What Students Are Saying About Teachers Using A.I. to Grade — from nytimes.com by ; via Claire Zau
Teenagers and educators weigh in on a recent question from The Ethicist.

Is it unethical for teachers to use artificial intelligence to grade papers if they have forbidden their students from using it for their assignments?

That was the question a teacher asked Kwame Anthony Appiah in a recent edition of The Ethicist. We posed it to students to get their take on the debate, and asked them their thoughts on teachers using A.I. in general.

While our Student Opinion questions are usually reserved for teenagers, we also heard from a few educators about how they are — or aren’t — using A.I. in the classroom. We’ve included some of their answers, as well.


OpenAI wants to pair online courses with chatbots — from techcrunch.com by Kyle Wiggers; via James DeVaney on LinkedIn

If OpenAI has its way, the next online course you take might have a chatbot component.

Speaking at a fireside on Monday hosted by Coeus Collective, Siya Raj Purohit, a member of OpenAI’s go-to-market team for education, said that OpenAI might explore ways to let e-learning instructors create custom “GPTs” that tie into online curriculums.

“What I’m hoping is going to happen is that professors are going to create custom GPTs for the public and let people engage with content in a lifelong manner,” Purohit said. “It’s not part of the current work that we’re doing, but it’s definitely on the roadmap.”


Learning About Google Learn About: What Educators Need To Know — from techlearning.com by Ray Bendici
Google’s experimental Learn About platform is designed to create an AI-guided learning experience

Google Learn About is a new experimental AI-driven platform available that provides digestible and in-depth knowledge about various topics, but showcases it all in an educational context. Described by Google as a “conversational learning companion,” it is essentially a Wikipedia-style chatbot/search engine, and then some.

In addition to having a variety of already-created topics and leading questions (in areas such as history, arts, culture, biology, and physics) the tool allows you to enter prompts using either text or an image. It then provides a general overview/answer, and then suggests additional questions, topics, and more to explore in regard to the initial subject.

The idea is for student use is that the AI can help guide a deeper learning process rather than just provide static answers.


What OpenAI’s PD for Teachers Does—and Doesn’t—Do — from edweek.org by Olina Banerji
What’s the first thing that teachers dipping their toes into generative artificial intelligence should do?

They should start with the basics, according to OpenAI, the creator of ChatGPT and one of the world’s most prominent artificial intelligence research companies. Last month, the company launched an hour-long, self-paced online course for K-12 teachers about the definition, use, and harms of generative AI in the classroom. It was launched in collaboration with Common Sense Media, a national nonprofit that rates and reviews a wide range of digital content for its age appropriateness.

…the above article links to:

ChatGPT Foundations for K–12 Educators — from commonsense.org

This course introduces you to the basics of artificial intelligence, generative AI, ChatGPT, and how to use ChatGPT safely and effectively. From decoding the jargon to responsible use, this course will help you level up your understanding of AI and ChatGPT so that you can use tools like this safely and with a clear purpose.

Learning outcomes:

  • Understand what ChatGPT is and how it works.
  • Demonstrate ways to use ChatGPT to support your teaching practices.
  • Implement best practices for applying responsible AI principles in a school setting.

Takeaways From Google’s Learning in the AI Era Event — from edtechinsiders.substack.com by Sarah Morin, Alex Sarlin, and Ben Kornell
Highlights from Our Day at Google + Behind-the-Scenes Interviews Coming Soon!

  1. NotebookLM: The Start of an AI Operating System
  2. Google is Serious About AI and Learning
  3. Google’s LearnLM Now Available in AI Studio
  4. Collaboration is King
  5. If You Give a Teacher a Ferrari

Rapid Responses to AI — from the-job.beehiiv.com by Paul Fain
Top experts call for better data and more short-term training as tech transforms jobs.

AI could displace middle-skill workers and widen the wealth gap, says landmark study, which calls for better data and more investment in continuing education to help workers make career pivots.

