest tech companies have announced efforts to reskill people to avoid job losses caused by artificial intelligence, even as they work to perfect the technology that could eliminate millions of those jobs.
It’s fair to ask, however: What should college students and prospective students, weighing their choices and possible time and financial expenses, think of this?
The news this spring was encouraging for people seeking to reinvent their careers to grab middle-class jobs and a shot at economic security.
For too long, students with learning disabilities have struggled to navigate a traditional education system that often fails to meet their unique needs. But what if technology could help bridge the gap, offering personalized support and unlocking the full potential of every learner?
Artificial intelligence (AI) is emerging as a powerful ally in special education, offering many opportunities to create more inclusive and effective learning experiences for students with diverse learning profiles.
*SearchGPT
*Smaller & on-device (phones, glasses) AI models
*AI TAs
*Access barriers decline, equity barriers grow
*Claude Artifacts and Projects
*Agents, and Agent Teams of a million+
*Humanoid robots & self-driving cars
*AI Curricular integration
*Huge video and video-segmentation gains
*Writing Detectors — The final blow
*AI Unemployment, Student AI anxiety, and forward-thinking approaches
*Alternative assessments
Since then, two more pieces have been widely shared including this piece from Inside Higher Ed by Kathryn Palmer (and to which I was interviewed and mentioned in) and this piece from Chronicle of Higher Ed by Christa Dutton. Both pieces try to cover the different sides talking to authors, scanning the commentary online, finding some experts to consult and talking to the publishers. It’s one of those things that can feel like really important and also probably only to a very small amount of folks that find themselves thinking about academic publishing, scholarly communication, and generative AI.
In one respect, we already have a partial answer. Over the last thirty years, there has been a dramatic shift from a teaching-centered to a learning-centered education model. High-impact practices, such as service learning, undergraduate research, and living-learning communities, are common and embraced because they help students see the real-world connections of what they are learning and make learning personal.11
Therefore, I believe we must double down on a learning-centered model in the age of AI.
The first step is to fully and enthusiastically embrace AI.
…
The second step is to find the “jagged technological frontier” of using AI in the college classroom.
We’re starting to roll out advanced Voice Mode to a small group of ChatGPT Plus users. Advanced Voice Mode offers more natural, real-time conversations, allows you to interrupt anytime, and senses and responds to your emotions. pic.twitter.com/64O94EhhXK
Why it matters: AI is slowly shifting from a tool we text/prompt with, to an intelligence that we collaborate, learn, and grow with. Advanced Voice Mode’s ability to understand and respond to emotions in real-time convos could also have huge use cases in everything from customer service to mental health support.
“Every single restaurant, every single website will probably, in the future, have these AIs …” Huang said.
“…just like every business has an email address and a website and a social media account, I think, in the future, every business is going to have an AI,” Zuckerberg responded.
…
More broadly, the advancement of AI across a broad ecosystem promises to supercharge human productivity, for example, by giving every human on earth a digital assistant — or assistants — allowing people to live richer lives that they can interact with quickly and fluidly.
DC: Nvidia continues 2get rocked as I think people are taking their gains & getting nervous about AI’s ability 2deliver healthy ROI’s. But I think co’s will let many people go as a result of various AI’s impacts. They WILL get their ROI. But it may be at a great cost to some pple
From DSC: Today was a MUCH better day for Nvidia however (up 12.81%). But it’s been very volatile in the last several weeks — as people and institutions ask where the ROI’s are going to come from.
DC: What do you think about this? What about if this occurred at *your* place of employment? https://t.co/CWc09Cm7n1
This last wave of AI releases is truly making us more capable than ever.
Here are 10 amazing examples of my favorite new tool ?
This is Claude 3.5 Sonnet with Artifacts, a new feature that allows people to go from a super simple prompt to immediate previews of games, code… pic.twitter.com/w4kkT25fch
9 compelling reasons to learn how to use AI Chatbots — from interestingengineering.com by Atharva Gosavi AI Chatbots are conversational agents that can act on your behalf and converse with humans – a futuristic novelty that is already getting people excited about its usage in improving efficiency.
7. Accessibility and inclusivity
Chatbots can be designed to support multiple languages and accessibility needs, making services more inclusive. They can cater to users with disabilities by providing voice interaction capabilities and simplifying access to information. Understanding how to develop inclusive chatbots can help you contribute to making technology more accessible to everyone, a crucial aspect in today’s diverse society.
8. Future-proofing your skills
AI and automation are the future of work. Having the skills of building AI chatbots is a great way to future-proof your skills, and given the rising trajectory of AI, it’ll be a demanding skill in the market in the years to come. Staying ahead of technological trends is a great way to ensure you remain relevant and competitive in the job market.
