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“History repeats itself…again. The ways of the world/power continue on.” [Christian] + other items re: AI

On 11/27/2023, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, Asia, change, computer science, corporate / business world, dangers of the status quo, Daniel S. Christian, digital learning, digital video, emerging technologies, experimentation, future, game-changing environment, Google, history, intelligent systems, law schools, leadership, legislatures / government / legal, NVIDIA, organizational change, pace of change, platforms, productivity / tips and tricks, society, the downsides of technology, United States, workplace, by Daniel Christian

Expanding Bard’s understanding of YouTube videos — via AI Valley

  • What: We’re taking the first steps in Bard’s ability to understand YouTube videos. For example, if you’re looking for videos on how to make olive oil cake, you can now also ask how many eggs the recipe in the first video requires.
  • Why: We’ve heard you want deeper engagement with YouTube videos. So we’re expanding the YouTube Extension to understand some video content so you can have a richer conversation with Bard about it.

Reshaping the tree: rebuilding organizations for AI — from oneusefulthing.org by Ethan Mollick
Technological change brings organizational change.

I am not sure who said it first, but there are only two ways to react to exponential change: too early or too late. Today’s AIs are flawed and limited in many ways. While that restricts what AI can do, the capabilities of AI are increasing exponentially, both in terms of the models themselves and the tools these models can use. It might seem too early to consider changing an organization to accommodate AI, but I think that there is a strong possibility that it will quickly become too late.

From DSC:
Readers of this blog have seen the following graphic for several years now, but there is no question that we are in a time of exponential change. One would have had an increasingly hard time arguing the opposite of this perspective during that time.

 

 

Nvidia’s revenue triples as AI chip boom continues — from cnbc.com by Jordan Novet; via GSV

KEY POINTS

  • Nvidia’s results surpassed analysts’ projections for revenue and income in the fiscal fourth quarter.
  • Demand for Nvidia’s graphics processing units has been exceeding supply, thanks to the rise of generative artificial intelligence.
  • Nvidia announced the GH200 GPU during the quarter.

Here’s how the company did, compared to the consensus among analysts surveyed by LSEG, formerly known as Refinitiv:

  • Earnings: $4.02 per share, adjusted, vs. $3.37 per share expected
  • Revenue: $18.12 billion, vs. $16.18 billion expected

Nvidia’s revenue grew 206% year over year during the quarter ending Oct. 29, according to a statement. Net income, at $9.24 billion, or $3.71 per share, was up from $680 million, or 27 cents per share, in the same quarter a year ago.

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“Thomson Reuters’ AI debut signals a new era of widespread AI integration in legaltech” [Black] + other legaltech-related items

On 11/22/2023, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, game-changing environment, innovation, legal technologies, legislatures / government / legal, tools, vendors, by Daniel Christian

Thomson Reuters’ AI debut signals a new era of widespread AI integration in legaltech — from nydailyrecord.com by Nicole Black

It shouldn’t surprise you to learn that legal technology companies have joined the fray. Since early 2023, over one hundred announcements from legal technology companies have emerged, detailing plans to incorporate generative AI functionality into their products. Although most products are stillfirm;eta, rest assured that regardless of the software platforms used in your firm, you can expect that generative AI will soon be seamlessly integrated into the tools that are part of the daily workflows of legal professionals in your firm.

Proof in point: Wednesday’s generative AI announcements from Thomson Reuters offer strong evidence that we’re entering a new era of widespread AI integration. For Thomson Reuter’s legal customers, the integrated generative AI experience will soon be a reality and readily accessible across several different products. This newfound capability largely stems from leveraging CoCounsel, a generative AI legal assistant tool acquired by Thomson Reuters as part of the acquisition of Casetext for $650 million, which was completed in August.

Ironcrow AI’s LLM Sandbox: Setting an Industry Standard — from mccrus.com by McCoy Russell; with thanks to Mr. Justin Wagner out on LinkedIn for this resource

As an innovative firm, McCoy Russell has been at the forefront of patent law with its development and use of proprietary AI software via its software arm Ironcrow AI. Recently, Ironcrow has invested substantial efforts to create a specialized AI LLM Sandbox as a key tool for patent professionals.

Ironcrow is excited to announce a groundbreaking achievement in the field of AI/ML for Patent Law professionals – Ironcrow’s specialized AI LLM Sandbox has achieved a score above the 70% threshold required to pass the patent bar exam, using a test set of questions. While other researchers have developed tools to pass a state bar exam, none have attempted to pass the specialized patent bar exam administered by the USPTO.

This remarkable feat showcases the innovation by the Ironcrow and McCoy Russell partnership and the ability of the LLM Sandbox’s “Interrogate” feature to answer questions based on the knowledge of the patent procedure. The Sandbox can provide well-cited answers along with relevant excerpts from the MPEP, etc., to its users. This unique feature sets Ironcrow AI’s LLM Sandbox apart from other systems in the market.