Ensuring That AI Helps Workers
Artificial intelligence has emerged as a general purpose technology with sweeping implications for the workforce and education. While it’s impossible to precisely predict the scope and timing of looming changes to the labor market, the U.S. should build its capacity to rapidly detect and respond to AI developments.
That’s the big-ticket framing of a broad new report from the National Academies of Sciences, Engineering, and Medicine. Congress requested the study, tapping an all-star committee of experts to assess the current and future impact of AI on the workforce.

“In contemplating what the future holds, one must approach predictions with humility,” the study says…

“AI could accelerate occupational polarization,” the committee said, “by automating more nonroutine tasks and increasing the demand for elite expertise while displacing middle-skill workers.”

The Kicker: “The education and workforce ecosystem has a responsibility to be intentional with how we value humans in an AI-powered world and design jobs and systems around that,” says Hsieh.


Why We Undervalue Ideas and Overvalue Writing — from aiczar.blogspot.com by Alexander “Sasha” Sidorkin

A student submits a paper that fails to impress stylistically yet approaches a worn topic from an angle no one has tried before. The grade lands at B minus, and the student learns to be less original next time. This pattern reveals a deep bias in higher education: ideas lose to writing every time.

This bias carries serious equity implications. Students from disadvantaged backgrounds, including first-generation college students, English language learners, and those from under-resourced schools, often arrive with rich intellectual perspectives but struggle with academic writing conventions. Their ideas – shaped by unique life experiences and cultural viewpoints – get buried under red ink marking grammatical errors and awkward transitions. We systematically undervalue their intellectual contributions simply because they do not arrive in standard academic packaging.


Google Scholar’s New AI Outline Tool Explained By Its Founder — from techlearning.com by Erik Ofgang
Google Scholar PDF reader uses Gemini AI to read research papers. The AI model creates direct links to the paper’s citations and a digital outline that summarizes the different sections of the paper.

Google Scholar has entered the AI revolution. Google Scholar PDF reader now utilizes generative AI powered by Google’s Gemini AI tool to create interactive outlines of research papers and provide direct links to sources within the paper. This is designed to make reading the relevant parts of the research paper more efficient, says Anurag Acharya, who co-founded Google Scholar on November 18, 2004, twenty years ago last month.


The Four Most Powerful AI Use Cases in Instructional Design Right Now — from drphilippahardman.substack.com by Dr. Philippa Hardman
Insights from ~300 instructional designers who have taken my AI & Learning Design bootcamp this year

  1. AI-Powered Analysis: Creating Detailed Learner Personas…
  2. AI-Powered Design: Optimising Instructional Strategies…
  3. AI-Powered Development & Implementation: Quality Assurance…
  4. AI-Powered Evaluation: Predictive Impact Assessment…

How Are New AI Tools Changing ‘Learning Analytics’? — from edsurge.com by Jeffrey R. Young
For a field that has been working to learn from the data trails students leave in online systems, generative AI brings new promises — and new challenges.

In other words, with just a few simple instructions to ChatGPT, the chatbot can classify vast amounts of student work and turn it into numbers that educators can quickly analyze.

Findings from learning analytics research is also being used to help train new generative AI-powered tutoring systems.

Another big application is in assessment, says Pardos, the Berkeley professor. Specifically, new AI tools can be used to improve how educators measure and grade a student’s progress through course materials. The hope is that new AI tools will allow for replacing many multiple-choice exercises in online textbooks with fill-in-the-blank or essay questions.

 

(Excerpt from the 12/4/24 edition)

Robot “Jailbreaks”
In the year or so since large language models hit the big time, researchers have demonstrated numerous ways of tricking them into producing problematic outputs including hateful jokes, malicious code, phishing emails, and the personal information of users. It turns out that misbehavior can take place in the physical world, too: LLM-powered robots can easily be hacked so that they behave in potentially dangerous ways.

Researchers from the University of Pennsylvania were able to persuade a simulated self-driving car to ignore stop signs and even drive off a bridge, get a wheeled robot to find the best place to detonate a bomb, and force a four-legged robot to spy on people and enter restricted areas.

“We view our attack not just as an attack on robots,” says George Pappas, head of a research lab at the University of Pennsylvania who helped unleash the rebellious robots. “Any time you connect LLMs and foundation models to the physical world, you actually can convert harmful text into harmful actions.”