Top 7 generative AI use cases for business— from cio.com by Grant Gross Advanced chatbots, digital assistants, and coding helpers seem to be some of the sweet spots for gen AI use so far in business.
Many AI experts say the current use cases for generative AI are just the tip of the iceberg. More uses cases will present themselves as gen AIs get more powerful and users get more creative with their experiments.
However, a handful of gen AI use cases are already bubbling up. Here’s a look at the most popular and promising.
A newly issued federal rule to ensure web content and mobile apps are accessible for people with disabilities will require public K-12 and higher education institutions to do a thorough inventory of their digital materials to make sure they are in compliance, accessibility experts said.
The update to regulations for Title II of the Americans with Disabilities Act, published April 24 by the U.S. Department of Justice, calls for all state and local governments to verify that their web content — including mobile apps and social media postings — is accessible for those with vision, hearing, cognitive and manual dexterity disabilities.
These key points underscore the importance of addressing challenges, enhancing policies, and leveraging AI technologies to create more inclusive opportunities for individuals with disabilities in the labor market.
The Adobe PDF (Portable Document Format) is one of the most popular formats for online documents. Put simply, if you need to download a tax form or review a company brochure, you’ll probably download a PDF to do so.
Unfortunately, many PDFs aren’t accessible for users with disabilities. A 2023 report from the Department of Justice (DOJ) found that only 20% of the government’s most-downloaded PDFs were conformant with federal accessibility standards. Private businesses also struggle to meet basic accessibility requirements.
The good news: If you think about accessibility when authoring your documents, you can provide a better experience for readers. Here’s how to get started.
What if a person with a visual impairment could receive audio assistance reading a map — and detailed instructions on how to navigate their local railway system? Or what if they could use image-to-text technology to quickly discern what’s in their fridge, along with recipe suggestions and a shopping list for their grocery delivery order?
AI-powered tools that do just that are now a reality thanks to Danish startup Be My Eyes, which uses the visual input capability of GPT-4 to create “virtual volunteers” for people who are blind or vision-impaired. It’s just one example of how advancements in AI are transforming the digital accessibility landscape.
Wagner herself recently relied on the power of collegial conversations to probe the question: What’s on the minds of educators as they make ready for the growing influence of AI in higher education? CT asked her for some takeaways from the process.
We are in the very early days of seeing how AI is going to affect education. Some of us are going to need to stay focused on the basic research to test hypotheses. Others are going to dive into laboratory “sandboxes” to see if we can build some new applications and tools for ourselves. Still others will continue to scan newsletters like ProductHunt every day to see what kinds of things people are working on. It’s going to be hard to keep up, to filter out the noise on our own. That’s one reason why thinking with colleagues is so very important.
We are interested how K-12 education will change in terms of foundational learning. With in-class, active learning designs, will younger students do a lot more intensive building of foundational writing and critical thinking skills before they get to college?
The Human in the Loop: AI is built using math: think of applied statistics on steroids. Humans will be needed more than ever to manage, review and evaluate the validity and reliability of results. Curation will be essential.
We will need to generate ideas about how to address AI factors such as privacy, equity, bias, copyright, intellectual property, accessibility, and scalability.
Have other institutions experimented with AI detection and/or have held off on emerging tools related to this? We have just recently adjusted guidance and paused some tools related to this given the massive inaccuracies in detection (and related downstream issues in faculty-elevated conduct cases)
Even though we learn repeatedly that innovation has a lot to do with effective project management and a solid message that helps people understand what they can do to implement change, people really need innovation to be more exciting and visionary than that. This is the place where we all need to help each other stay the course of change.
I have been talking to a lot of people about Generative AI, from teachers to business executives to artists to people actually building LLMs. In these conversations, a few key questions and themes keep coming up over and over again. Many of those questions are more informed by viral news articles about AI than about the real thing, so I thought I would try to answer a few of the most common, to the best of my ability.
I can’t blame people for asking because, for whatever reason, the companies actually building and releasing Large Language Models often seem allergic to providing any sort of documentation or tutorial besides technical notes. I was given much better documentation for the generic garden hose I bought on Amazon than for the immensely powerful AI tools being released by the world’s largest companies. So, it is no surprise that rumor has been the way that people learn about AI capabilities.
Currently, there are only really three AIs to consider: (1) OpenAI’s GPT-4 (which you can get access to with a Plus subscription or via Microsoft Bing in creative mode, for free), (2) Google’s Bard (free), or (3) Anthropic’s Claude 2 (free, but paid mode gets you faster access). As of today, GPT-4 is the clear leader, Claude 2 is second best (but can handle longer documents), and Google trails, but that will likely change very soon when Google updates its model, which is rumored to be happening in the near future.