 

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“The Wolters Kluwer Future Ready Lawyer Report: Embracing innovation, adapting to change” + other legaltech related items

On 11/17/2023, in 21st century, 24x7x365 access, Access to Justice (A2J), change, changing business models, emerging technologies, future, game-changing environment, innovation, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, pace of change, by Daniel Christian

Don’t Believe the Hype? Practical Thoughts About Using AI in Legal (Stephen Embry – TechLaw Crossroads) — from tlpodcast.com by Stephen Embry

Despite the hype and big promises about AI, if it is used correctly, could it be the differentiator that sets good legal professionals apart from the pack? Stephen Embry offers a good argument for this in the latest episode.

Stephen is a long-time attorney and the legal tech aficionado behind the TechLaw Crossroads blog– a great resource for practical and real-world insight about legal tech and how technology is impacting the practice of law. Embry emphasizes that good lawyers will embrace artificial intelligence to increase efficiency and serve their clients better, leaving more time for strategic thinking and advisory roles.

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AI Pedagogy Project, metaLAB (at) Harvard + other AI-related items in our learning ecosystems

On 11/17/2023, in 21st century, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, colleges, community colleges, emerging technologies, Europe, experimentation, faculty, future, future of higher education, game-changing environment, higher education, innovation, intelligent systems, IT in HE, law schools, leadership, learning ecosystem, United States, universities, by Daniel Christian

AI Pedagogy Project, metaLAB (at) Harvard
Creative and critical engagement with AI in education. A collection of assignments and materials inspired by the humanities, for educators curious about how AI affects their students and their syllabi

AI Guide
Focused on the essentials and written to be accessible to a newcomer, this interactive guide will give you the background you need to feel more confident with engaging conversations about AI in your classroom.

From #47 of SAIL: Sensemaking AI Learning — by George Siemens

Excerpt (emphasis DSC):

Welcome to Sensemaking, AI, and Learning (SAIL), a regular look at how AI is impacting education and learning.

Over the last year, after dozens of conferences, many webinars, panels, workshops, and many (many) conversations with colleagues, it’s starting to feel like higher education, as a system, is in an AI groundhog’s day loop. I haven’t heard anything novel generated by universities. We have a chatbot! Soon it will be a tutor! We have a generative AI faculty council! Here’s our list of links to sites that also have lists! We need AI literacy! My mantra over the last while has been that higher education leadership is failing us on AI in a more dramatic way than it failed us on digitization and online learning. What will your universities be buying from AI vendors in five years because they failed to develop a strategic vision and capabilities today?

AI + the Education System — from drphilippahardman.substack.com Dr. Philippa Hardman
The key to relevance, value & excellence?

The magic school of the future is one that helps students learn to work together and care for each other — from stefanbauschard.substack.com by Stefan Bauschard
AI is going to alter economic and professional structures. Will we alter the educational structures?

(e) What is really required is a significant re-organization of schooling and curriculum. At a meta-level, the school system is focused on developing the type of intelligence I opened with, and the economic value of that is going to rapidly decline.

(f). This is all going to happen very quickly (faster than any previous change in history), and many people aren’t paying attention.  AI is already here.

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Where a developing, new kind of learning ecosystem is likely headed [Christian]

On 11/17/2023, in 21st century, 24x7x365 access, adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, career development, change, changing business models, cloud-based computing / apps / other cloud-related, colleges, communities of practice, community colleges, competency-based learning/education, corporate / business world, corporate universities / corporate training, cost of getting a degree, Daniel S. Christian, digital learning, distance education, education, education technology, educational games / serious games, elearning, emerging technologies, engagement / engaging students, faculty, future, future of higher education, game-changing environment, generational differences, heutagogy, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning from the Living [Class] Room, learning spaces, lifelong learning, love of learning, marketplaces, microlearning, more voice more choice more control, new business models, online learning, online media, online tutoring, personalized/customized learning, platforms, professional development, reinvent, skills, smart/connected TV, social learning / networks, society, streams of content, student-related, teachers, teaching & learning, teaching online, technologies for your home, training / L&D, trends, ubiquitous learning, United States, universities, using teams, vendors, virtual tutoring, vision/possibilities, vocational / trades, workplace, youth, by Daniel Christian

From DSC:
As I’ve long stated on the Learning from the Living [Class]Room vision, we are heading toward a new AI-empowered learning platform — where humans play a critically important role in making this new learning ecosystem work.

Along these lines, I ran into this site out on X/Twitter. We’ll see how this unfolds, but it will be an interesting space to watch.