The robot “jailbreaks” highlight a broader risk that is likely to grow as AI models become increasingly used as a way for humans to interact with physical systems, or to enable AI agents autonomously on computers, say the researchers involved.


Virtual lab powered by ‘AI scientists’ super-charges biomedical research — from nature.com by Helena Kudiabor
Could human-AI collaborations be the future of interdisciplinary studies?

In an effort to automate scientific discovery using artificial intelligence (AI), researchers have created a virtual laboratory that combines several ‘AI scientists’ — large language models with defined scientific roles — that can collaborate to achieve goals set by human researchers.

The system, described in a preprint posted on bioRxiv last month1, was able to design antibody fragments called nanobodies that can bind to the virus that causes COVID-19, proposing nearly 100 of these structures in a fraction of the time it would take an all-human research group.


Can AI agents accelerate AI implementation for CIOs? — from intelligentcio.com by Arun Shankar

By embracing an agent-first approach, every CIO can redefine their business operations. AI agents are now the number one choice for CIOs as they come pre-built and can generate responses that are consistent with a company’s brand using trusted business data, explains Thierry Nicault at Salesforce Middle.


AI Turns Photos Into 3D Real World — from theaivalley.com by Barsee

Here’s what you need to know:

  • The system generates full 3D environments that expand beyond what’s visible in the original image, allowing users to explore new perspectives.
  • Users can freely navigate and view the generated space with standard keyboard and mouse controls, similar to browsing a website.
  • It includes real-time camera effects like depth-of-field and dolly zoom, as well as interactive lighting and animation sliders to tweak scenes.
  • The system works with both photos and AI-generated images, enabling creators to integrate it with text-to-image tools or even famous works of art.

Why it matters:
This technology opens up exciting possibilities for industries like gaming, film, and virtual experiences. Soon, creating fully immersive worlds could be as simple as generating a static image.

Also related, see:

From World Labs

Today we’re sharing our first step towards spatial intelligence: an AI system that generates 3D worlds from a single image. This lets you step into any image and explore it in 3D.

Most GenAI tools make 2D content like images or videos. Generating in 3D instead improves control and consistency. This will change how we make movies, games, simulators, and other digital manifestations of our physical world.

In this post you’ll explore our generated worlds, rendered live in your browser. You’ll also experience different camera effects, 3D effects, and dive into classic paintings. Finally, you’ll see how creators are already building with our models.


Addendum on 12/5/24:

 

AI Tutors: Hype or Hope for Education? — from educationnext.org by John Bailey and John Warner
In a new book, Sal Khan touts the potential of artificial intelligence to address lagging student achievement. Our authors weigh in.

In Salman Khan’s new book, Brave New Words: How AI Will Revolutionize Education (and Why That’s a Good Thing) (Viking, 2024), the Khan Academy founder predicts that AI will transform education by providing every student with a virtual personalized tutor at an affordable cost. Is Khan right? Is radically improved achievement for all students within reach at last? If so, what sorts of changes should we expect to see, and when? If not, what will hold back the AI revolution that Khan foresees? John Bailey, a visiting fellow at the American Enterprise Institute, endorses Khan’s vision and explains the profound impact that AI technology is already making in education. John Warner, a columnist for the Chicago Tribune and former editor for McSweeney’s Internet Tendency, makes the case that all the hype about AI tutoring is, as Macbeth quips, full of sound and fury, signifying nothing.

 

(An excerpt from Brainyacts #253 12/3/24)

A New Era for Law Firm Learning and Development — from brainyacts.beehiiv.com by Josh Kubicki

By becoming early adopters, law firms can address two critical challenges in professional development:

1. Empowering Educators and Mentors
Generative AI equips legal educators, practice group leaders, and mentors with tools to amplify their impact. It assists with:

  • Content generation: …
  • Research facilitation: …
  • Skill-building frameworks: …


2. Cracking the Personalized Learning Code
Every lawyer’s learning needs are unique. Generative AI delivers hyper-personalized educational experiences that adapt to an individual’s role, practice area, and career stage. This addresses the “Two Sigma Problem” (the dramatic performance gains of one-on-one tutoring) by making tailored learning scalable and actionable. Imagine:

  • AI-driven tutors: …
  • Instant feedback loops: …
  • Adaptive learning models: …

Case Study: Building AI Tutors in Legal Education

Moving Beyond CLEs: A New Vision for Professional Development…


 
 

Below is an excerpt from 2024: The State of Generative AI in the Enterprise — from Menlo Ventures

  • Legal: Historically resistant to tech, the legal industry ($350 million in enterprise AI spend) is now embracing generative AI to manage massive amounts of unstructured data and automate complex, pattern-based workflows. The field broadly divides into litigation and transactional law, with numerous subspecialties. Rooted in litigation, Everlaw* focuses on legal holds, e-discovery, and trial preparation, while Harvey and Spellbook are advancing AI in transactional law with solutions for contract review, legal research, and M&A. Specific practice areas are also targeted AI innovations: EvenUp focuses on injury law, Garden on patents and intellectual property, Manifest on immigration and employment law, while Eve* is re-inventing plaintiff casework from client intake to resolution.

Excerpt from Brainyacts #250 (from 11/22/24) — from the Leveraging Generative AI in Client Interviews section

Here’s what the article from Forbes said:

  • CodeSignal, an AI tech company, has launched Conversation Practice, an AI-driven platform to help learners practice critical workplace communication and soft skills.
  • Conversation Practice uses multiple AI models and a natural spoken interface to simulate real-world scenarios and provide feedback.
  • The goal is to address the challenge of developing conversational skills through iterative practice, without the awkwardness of peer role-play.

What I learned about this software changed my perception about how I can prepare in the future for client meetings. Here’s what I’ve taken away from the potential use of this software in a legal practice setting:


Why Technology-Driven Law Firms Are Poised For Long-Term Success — from forbes.com by Daniel Farrar

I see the shift to cloud-based digital systems, especially for small and midsized law firms, as evening the playing field by providing access to robust tools that can aid legal services. Here are some examples of how legal professionals are leveraging tech every day:

    • Cloud-based case management solutions. These help enhance productivity through collaboration tools and automated workflows while keeping data secure.
    • E-discovery tools. These tools manage vast amounts of data and help speed up litigation processes.
    • Artificial intelligence. AI has helped automate tasks for legal professionals including for case management, research, contract review and predictive analytics.
 

2024: The State of Generative AI in the Enterprise — from menlovc.com (Menlo Ventures)
The enterprise AI landscape is being rewritten in real time. As pilots give way to production, we surveyed 600 U.S. enterprise IT decision-makers to reveal the emerging winners and losers.

This spike in spending reflects a wave of organizational optimism; 72% of decision-makers anticipate broader adoption of generative AI tools in the near future. This confidence isn’t just speculative—generative AI tools are already deeply embedded in the daily work of professionals, from programmers to healthcare providers.

Despite this positive outlook and increasing investment, many decision-makers are still figuring out what will and won’t work for their businesses. More than a third of our survey respondents do not have a clear vision for how generative AI will be implemented across their organizations. This doesn’t mean they’re investing without direction; it simply underscores that we’re still in the early stages of a large-scale transformation. Enterprise leaders are just beginning to grasp the profound impact generative AI will have on their organizations.


Business spending on AI surged 500% this year to $13.8 billion, says Menlo Ventures — from cnbc.com by Hayden Field

Key Points

  • Business spending on generative AI surged 500% this year, hitting $13.8 billion — up from just $2.3 billion in 2023, according to data from Menlo Ventures released Wednesday.
  • OpenAI ceded market share in enterprise AI, declining from 50% to 34%, per the report.
  • Amazon-backed Anthropic doubled its market share from 12% to 24%.

Microsoft quietly assembles the largest AI agent ecosystem—and no one else is close — from venturebeat.com by Matt Marshall

Microsoft has quietly built the largest enterprise AI agent ecosystem, with over 100,000 organizations creating or editing AI agents through its Copilot Studio since launch – a milestone that positions the company ahead in one of enterprise tech’s most closely watched and exciting  segments.

