vendors

VLOG: Learning in Medical School [The Learning Scientists]

On 12/07/2024, in Emotion, experimentation, faculty/staff, health, higher education, instructional design, learning, learning ecosystem, Learning Experience Design, memory, productivity / tips and tricks, student-related, teaching & learning, United States, universities, vendors, by Daniel Christian

VLOG: Learning in Medical School — from learningscientists.org by The Learning Scientists

NOTE:

This vlog is for anyone in medical school, interested in medical school, or just curious about what learning is like in medical school!

In this vlog Althea and Cindy talk about their work with medical student learners. They discuss common learning challenges in medical school, efficient learning strategies, learning in the context of attentional disorders and anxiety, and what it means to prepare future healers.

“20 Years of Law School Insights” [Laus] + other items related to law schools

On 12/07/2024, in law schools, student-related, United States, universities, vendors, by Daniel Christian

20 Years of Law School Insights: Diversity, Debt, and Student Satisfaction Trends — from jdjournal.com by Maria Lenin Laus (may ask for email address and first name to access this)

Over the past two decades, law school students have consistently rated their educational experiences highly. According to the Law School Survey of Student Engagement (LSSSE), nearly 80% of law students have described their experience as “good” or “excellent” since the survey’s inception in 2004. However, significant disparities in satisfaction persist, particularly among students of color.

The LSSSE, conducted by Indiana University’s Center for Postsecondary Research, recently released its 20th-anniversary report. The report reflects on changes in student diversity, debt, career aspirations, and overall satisfaction and paints a nuanced picture of the evolving law school experience and the remaining challenges.

Also see:

Information for law students from JD Journal

Law student satisfaction rates high for last 20 years, lower for students of color, study shows — from reuters.com by Karen Sloan

Nov 26 (Reuters) – Aspiring lawyers have consistently rated their experience at law schools well over the past two decades, with about 80% rating their experience as either “good” or “excellent” on the annual Law School Survey of Student Engagement, although satisfaction rates among students of color were lower than among whites over the past 20 years.

The survey, opens new tab, part of Indiana University’s Center for Postsecondary Research, marked its 20th edition this month with a look back at how student diversity, debt loads, career plans and satisfaction levels have changed – or not – during that time.

Reflections on “US College Closures Are Expected to Soar, Fed Research Says” [Bloomberg.com]

On 12/07/2024, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, assessment, business side of he, change, changing business models, colleges, community colleges, cost of getting a degree, dangers of the status quo, Daniel S. Christian, data related items, economics, faculty/staff, game-changing environment, higher education, ideas, law schools, learning ecosystem, Learning from the Living [Class] Room, legislatures / government / legal, liberal arts, new business models, parents/guardians, policy, reinvent, society, staying relevant, student-related, surviving, United States, universities, vendors, by Daniel Christian

US College Closures Are Expected to Soar, Fed Research Says — from bloomberg.com

Fed research created predictive model of college stress
Worst-case scenario forecasts 80 additional closures

The number of colleges that close each year is poised to significantly increase as schools contend with a slowdown in prospective students.

That’s the finding of a new working paper published by the Federal Reserve Bank of Philadelphia, where researchers created predictive models of schools’ financial distress using metrics like enrollment and staffing patterns, sources of revenue and liquidity data. They overlayed those models with simulations to estimate the likely increase of future closures.

Excerpt from the working paper:

We document a high degree of missing data among colleges that eventually close and show that this is a key impediment to identifying at risk institutions. We then show that modern machine learning techniques, combined with richer data, are far more effective at predicting college closures than linear probability models, and considerably more effective than existing accountability metrics. Our preferred model, which combines an off-the-shelf machine learning algorithm with the richest set of explanatory variables, can significantly improve predictive accuracy even for institutions with complete data, but is particularly helpful for predicting instances of financial distress for institutions with spotty data.

From DSC:
Questions that come to my mind here include:

Shouldn’t the public — especially those relevant parents and students — be made more aware of these types of papers and reports?
.
How would any of us like finishing up 1-3 years of school and then being told that our colleges or universities were closing, effective immediately? (This has happened many times already.) and with the demographic cliff starting to hit higher education, this will happen even more now.
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Adding insult to injury…when we transfer to different institutions, we’re told that many of our prior credits don’t transfer — thus adding a significant amount to the overall cost of obtaining our degrees.
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Would we not be absolutely furious to discover such communications from our prior — and new — colleges and universities?
.
Will all of these types of closures move more people to this vision here?