Project Chiron's vision: Our vision for education Every child will soon have a super-intelligent AI teacher by their side. We want to make sure they instill a love of learning in children.

From DSC:
This future learning platform will also focus on developing skills and competencies. Along those lines, see:

Scale for Skills-First — from the-job.beehiiv.com by Paul Fain
An ed-tech giant’s ambitious moves into digital credentialing and learner records.

A Digital Canvas for Skills
Instructure was a player in the skills and credentials space before its recent acquisition of Parchment, a digital transcript company. But that $800M move made many observers wonder if Instructure can develop digital records of skills that learners, colleges, and employers might actually use broadly.
…

Ultimately, he says, the CLR approach will allow students to bring these various learning types into a coherent format for employers.

Instructure seeks a leadership role in working with other organizations to establish common standards for credentials and learner records, to help create consistency. The company collaborates closely with 1EdTech. And last month it helped launch the 1EdTech TrustEd Microcredential Coalition, which aims to increase quality and trust in digital credentials.

Paul also links to 1EDTECH’s page regarding the Comprehensive Learning Record

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Will students be able to create their own personalized degree programs using GPTs? Plus other items re: AI in our LE’s.

On 11/14/2023, in 21st century, adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, cloud-based computing / apps / other cloud-related, colleges, community colleges, education, education reform, education technology, emerging technologies, experimentation, faculty, future, future of higher education, game-changing environment, higher education, learning, learning ecosystem, more voice more choice more control, personalized/customized learning, platforms, productivity / tips and tricks, universities, by Daniel Christian

From GPTs (pt. 3) — from theneurondaily.com by Noah Edelman

BTW, here are a few GPTs worth checking out today:

  • ConvertAnything—convert images, audio, videos, PDFs, files, & more.
  • editGPT—edit any writing (like Grammarly inside ChatGPT).
  • Grimoire—a coding assistant that helps you build anything!

Some notes from Dan Fitzpatrick – The AI Educator:

Custom GPT Bots:

  • These could help with the creation of interactive learning assistants, aligned with curricula.
  • They can be easily created with natural language programming.
  • Important to note users must have a ChatGPT Plus paid account

Custom GPT Store:

  • Marketplace for sharing and accessing educational GPT tools created by other teachers.
  • A store could offer access to specialised tools for diverse learning needs.
  • A store could enhance teaching strategies when accessing proven, effective GPT applications.

From DSC:
I appreciate Dan’s potential menu of options for a child’s education:

Monday AM: Sports club
Monday PM: Synthesis Online School AI Tutor
Tuesday AM: Music Lesson
Tuesday PM: Synthesis Online School Group Work
Wednesday AM: Drama Rehearsal
Wednesday PM: Synthesis Online School AI Tutor
Thursday AM: Volunteer work
Thursday PM: Private study
Friday AM: Work experience
Friday PM: Work experience

Our daughter has special learning needs and this is very similar to what she is doing. 

Also, Dan has a couple of videos out here at Google for Education:

Tuesday’s AI Ten for Educators (November 14) — from stefanbauschard.substack.com by Stefan Bauschard
Ten AI developments for educators to be aware of

Two boxes. In my May Cottesmore presentation, I put up two boxes:

(a) Box 1 — How educators can use AI to do what they do now (lesson plans, quizzes, tests, vocabulary lists, etc.)

(b) Box 2 — How the education system needs to change because, in the near future (sort of already), everyone is going to have multiple AIs working with them all day, and the premium on intelligence, especially “knowledge-based” intelligence, is going to decline rapidly. It’s hard to think that significant changes in the education system won’t be needed to accommodate that change.

There is a lot of focus on preparing educators to work in Box 1, which is important, if for no other reason than that they can see the power of even the current but limited technologies, but the hard questions are starting to be about Box 2. I encourage you to start those conversations, as the “ed tech” companies already are, and they’ll be happy to provide the answers and the services if you don’t want to.

Practical suggestions: Two AI teams in your institution. Team 1 works on Box A and Team 2 works on Box B.

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“13 Nuggets of AI Wisdom for Higher Education Leaders” [Klitgaard Stricker] + other AI-related items for our learning ecosystems

On 11/10/2023, in 21st century, adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, colleges, community colleges, corporate / business world, corporate universities / corporate training, education, education reform, education technology, emerging technologies, experimentation, faculty, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, liberal arts, library / librarians, lifelong learning, Microsoft, platforms, teaching & learning, trends, universities, by Daniel Christian

A future-facing minister, a young inventor and a shared vision: An AI tutor for every student — from news.microsoft.com by Chris Welsch

The Ministry of Education and Pativada see what has become known as the U.A.E. AI Tutor as a way to provide students with 24/7 assistance as well as help level the playing field for those families who cannot afford a private tutor. At the same time, the AI Tutor would be an aid to teachers, they say. “We see it as a tool that will support our teachers,” says Aljughaiman. “This is a supplement to classroom learning.”