The rapid adoption comes as Microsoft significantly expands its agent capabilities. At its Ignite conference [that started on 11/19/24], the company announced it will allow enterprises to use any of the 1,800 large language models (LLMs) in the Azure catalog within these agents – a significant move beyond its exclusive reliance on OpenAI’s models. The company also unveiled autonomous agents that can work independently, detecting events and orchestrating complex workflows with minimal human oversight.


Now Hear This: World’s Most Flexible Sound Machine Debuts — from
Using text and audio as inputs, a new generative AI model from NVIDIA can create any combination of music, voices and sounds.

Along these lines, also see:


AI Agents Versus Human Agency: 4 Ways To Navigate Our AI-Driven World — from forbes.com by Cornelia C. Walther

To understand the implications of AI agents, it’s useful to clarify the distinctions between AI, generative AI, and AI agents and explore the opportunities and risks they present to our autonomy, relationships, and decision-making.

AI Agents: These are specialized applications of AI designed to perform tasks or simulate interactions. AI agents can be categorized into:

    • Tool Agents…
    • Simulation Agents..

While generative AI creates outputs from prompts, AI agents use AI to act with intention, whether to assist (tool agents) or emulate (simulation agents). The latter’s ability to mirror human thought and action offers fascinating possibilities — and raises significant risks.

 

2024-11-22: The Race to the TopDario Amodei on AGI, Risks, and the Future of Anthropic — from emergentbehavior.co by Prakash (Ate-a-Pi)

Risks on the Horizon: ASL Levels
The two key risks Dario is concerned about are:

a) cyber, bio, radiological, nuclear (CBRN)
b) model autonomy

These risks are captured in Anthropic’s framework for understanding AI Safety Levels (ASL):

1. ASL-1: Narrow-task AI like Deep Blue (no autonomy, minimal risk).
2. ASL-2: Current systems like ChatGPT/Claude, which lack autonomy and don’t pose significant risks beyond information already accessible via search engines.
3. ASL-3: Agents arriving soon (potentially next year) that can meaningfully assist non-state actors in dangerous activities like cyber or CBRN (chemical, biological, radiological, nuclear) attacks. Security and filtering are critical at this stage to prevent misuse.
4. ASL-4: AI smart enough to evade detection, deceive testers, and assist state actors with dangerous projects. AI will be strong enough that you would want to use the model to do anything dangerous. Mechanistic interpretability becomes crucial for verifying AI behavior.
5. ASL-5: AGI surpassing human intelligence in all domains, posing unprecedented challenges.

Anthropic’s if/then framework ensures proactive responses: if a model demonstrates danger, the team clamps down hard, enforcing strict controls.



Should You Still Learn to Code in an A.I. World? — from nytimes.com by
Coding boot camps once looked like the golden ticket to an economically secure future. But as that promise fades, what should you do? Keep learning, until further notice.

Compared with five years ago, the number of active job postings for software developers has dropped 56 percent, according to data compiled by CompTIA. For inexperienced developers, the plunge is an even worse 67 percent.
“I would say this is the worst environment for entry-level jobs in tech, period, that I’ve seen in 25 years,” said Venky Ganesan, a partner at the venture capital firm Menlo Ventures.

For years, the career advice from everyone who mattered — the Apple chief executive Tim Cook, your mother — was “learn to code.” It felt like an immutable equation: Coding skills + hard work = job.

Now the math doesn’t look so simple.

Also see:

AI builds apps in 2 mins flat — where the Neuron mentions this excerpt about Lovable:

There’s a new coding startup in town, and it just MIGHT have everybody else shaking in their boots (we’ll qualify that in a sec, don’t worry).

It’s called Lovable, the “world’s first AI fullstack engineer.”

Lovable does all of that by itself. Tell it what you want to build in plain English, and it creates everything you need. Want users to be able to log in? One click. Need to store data? One click. Want to accept payments? You get the idea.

Early users are backing up these claims. One person even launched a startup that made Product Hunt’s top 10 using just Lovable.