Relevant excerpts from Ray Schroeder’s recent articles out at insidehighered.com:

Winds of Change in Higher Ed to Become a Hurricane in 2025

A number of factors are converging to create a huge storm. Generative AI advances, massive federal policy shifts, broad societal and economic changes, and the demographic cliff combine to create uncertainty today and change tomorrow.

Higher Education in 2025: AGI Agents to Displace People

The anticipated enrollment cliff, reductions in federal and state funding, increased inflation, and dwindling public support for tuition increases will combine to put even greater pressure on university budgets.

On the positive side of things, the completion rates have been getting better:

National college completion rate ticks up to 61.1% — from highereddive.com by Natalie Schwartz
Those who started at two-year public colleges helped drive the overall increase in students completing a credential.

Dive Brief:

Completion rates ticked up to 61.1% for students who entered college in fall 2018, a 0.5 percentage-point increase compared to the previous cohort, according to data released Wednesday by the National Student Clearinghouse Research Center.
The increase marks the highest six-year completion rate since 2007 when the clearinghouse began tracking the data. The growth was driven by fewer students stopping out of college, as well as completion gains among students who started at public two-year colleges.
“Higher completion rates are welcome news for colleges and universities still struggling to regain enrollment levels from before the pandemic,” Doug Shapiro, the research center’s executive director, said in a statement dated Wednesday.

Addendum:

Attention Please: Professors Struggle With Student Disengagement — from edsurge.com

The stakes are huge, because the concern is that maybe the social contract between students and professors is kind of breaking down. Do students believe that all this college lecturing is worth hearing? Or, will this moment force a change in the way college teaching is done?

DC: From a box of Post cereal, a deep reflection.

On 12/05/2024, in business, corporate / business world, dangers of the status quo, Daniel S. Christian, ethics, faith, hearts -- matters of the heart, leadership, morals/values, relationships, religion, society, sociology, strategy, trends, United States, vendors, by Daniel Christian

From DSC:
I opened up a BRAND NEW box of cereal from Post the other day. As I looked down into the package, I realized that it was roughly half full. (This has happened many times before, but it struck me so much this time that I had to take pictures of it and post this item.)
.

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Looks can be deceiving for sure. It looks like I should have been getting a full box of cereal…but no…only about half of the package was full. It’s another example of the shrinkflation of things — which can also be described as people deceptively ripping other people off.

“As long as I’m earning $$, I don’t care how it impacts others.” <– That’s not me talking, but it’s increasingly the perspective that many Americans have these days. We don’t bother with ethics and morals…how old-fashioned can you get, right? We just want to make as much money as possible and to hell with how our actions/products are impacting others.

Another example from the food industry is one of the companies that I worked for in the 1990’s — Kraft Foods. Kraft has not served peoples’ health well at all. Even when they tried to take noble steps to provide healthier foods, other food executives/companies in the industry wouldn’t hop on board. They just wanted to please Wall Street, not Main Street. So companies like Kraft have contributed to the current situations that we face which involve obesity, diabetes, heart attacks, and other ailments. (Not to mention increased health care costs.)

The gambling industry doesn’t give a rip about people either. Look out for the consequences.

And the cannabis industry joins the gambling industry...and they’re often right on the doorsteps of universities and colleges.

Bottom line reflection:
There are REAL ramifications when we don’t take Christ’s words/commands to love one another seriously (or even to care about someone at all). We’re experiencing such ramifications EVERY DAY now.

Closing the digital use divide with active and engaging learning [Ascione]

On 12/04/2024, in active learning, Artificial Intelligence/Agents/LLMs/and Related, collaboration, communications, computer science, content development, aggregation, repositories, creativity, curriculum, data related items, education, education technology, educational games / serious games, engagement / engaging students, experimentation, face-to-face, instructional design, K-12 related, learning, learning ecosystem, Learning Experience Design, learning preferences, multimedia, new media literacies, personalized/customized learning, programming, simulations, skills, student teaching/teacher education, student-related, teachers, tools, United States, vendors, Virtual Reality (VR) / worlds / learning, vision/possibilities, XR - extended reality, youth, by Daniel Christian

Closing the digital use divide with active and engaging learning — from eschoolnews.com by Laura Ascione
Students offered insight into how to use active learning, with digital tools, to boost their engagement

When it comes to classroom edtech use, digital tools have a drastically different impact when they are used actively instead of passively–a critical difference examined in the 2023-2024 Speak Up Research by Project Tomorrow.