If everything goes according to plan, every student in the United Arab Emirates’ school system will have a personal AI tutor – that fits in their pockets.

It’s a story that involves an element of coincidence, a forward-looking education minister and a tech team led by a chief executive officer who still lives at home with his parents.

In February 2023, the U.A.E.’s education minister, His Excellency Dr. Ahmad Belhoul Al Falasi, announced that the ministry was embracing AI technology and pursuing the idea of an AI tutor to help Emirati students succeed. And he also announced that the speech he presented had been written by ChatGPT. “We should not demonize AI,” he said at the time.

Fostering deep learning in humans and amplifying our intelligence in an AI World — from stefanbauschard.substack.com by Stefan Bauschard
A free 288-page report on advancements in AI and related technology, their effects on education, and our practical support for AI-amplified human deep learning

Six weeks ago, Dr. Sabba Quidwai and I accidentally stumbled upon an idea to compare the deep learning revolution in computer science to the mostly lacking deep learning efforts in education (Mehta & Fine). I started writing, and as these things often go with me, I thought there were many other things that would be useful to think through and for educators to know, and we ended up with this 288-page report.

***

Here’s an abstract from that report:

This report looks at the growing gap between the attention paid to the development of intelligence in machines and humans. While computer scientists have made great strides in developing human intelligence capacities in machines using deep learning technologies, including the abilities of machines to learn on their own, a significant part of the education system has not kept up with developing the intelligence capabilities in people that will enable them to succeed in the 21st century. Instead of fully embracing pedagogical methods that place primary emphasis on promoting collaboration, critical thinking, communication, creativity, and self-learning through experiential, interdisciplinary approaches grounded in human deep learning and combined with current technologies, a substantial portion of the educational system continues to heavily rely on traditional instructional methods and goals. These methods and goals prioritize knowledge acquisition and organization, areas in which machines already perform substantially better than people.

Also from Stefan Bauschard, see:

  • Debating in the World of AI
    Performative assessment, learning to collaborate with humans and machines, and developing special human qualities

13 Nuggets of AI Wisdom for Higher Education Leaders — from jeppestricker.substack.com by Jeppe Klitgaard Stricker
Actionable AI Guidance for Higher Education Leaders

Incentivize faculty AI innovation with AI. 

Invest in people first, then technology. 

On teaching, learning, and assessment. AI has captured the attention of all institutional stakeholders. Capitalize to reimagine pedagogy and evaluation. Rethink lectures, examinations, and assignments to align with workforce needs. Consider incorporating Problem-Based Learning, building portfolios and proof of work, and conducting oral exams. And use AI to provide individualized support and assess real-world skills.

Actively engage students.

Some thoughts from George Siemens re: AI:

Sensemaking, AI, and Learning (SAIL), a regular look at how AI is impacting learning.

Our education system has a uni-dimensional focus: learning things. Of course, we say we care about developing the whole learner, but the metrics that matter (grade, transcripts) that underpin the education system are largely focused on teaching students things that have long been Google-able but are now increasingly doable by AI. Developments in AI matters in ways that calls into question large parts of what happens in our universities. This is not a statement that people don’t need to learn core concepts and skills. My point is that the fulcrum of learning has shifted. Knowing things will continue to matter less and less going forward as AI improves its capabilities. We’ll need to start intentionally developing broader and broader attributes of learners: metacognition, wellness, affect, social engagement, etc. Education will continue to shift toward human skills and away from primary assessment of knowledge gains disconnected from skills and practice and ways of being.

AI, the Next Chapter for College Librarians — from insidehighered.com by Lauren Coffey
Librarians have lived through the disruptions of fax machines, websites and Wikipedia, and now they are bracing to do it again as artificial intelligence tools go mainstream: “Maybe it’s our time to shine.”

A few months after ChatGPT launched last fall, faculty and students at Northwestern University had many questions about the building wave of new artificial intelligence tools. So they turned to a familiar source of help: the library.

“At the time it was seen as a research and citation problem, so that led them to us,” said Michelle Guittar, head of instruction and curriculum support at Northwestern University Libraries.

In response, Guittar, along with librarian Jeanette Moss, created a landing page in April, “Using AI Tools in Your Research.” At the time, the university itself had yet to put together a comprehensive resource page.