As for us, we made a Wordle clone in 2 minutes with one prompt. Only edit needed? More words in the dictionary. It’s like, really easy y’all.


When to chat with AI (and when to let it work) — from aiwithallie.beehiiv.com by Allie K. Miller

Re: some ideas on how to use Notebook LM:

  • Turn your company’s annual report into an engaging podcast
  • Create an interactive FAQ for your product manual
  • Generate a timeline of your industry’s history from multiple sources
  • Produce a study guide for your online course content
  • Develop a Q&A system for your company’s knowledge base
  • Synthesize research papers into digestible summaries
  • Create an executive content briefing from multiple competitor blog posts
  • Generate a podcast discussing the key points of a long-form research paper

Introducing conversation practice: AI-powered simulations to build soft skills — from codesignal.com by Albert Sahakyan

From DSC:
I have to admit I’m a bit suspicious here, as the “conversation practice” product seems a bit too scripted at times, but I post it because the idea of using AI to practice soft skills development makes a great deal of sense:


 

7 Legal Tech Trends To Watch In 2025 — from lexology.com by Sacha Kirk
Australia, United Kingdom November 25 2024

In-house legal teams are changing from a traditional support function to becoming proactive business enablers. New tools are helping legal departments enhance efficiency, improve compliance, and to deliver greater strategic value.

Here’s a look at seven emerging trends that will shape legal tech in 2025 and insights on how in-house teams can capitalise on these innovations.

1. AI Solutions…
2. Regulatory Intelligence Platforms…

7. Self-Service Legal Tools and Knowledge Management
As the demand on in-house legal teams continues to grow, self-service tools are becoming indispensable for managing routine legal tasks. In 2025, these tools are expected to evolve further, enabling employees across the organisation to handle straightforward legal processes independently. Whether it’s accessing pre-approved templates, completing standard agreements, or finding answers to common legal queries, self-service platforms reduce the dependency on legal teams for everyday tasks.

Advanced self-service tools go beyond templates, incorporating intuitive workflows, approval pathways, and built-in guidance to ensure compliance with legal and organisational policies. By empowering business users to manage low-risk matters on their own, these tools free up legal teams to focus on complex and high-value work.


 

 

How to use NotebookLM for personalized knowledge synthesis — from ai-supremacy.com by Michael Spencer and Alex McFarland
Two powerful workflows that unlock everything else. Intro: Golden Age of AI Tools and AI agent frameworks begins in 2025.

What is Google Learn about?
Google’s new AI tool, Learn About, is designed as a conversational learning companion that adapts to individual learning needs and curiosity. It allows users to explore various topics by entering questions, uploading images or documents, or selecting from curated topics. The tool aims to provide personalized responses tailored to the user’s knowledge level, making it user-friendly and engaging for learners of all ages.

Is Generative AI leading to a new take on Educational technology? It certainly appears promising heading into 2025.

The Learn About tool utilizes the LearnLM AI model, which is grounded in educational research and focuses on how people learn. Google insists that unlike traditional chatbots, it emphasizes interactive and visual elements in its responses, enhancing the educational experience. For instance, when asked about complex topics like the size of the universe, Learn About not only provides factual information but also includes related content, vocabulary building tools, and contextual explanations to deepen understanding.

 

Introducing Copilot Actions, new agents, and tools to empower IT teams — from microsoft.com by Jared Spataro

[On November 19th] at Microsoft Ignite 2024, we’re accelerating our ambition to empower every employee with Copilot as a personal assistant and to transform every business process with agents built in Microsoft Copilot Studio.

Announcements include:

  • Copilot Actions in Microsoft 365 Copilot to help you automate everyday repetitive tasks.
  • New agents in Microsoft 365 to unlock SharePoint knowledge, provide real-time language interpretation in Microsoft Teams meetings, and automate employee self-service.
  • The Copilot Control System to help IT professionals confidently manage Copilot and agents securely.

These announcements build on our wave 2 momentum, including the new autonomous agent capabilities that we announced in October 2024.