Students also outlined their ideal active learning technologies:

Collaboration tools to support projects
Student-teacher communication tools
Online databases for self-directed research
Multi-media tools for creating new content
Online and digital games
AI tools to support personalized learning
Coding and computer programming resources
Online animations, simulations, and virtual labs
Virtual reality equipment and content

(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:

World Labs’ AI can generate interactive 3D scenes from a single photo — from techcrunch.com by Kyle Wiggers

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:

ChatGPT turns two: how has it impacted markets? — from moneyweek.com
Two years on from ChatGPT’s explosive launch into the public sphere, we assess the impact that it has had on stock markets and the world of technology

DC: This is a great posting! “AI Tutors: Hype or Hope for Education?” [Bailey & Warner]

On 12/04/2024, in 21st century, 24x7x365 access, Artificial Intelligence/Agents/LLMs/and Related, content development, aggregation, repositories, education, education reform, education technology, emerging technologies, engagement / engaging students, experimentation, future, game-changing environment, Google, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learning, learning agents, learning ecosystem, Learning Experience Design, Learning from the Living [Class] Room, learning preferences, mathematics, multimedia, new media literacies, Open AI, personalized/customized learning, relationships, science, skills, student-related, teachers, the downsides of how people use tech, United States, vendors, vision/possibilities, writing, by Daniel Christian

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.

How to Secure Your 2025 Legal Tech [Bailey at the ABA] + several other legaltech-related items

On 12/03/2024, in Artificial Intelligence/Agents/LLMs/and Related, Canada, cloud-based computing / apps / other cloud-related, data related items, ethics, law schools, Legal operations, legal reform, legal technologies, legislatures / government / legal, policy, privacy, strategy, using teams, vendors, by Daniel Christian

How to Secure Your 2025 Legal Tech — from americanbar.org by Rachel Bailey

Summary

With firms increasingly open to AI tools, now is an exciting time to do some blue-sky thinking about your firm’s technology as a whole.
This is a chance for teams to envision the future of their firm’s technology landscape and make bold choices that align with long-term goals.
Learn six tips that will improve your odds of approval for your legal tech budget.

Also relevant, see:

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

Client expectations have shifted significantly in today’s technology-driven world. Quick communication and greater transparency are now a priority for clients throughout the entire case life cycle. This growing demand for tech-enhanced processes comes not only from clients but also from staff, and is set to rise even further as more advances become available.
…
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…

Just 10% of law firms have a GenAI policy, new Thomson Reuters report shows — from legaltechnology.com by Caroline Hill

Just 10% of law firms and 21% of corporate legal teams have now implemented policies to guide their organisation’s use of generative AI, according to a report out today (2 December) from Thomson Reuters.

AI & Law Symposium: Students Exploring Innovation, Challenges, and Legal Implications of a Technological Revolution — from allard.ubc.ca

Artificial Intelligence (AI) has been rapidly deployed around the world in a growing number of sectors, offering unprecedented opportunities while raising profound legal and ethical questions. This symposium will explore the transformative power of AI, focusing on its benefits, limitations, and the legal challenges it poses.

AI’s ability to revolutionize sectors such as healthcare, law, and business holds immense potential, from improving efficiency and access to services, to providing new tools for analysis and decision-making. However, the deployment of AI also introduces significant risks, including bias, privacy concerns, and ethical dilemmas that challenge existing legal and regulatory frameworks. As AI technologies continue to evolve, it is crucial to assess their implications critically to ensure responsible and equitable development.

The role of legal teams in creating AI ethics guardrails — from legaldive.com by Catherine Dawson
For organizations to balance the benefits of artificial intelligence with its risk, it’s important for counsel to develop policy on data governance and privacy.

How Legal Aid and Tech Collaboration Can Bridge the Justice Gap — from law.com by Kelli Raker and Maya Markovich
“Technology, when thoughtfully developed and implemented, has the potential to expand access to legal services significantly,” write Kelli Raker and Maya Markovich.

Challenges and Concerns
Despite the potential benefits, legal aid organizations face several hurdles in working with new technologies:

1. Funding and incentives: Most funding for legal aid is tied to direct legal representation, leaving little room for investment in general case management or exploration of innovative service delivery methods to exponentially scale impact.

2. Jurisdictional inconsistency: The lack of a unified court system or standardized forms across regions makes it challenging to develop accurate and widely applicable tech solutions in certain types of matters.

3. Organizational capacity: Many legal aid organizations lack the time and resources to thoroughly evaluate new tech offerings or collaboration opportunities or identify internal workflows and areas of unmet need with the highest chance for impact.

4. Data privacy and security: Legal aid providers need assurance that tech protects client data and avoids misuse of sensitive information.

5. Ethical considerations: There’s significant concern about the accuracy of information produced by consumer-facing technology and the potential for inadvertent unauthorized practice of law.