From Dr. Nick Jackson’s recent post on LinkedIn: 

Last night the Digitech team of junior and senior teachers from Scotch College Adelaide showcased their 2023 experiments, innovation, successes and failures with technology in education. Accompanied by Student digital leaders, we saw the following:

  •  AI used for languagelearning where avatars can help with accents
  • Motioncapture suits being used in mediastudies
  • AI used in assessment and automatic grading of work
  • AR used in designtechnology
  • VR used for immersive Junior school experiences
  • A teacher’s AI toolkit that has changed teaching practice and workflow
  • AR and the EyeJack app used by students to create dynamic art work
  • VR use in careers education in Senior school
  • How ethics around AI is taught to Junior school students from Year 1
  • Experiments with MyStudyWorks

Almost an Agent: What GPTs can do — from oneusefulthing.org by Ethan Mollick

What would a real AI agent look like? A simple agent that writes academic papers would, after being given a dataset and a field of study, read about how to compose a good paper, analyze the data, conduct a literature review, generate hypotheses, test them, and then write up the results, all without intervention. You put in a request, you get a Word document that contains a draft of an academic paper.

A process kind of like this one:

What I Learned From an Experiment to Apply Generative AI to My Data Course — from edsurge.com by Wendy Castillo

As an educator, I have a duty to remain informed about the latest developments in generative AI, not only to ensure learning is happening, but to stay on top of what tools exist, what benefits and limitations they have, and most importantly, how students might be using them.

However, it’s also important to acknowledge that the quality of work produced by students now requires higher expectations and potential adjustments to grading practices. The baseline is no longer zero, it is AI. And the upper limit of what humans can achieve with these new capabilities remains an unknown frontier.

Artificial Intelligence in Higher Education: Trick or Treat? — from tytonpartners.com by Kristen Fox and Catherine Shaw
.

Two components of AI -- generative AI and predictive AI

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Two items from the Teaching newsletter out at the Chronicle of Higher Education

On 11/10/2023, in 21st century, adjunct faculty, change, changing business models, collaboration, colleges, communities of practice, community colleges, digital audio, digital learning, digital video, distance education, education technology, engagement / engaging students, experimentation, faculty, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), innovation, instructional design, internet, IT in HE, law schools, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, liberal arts, multimedia, new business models, new media literacies, online learning, online media, online tutoring, platforms, teaching & learning, teaching online, technologies for your home, telecommunications, tools, United States, universities, vendors, videoconferencing, by Daniel Christian

What happens to teaching after Covid? — from chronicle.com by Beth McMurtrie

It’s an era many instructors would like to put behind them: black boxes on Zoom screens, muffled discussions behind masks, students struggling to stay engaged. But how much more challenging would teaching during the pandemic have been if colleges did not have experts on staff to help with the transition? On many campuses, teaching-center directors, instructional designers, educational technologists, and others worked alongside professors to explore learning-management systems, master video technology, and rethink what and how they teach.

A new book out this month, Higher Education Beyond Covid: New Teaching Paradigms and Promise, explores this period through the stories of campus teaching and learning centers. Their experiences reflect successes and failures, and what higher education could learn as it plans for the future.

Beth also mentioned/link to:

How to hold difficult discussions online — from chronicle.com by Beckie Supiano

As usual, our readers were full of suggestions. Kathryn Schild, the lead instructional designer in faculty development and instructional support at the University of Alaska at Anchorage, shared a guide she’s compiled on holding asynchronous discussions, which includes a section on difficult topics.

In an email, Schild also pulled out a few ideas she thought were particularly relevant to Le’s question, including:

  • Set the ground rules as a class. One way to do this is to share your draft rules in a collaborative document and ask students to annotate it and add suggestions.
  • Plan to hold fewer difficult discussions than in a face-to-face class, and work on quality over quantity. This could include multiweek discussions, where you spiral through the same issue with fresh perspectives as the class learns new approaches.
  • Start with relationship-building interactions in the first few weeks, such as introductions, low-stakes group assignments, or peer feedback, etc.
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“Colleges are wasting valuable time. They can’t keep AI out of the classroom.” [Gulya] + other items re: AI in our Learning Ecosystems

On 10/30/2023, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, business side of he, change, colleges, community colleges, education technology, emerging technologies, expectations, experimentation, faculty, future, future of higher education, game-changing environment, generational differences, higher education, innovation, instructional design, intelligent systems, law schools, leadership, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, personalized/customized learning, platforms, strategy, student-related, teachers, technology (general), tools, United States, universities, writing, by Daniel Christian

Teaching writing in the age of AI — from the Future of Learning (a Hechinger Report newsletter) by Javeria Salman

ChatGPT can produce a perfectly serviceable writing “product,” she said. But writing isn’t a product per se — it’s a tool for thinking, for organizing ideas, she said.

“ChatGPT and other text-based tools can’t think for us,” she said. “There’s still things to learn when it comes to writing because writing is a form of figuring out what you think.”

When students could contrast their own writing to ChatGPT’s more generic version, Levine said, they were able to “understand what their own voice is and what it does.”