Per the Rundown AI:
By integrating AI agents directly into Microsoft’s billion-plus users’ daily workflows, this release could normalize agentic AI faster than any previous rollout. Just as users now reach for specific apps or plugins to solve particular problems, specialized agents could soon become the natural first stop for getting work done.

Along these lines, also see:

AI agents — what they are, and how they’ll change the way we work — from news.microsoft.com by Susanna Ray

An agent takes the power of generative AI a step further, because instead of just assisting you, agents can work alongside you or even on your behalf. Agents can do a range of things, from responding to questions to more complicated or multistep assignments. What sets them apart from a personal assistant is that they can be tailored to have a particular expertise.

For example, you could create an agent to know everything about your company’s product catalog so it can draft detailed responses to customer questions or automatically compile product details for an upcoming presentation.

Microsoft pitches AI ‘agents’ that can perform tasks on their own at Ignite 2024 — from techxplore.com
Microsoft CEO Satya Nadella told customers at a conference in Chicago on Tuesday that the company is teaching a new set of artificial intelligence tools how to “act on our behalf across our work and life.”


From DSC:
I am not trying to push all things AI. There are serious concerns that I and others have with agents and other AI-based technologies especially:

  • When competitive juices get going and such forces throw people and companies into a sort of an AI arms race, and
  • When many people haven’t yet obtained the wisdom of reflecting on things like “just because we CAN build this doesn’t mean we SHOULD build it”, or
  • When governments seek to be the leader of AI due to military applications (and yes, I’m looking at the U.S. Federal Government especially here)
  • Etc, etc. 

But there are also areas where I’m more hopeful and positive about AI-related technologies — such as providing personalized learning and productivity tools (like those from Microsoft above).

 

VR training aims to help doctors avoid bias — from inavateonthenet.net

A new virtual reality training programme aims to tackle biases in healthcare settings, aimed at improving recognition, understanding, and addressing implicit bias towards black mothers.

Participants in the program at the University of Illinois Urbana-Champaign underwent a series of three modules, with the first module focusing on implicit bias and how it can negatively affect a patient at a doctor’s appointment.

 

What DICE does in this posting will be available 24x7x365 in the future [Christian]

From DSC:
First of all, when you look at the following posting:


What Top Tech Skills Should You Learn for 2025? — from dice.com by Nick Kolakowski


…you will see that they outline which skills you should consider mastering in 2025 if you want to stay on top of the latest career opportunities. They then list more information about the skills, how you apply the skills, and WHERE to get those skills.

I assert that in the future, people will be able to see this information on a 24x7x365 basis.

  • Which jobs are in demand?
  • What skills do I need to do those jobs?
  • WHERE do I get/develop those skills?


And that last part (about the WHERE do I develop those skills) will pull from many different institutions, people, companies, etc.

BUT PEOPLE are the key! Oftentimes, we need to — and prefer to — learn with others!


 

“The Value of Doing Things: What AI Agents Mean for Teachers” — from nickpotkalitsky.substack.com by guest author Jason Gulya, Professor of English and Applied Media at Berkeley College in New York City

AI Agents make me nervous. Really nervous.

I wish they didn’t.

I wish I could write that the last two years have made me more confident, more self-assured that AI is here to augment workers rather than replace them.

But I can’t.

I wish I could write that I know where schools and colleges will end up. I wish I could say that AI Agents will help us get where we need to be.

But I can’t.

At this point, today, I’m at a loss. I’m not sure where the rise of AI agents will take us, in terms of how we work and learn. I’m in the question-asking part of my journey. I have few answers.

So, let’s talk about where (I think) AI Agents will take education. And who knows? Maybe as I write I’ll come up with something more concrete.

It’s worth a shot, right?

From DSC: 
I completely agree with Jason’s following assertion:

A good portion of AI advancement will come down to employee replacement. And AI Agents push companies towards that. 

THAT’s where/what the ROI will be for corporations. They will make their investments up in the headcount area, and likely in other areas as well (product design, marketing campaigns, engineering-related items, and more). But how much time it takes to get there is a big question mark.

One last quote here…it’s too good not to include:

Behind these questions lies a more abstract, more philosophical one: what is the relationship between thinking and doing in a world of AI Agents and other kinds of automation?