Grammarly’s new generative AI feature learns your style — and applies it to any text — from techcrunch.com by Kyle Wiggers; via Tom Barrett

But what about text? Should — and if so, how should — writers be recognized and remunerated for AI-generated works that mimic their voices?

Those are questions that are likely to be raised by a feature in Grammarly, the cloud-based typing assistant, that’s scheduled to launch by the end of the year for subscribers to Grammarly’s business tier. Called “Personalized voice detection and application,” the feature automatically detects a person’s unique writing style and creates a “voice profile” that can rewrite any text in the person’s style.

Is AI Quietly Weaving the Fabric of a Global Classroom Renaissance? — from medium.com by Robert the Robot
In a world constantly buzzing with innovation, a silent revolution is unfolding within the sanctuaries of learning—our classrooms.

From bustling metropolises to serene hamlets, schools across the globe are greeting a new companion—Artificial Intelligence (AI). This companion promises to redefine the essence of education, making learning a journey tailored to each child’s unique abilities.

The advent of AI in education is akin to a gentle breeze, subtly transforming the academic landscape. Picture a classroom where each child, with their distinct capabilities and pace, embarks on a personalized learning path. AI morphs this vision into reality, crafting a personalized educational landscape that celebrates the unique potential harbored within every learner.

AI Books for Educators — from aiadvisoryboards.wordpress.com by Barbara Anna Zielonka

Books have always held a special place in my heart. As an avid reader and AI enthusiast, I have curated a list of books on artificial intelligence specifically tailored for educators. These books delve into the realms of AI, exploring its applications, ethical considerations, and its impact on education. Share your suggestions and let me know which books you would like to see included on this list.

SAIL: ELAI recordings, AI Safety, Near term AI/learning — by George Siemens

We held our fourth online Empowering Learners for the Age of AI conference last week. We sold out at 1500 people (a Whova and budget limit). The recordings/playlist from the conference can now be accessed here.

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How might you alter your teaching if in 5 years you knew: [Stefan Bauschard]

On 10/24/2023, in adjunct faculty, change, colleges, community colleges, expectations, experimentation, faculty, future, future of higher education, game-changing environment, generational differences, higher education, homeschooling/homeschoolers, innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, law schools, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning hubs & pods & microschooling, learning preferences, learning spaces, liberal arts, online learning, pedagogy, student teaching/teacher education, student-related, teachers, teaching & learning, trends, United States, universities, by Daniel Christian

From DSC:
Interesting fodder for thought, for sure. Thanks Stefan.

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60 Minutes interview with ‘the Godfather of AI’, Geoffrey Hinton [CBS, w/ reflections from Downes & Marcus] + other items re: AI in general

On 10/15/2023, in 21st century, 24x7x365 access, Adobe, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, business, Canada, computer science, emerging technologies, future, game-changing environment, human-computer interaction (HCI), ideas, innovation, intelligent systems, open courseware and systems, platforms, robotics, society, the downsides of technology, tools, trends, UK, United States, vendors, by Daniel Christian

WHAT WAS GARY MARCUS THINKING, IN THAT INTERVIEW WITH GEOFF HINTON? — from linkedin.com by Stephen Downes

Background (emphasis DSC): 60 Minutes did an interview with ‘the Godfather of AI’, Geoffrey Hinton. In response, Gary Marcus wrote a column in which he inserted his own set of responses into the transcript, as though he were a panel participant. Neat idea. So, of course, I’m stealing it, and in what follows, I insert my own comments as I join the 60 Minutes panel with Geoffrey Hinton and Gary Marcus.

Usually I put everyone else’s text in italics, but for this post I’ll put it all in normal font, to keep the format consistent.

Godfather of Artificial Intelligence Geoffrey Hinton on the promise, risks of advanced AI

OpenAI’s Revenue Skyrockets to $1.3 Billion Annualized Rate — from maginative.com by Chris McKay
This means the company is generating over $100 million per month—a 30% increase from just this past summer.

OpenAI, the company behind the viral conversational AI ChatGPT, is experiencing explosive revenue growth. The Information reports that CEO Sam Altman told the staff this week that OpenAI’s revenue is now crossing $1.3 billion on an annualized basis. This means the company is generating over $100 million per month—a 30% increase from just this past summer.

Since the launch of a paid version of ChatGPT in February, OpenAI’s financial growth has been nothing short of meteoric. Additionally, in August, the company announced the launch of ChatGPT Enterprise, a commercial version of its popular conversational AI chatbot aimed at business users.

For comparison, OpenAI’s total revenue for all of 2022 was just $28 million. The launch of ChatGPT has turbocharged OpenAI’s business, positioning it as a bellwether for demand for generative AI.

From 10/13:

New ways to get inspired with generative AI in Search — from blog.google
We’re testing new ways to get more done right from Search, like the ability to generate imagery with AI or creating the first draft of something you need to write.

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Thinking with Colleagues: AI in Education [Grush & Wagner]

On 10/14/2023, in accessibility / UDL, adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, assessment, Bias | Diversity Equity & Inclusion (DE&I), change, colleges, communities of practice, community colleges, copyright/ownership/NFTs, education technology, emerging technologies, engagement / engaging students, experimentation, face-to-face, faculty, future of higher education, game-changing environment, generational differences, Google, higher education, human-computer interaction (HCI), innovation, instructional design, intelligent systems, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, liberal arts, Microsoft, open courseware and systems, platforms, privacy, student-related, teaching & learning, United States, universities, vendors, by Daniel Christian

Thinking with Colleagues: AI in Education — from campustechnology.com by Mary Grush
A Q&A with Ellen Wagner

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.

Mary and Ellen linked to “What Is Top of Mind for Higher Education Leaders about AI?” — from northcoasteduvisory.com. Below are some excerpts from those notes:

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?

  1. 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.
  2. We will need to generate ideas about how to address AI factors such as privacy, equity, bias, copyright, intellectual property, accessibility, and scalability.
  3. 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. 

Along these lines, also see:

What people ask me most. Also, some answers. — from oneusefulthing.org by Ethan Mollick
A FAQ of sorts

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.

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The Public Is Giving Up on Higher Ed [Smith]

On 10/10/2023, in business side of he, change, changing business models, colleges, community colleges, dangers of the status quo, faculty, future of higher education, game-changing environment, higher education, ideas, innovation, learning ecosystem, Learning from the Living [Class] Room, new business models, online learning, parents/guardians, trends, United States, universities, by Daniel Christian

The Public Is Giving Up on Higher Ed — from chronicle.com by Michael D. Smith
Our current system isn’t working for society. Digital alternatives can change that.

Excerpts:

I fear that we in the academy are willfully ignoring this problem. Bring up student-loan debt and you’ll hear that it’s the government’s fault. Bring up online learning and you’ll hear that it is — and always will be — inferior to in-person education. Bring up exclusionary admissions practices and you’ll hear something close to, “Well, the poor can attend community colleges.”

On one hand, our defensiveness is natural. Change is hard, and technological change that risks making traditional parts of our sector obsolete is even harder. “A professor must have an incentive to adopt new technology,” a tenured colleague recently told me regarding online learning. “Innovation adoption will occur one funeral at a time.”

But while our defense of the status quo is understandable, maybe we should ask whether it’s ethical, given what we know about the injustice inherent in our current system. I believe a happier future for all involved — faculty, administrators, and students — is within reach, but requires we stop reflexively protecting our deeply flawed system. How can we do that? We could start by embracing three fundamental principles.

1. Digitization will change higher education.
…
2. We should want to embrace this change.
…
3. We have a way to embrace this change.

I fear that we in the academy are willfully ignoring this problem. Bring up student-loan debt and you’ll hear that it’s the government’s fault. Bring up online learning and you’ll hear that it is — and always will be — inferior to in-person education. Bring up exclusionary admissions practices and you’ll hear something close to, “Well, the poor can attend community colleges.”

 

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“NYC District Goes From Banning ChatGPT to Exploring AI’s Potential” [Klein] + other items re: AI in our learning ecosystems

On 10/09/2023, in adjunct faculty, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, curriculum, education, education technology, emerging technologies, experimentation, faculty, future, game-changing environment, generational differences, Google, higher education, instructional design, intelligent systems, IT in HE, leadership, learning ecosystem, Learning Experience Design, pace of change, personalized/customized learning, platforms, policy, strategy, teachers, teaching & learning, trends, United States, universities, vendors, by Daniel Christian

180 Degree Turn: NYC District Goes From Banning ChatGPT to Exploring AI’s Potential — from edweek.org by Alyson Klein (behind paywall)

New York City Public Schools will launch an Artificial Intelligence Policy Lab to guide the nation’s largest school district’s approach to this rapidly evolving technology.

The Leader’s Blindspot: How to Prepare for the Real Future — from preview.mailerlite.io by the AIEducator
The Commonly Held Belief: AI Will Automate Only Boring, Repetitive Tasks First

The Days of Task-Based Views on AI Are Numbered
The winds of change are sweeping across the educational landscape (emphasis DSC):

  1. Multifaceted AI: AI technologies are not one-trick ponies; they are evolving into complex systems that can handle a variety of tasks.
  2. Rising Expectations: As technology becomes integral to our lives, the expectations for personalised, efficient education are soaring.
  3. Skill Transformation: Future job markets will demand a different skill set, one that is symbiotic with AI capabilities.