How Good are Claude, ChatGPT & Gemini at Instructional Design? — from drphilippahardman.substack.com by Dr Philippa Hardman
A test of AI’s Instruction Design skills in theory & in practice

By examining models across three AI families—Claude, ChatGPT, and Gemini—I’ve started to identify each model’s strengths, limitations, and typical pitfalls.

Spoiler: my findings underscore that until we have specialised, fine-tuned AI copilots for instructional design, we should be cautious about relying on general-purpose models and ensure expert oversight in all ID tasks.


From DSC — I’m going to (have Nick) say this again:
I simply asked my students to use AI to brainstorm their own learning objectives. No restrictions. No predetermined pathways. Just pure exploration. The results? Astonishing.

Students began mapping out research directions I’d never considered. They created dialogue spaces with AI that looked more like intellectual partnerships than simple query-response patterns. 


The Digital Literacy Quest: Become an AI Hero — from gamma.app

From DSC:
I have not gone through all of these online-based materials, but I like what they are trying to get at:

  • Confidence with AI
    Students gain practical skills and confidence in using AI tools effectively.
  • Ethical Navigation
    Learn to navigate the ethical landscape of AI with integrity and responsibility. Make informed decisions about AI usage.
  • Mastering Essential Skills
    Develop critical thinking and problem-solving skills in the context of AI.

 


Expanding access to the Gemini app for teen students in education — from workspaceupdates.googleblog.com

Google Workspace for Education admins can now turn on the Gemini app with added data protection as an additional service for their teen users (ages 13+ or the applicable age in your country) in the following languages and countries. With added data protection, chats are not reviewed by human reviewers or otherwise used to improve AI models. The Gemini app will be a core service in the coming weeks for Education Standard and Plus users, including teens,


5 Essential Questions Educators Have About AI  — from edsurge.com by Annie Ning

Recently, I spoke with several teachers regarding their primary questions and reflections on using AI in teaching and learning. Their thought-provoking responses challenge us to consider not only what AI can do but what it means for meaningful and equitable learning environments. Keeping in mind these reflections, we can better understand how we move forward toward meaningful AI integration in education.


FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI — from epoch.ai
FrontierMath presents hundreds of unpublished, expert-level mathematics problems that specialists spend days solving. It offers an ongoing measure of AI complex mathematical reasoning progress.

We’re introducing FrontierMath, a benchmark of hundreds of original, expert-crafted mathematics problems designed to evaluate advanced reasoning capabilities in AI systems. These problems span major branches of modern mathematics—from computational number theory to abstract algebraic geometry—and typically require hours or days for expert mathematicians to solve.


Rising demand for AI courses in UK universities shows 453% growth as students adapt to an AI-driven job market — from edtechinnovationhub.com

The demand for artificial intelligence courses in UK universities has surged dramatically over the past five years, with enrollments increasing by 453%, according to a recent study by Currys, a UK tech retailer.

The study, which analyzed UK university admissions data and surveyed current students and recent graduates, reveals how the growing influence of AI is shaping students’ educational choices and career paths.

This growth reflects the broader trend of AI integration across industries, creating new opportunities while transforming traditional roles. With AI’s influence on career prospects rising, students and graduates are increasingly drawn to AI-related courses to stay competitive in a rapidly changing job market.

 

How Legal Education Must Evolve In The Age Of AI: Insights From An In-House Legal Innovator — from by abovethelaw.com Olga Mack
Traditional legal education has remained largely unchanged for decades, focusing heavily on theoretical knowledge and case law analysis.

As we stand on the brink of a new era defined by artificial intelligence (AI) and data-driven decision-making, the question arises: How should legal education adapt to prepare the next generation of lawyers for the challenges ahead?

Here are three unconventional, actionable insights from our conversation that highlight the need for a radical rethinking of legal education.

  1. Integrate AI Education Into Every Aspect Of Legal Training…
  2. Adopt A ‘Technology-Agnostic’ Approach To AI Training…
  3. Redefine Success In Legal Education To Include Technological Proficiency…
 
© 2024 | Daniel Christian