Teaching: How to help students better understand generative AI — from chronicle.com by Beth McMurtrie
Beth describes ways professors have used ChatGPT to bolster critical thinking in writing-intensive courses

Kevin McCullen, an associate professor of computer science at the State University of New York at Plattsburgh, teaches a freshman seminar about AI and robotics. As part of the course, students read Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots, by John Markoff. McCullen had the students work in groups to outline and summarize the first three chapters. Then he showed them what ChatGPT had produced in an outline.

“Their version and ChatGPT’s version seemed to be from two different books,” McCullen wrote. “ChatGPT’s version was essentially a ‘laundry list’ of events. Their version was narratives of what they found interesting. The students had focused on what the story was telling them, while ChatGPT focused on who did what in what year.” The chatbot also introduced false information, such as wrong chapter names.

The students, he wrote, found the writing “soulless.”

7 Questions with Dr. Cristi Ford, VP of Academic Affairs at D2L — from campustechnology.com by Rhea Kelly

In the Wild West of generative AI, educators and institutions are working out how best to use the technology for learning. How can institutions define AI guidelines that allow for experimentation while providing students with consistent guidance on appropriate use of AI tools?

To find out, we spoke with Dr. Cristi Ford, vice president of academic affairs at D2L. With more than two decades of educational experience in nonprofit, higher education, and K-12 institutions, Ford works with D2L’s institutional partners to elevate best practices in teaching, learning, and student support. Here, she shares her advice on setting and communicating AI policies that are consistent and future-ready.

AI Platform Built by Teachers, for Teachers, Class Companion Raises $4 Million to Tap Into the Power of Practice — from prweb.com

“If we want to use AI to improve education, we need more teachers at the table,” said Avery Pan, Class Companion co-founder and CEO. “Class Companion is designed by teachers, for teachers, to harness the most sophisticated AI and improve their classroom experience. Developing technologies specifically for teachers is imperative to supporting our next generation of students and education system.”

7 Questions on Generative AI in Learning Design — from campustechnology.com by Rhea Kelly
Open LMS Adoption and Education Specialist Michael Vaughn on the challenges and possibilities of using artificial intelligence to move teaching and learning forward.

The potential for artificial intelligence tools to speed up course design could be an attractive prospect for overworked faculty and spread-thin instructional designers. Generative AI can shine, for example, in tasks such as reworking assessment question sets, writing course outlines and learning objectives, and generating subtitles for audio and video clips. The key, says Michael Vaughn, adoption and education specialist at learning platform Open LMS, is treating AI like an intern who can be guided and molded along the way, and whose work is then vetted by a human expert.

We spoke with Vaughn about how best to utilize generative AI in learning design, ethical issues to consider, and how to formulate an institution-wide policy that can guide AI use today and in the future.

10 Ways Technology Leaders Can Step Up and Into the Generative AI Discussion in Higher Ed — from er.educause.edu by Lance Eaton and Stan Waddell

  1. Offer Short Primers on Generative AI
  2. Explain How to Get Started
  3. Suggest Best Practices for Engaging with Generative AI
  4. Give Recommendations for Different Groups
  5. Recommend Tools
  6. Explain the Closed vs. Open-Source Divide
  7. Avoid Pitfalls
  8. Conduct Workshops and Events
  9. Spot the Fake
  10. Provide Proper Guidance on the Limitations of AI Detectors

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As AI Chatbots Rise, More Educators Look to Oral Exams — With High-Tech Twist [Young]

On 10/06/2023, in 21st century, 24x7x365 access, A/V -- audio/visual, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, Australia, bots, colleges, community colleges, content development, aggregation, repositories, digital audio, digital learning, education, education technology, emerging technologies, experimentation, future, future of higher education, game-changing environment, higher education, ideas, innovation, instructional design, intelligent systems, intelligent tutoring, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, multimedia, Natural Language Processing (NLP), platforms, productivity / tips and tricks, teachers, teaching & learning, teaching online, United States, universities, vendors, vision/possibilities, voice recognition / voice enabled interfaces, by Daniel Christian

As AI Chatbots Rise, More Educators Look to Oral Exams — With High-Tech Twist — from edsurge.com by Jeffrey R. Young

To use Sherpa, an instructor first uploads the reading they’ve assigned, or they can have the student upload a paper they’ve written. Then the tool asks a series of questions about the text (either questions input by the instructor or generated by the AI) to test the student’s grasp of key concepts. The software gives the instructor the choice of whether they want the tool to record audio and video of the conversation, or just audio.

The tool then uses AI to transcribe the audio from each student’s recording and flags areas where the student answer seemed off point. Teachers can review the recording or transcript of the conversation and look at what Sherpa flagged as trouble to evaluate the student’s response.

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