Two items re: AI in our learning ecosystems

On 11/27/2024, in Artificial Intelligence/Agents/LLMs/and Related, colleges, community colleges, content development, aggregation, repositories, corporate universities / corporate training, digital learning, education technology, emerging technologies, experimentation, future, future of higher education, game-changing environment, Google, higher education, human-computer interaction (HCI), ideas, innovation, instructional design, intelligent systems, IT in HE, K-12 related, learning, learning ecosystem, Learning Experience Design, platforms, productivity / tips and tricks, research, skills, student-related, teaching & learning, tools, training / L&D, United States, universities, vendors, by Daniel Christian

From DSC:
Notebook LM continues to make waves…

“Why Technology-Driven Law Firms Are Poised For Long-Term Success” [Farrar] + other items re: legaltech

On 11/27/2024, in Artificial Intelligence/Agents/LLMs/and Related, cloud-based computing / apps / other cloud-related, human-computer interaction (HCI), ideas, innovation, instructional design, law schools, learning, learning ecosystem, Learning Experience Design, Legal operations, legal reform, legal technologies, legislatures / government / legal, skills, tools, United States, vendors, by Daniel Christian

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:

Nvidia unveils AI model for music, audio that can modify voices, generate new sounds — from seekingalpha.com

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:

This is mind-blowing!

NVIDIA has introduced Edify 3D, a 3D AI generator that lets us create high-quality 3D scenes using just a simple prompt. And all the assets are fully editable!

This is going to revolutionise the way we create!

5 Examples: pic.twitter.com/5yWlvL1cWD

— el.cine (@EHuanglu) November 24, 2024

Skill-Based Training: Embrace the Benefits; Stay Wary of the Hype — from learningguild.com by Paige Yousey

1. Direct job relevance
One of the biggest draws of skill-based training is its direct relevance to employees’ daily roles. By focusing on teaching job-specific skills, this approach helps workers feel immediately empowered to apply what they learn, leading to a quick payoff for both the individual and the organization. Yet, while this tight focus is a major benefit, it’s important to consider some potential drawbacks that could arise from an overly narrow approach.

Be wary of:

Overly Narrow Focus: Highly specialized training might leave employees with little room to apply their skills to broader challenges, limiting versatility and growth potential.
Risk of Obsolescence: Skills can quickly become outdated, especially in fast-evolving industries. L&D leaders should aim for regular updates to maintain relevance.
Neglect of Soft Skills: While technical skills are crucial, ignoring soft skills like communication and problem-solving may lead to a lack of balanced competency.

2. Enhanced job performance…
3. Addresses skill gaps…
…and several more areas to consider

Another item from Paige Yousey

5 Key EdTech Innovations to Watch — from learningguild.com by Paige Yousey

AI-driven course design
…
Strengths

Content creation and updates: AI streamlines the creation of training materials by identifying resource gaps and generating tailored content, while also refreshing existing materials based on industry trends and employee feedback to maintain relevance.
Data-driven insights: Use AI tools to provide valuable analytics to inform course development and instructional strategies, helping learner designers identify effective practices and improve overall learning outcomes.
Efficiency: Automating repetitive tasks, such as learner assessments and administrative duties, enables L&D professionals to concentrate on developing impactful training programs and fostering learner engagement.

Concerns

Limited understanding of context: AI may struggle to understand the specific educational context or the unique needs of diverse learner populations, potentially hindering effectiveness.
Oversimplification of learning: AI may reduce complex educational concepts to simple metrics or algorithms, oversimplifying the learning process and neglecting deeper cognitive development.
Resistance to change: Learning leaders may face resistance from staff who are skeptical about integrating AI into their training practices.

Also from the Learning Guild, see:

Use Twine to Easily Create Engaging, Immersive Scenario-Based Learning — from learningguild.com by Bill Brandon

Scenario-based learning immerses learners in realistic scenarios that mimic real-world challenges they might face in their roles. These learning experiences are highly relevant and relatable. SBL is active learning. Instead of passively consuming information, learners actively engage with the content by making decisions and solving problems within the scenario. This approach enhances critical thinking and decision-making skills.

SBL can be more effective when storytelling techniques create a narrative that guides learners through the scenario to maintain engagement and make the learning memorable. Learners receive immediate feedback on their decisions and learn from their mistakes. Reflection can deepen their understanding. Branching scenarios add simulated complex decision-making processes and show the outcome of various actions through interactive scenarios where learner choices lead to different outcomes.

Embrace the Future: Why L&D Leaders Should Prioritize AI Digital Literacy — from learningguild.com by Dr. Erica McCaig

The role of L&D leaders in AI digital literacy
For L&D leaders, developing AI digital literacy within an organization requires a well-structured curriculum and development plan that equips employees with the knowledge, skills, and ethical grounding needed to thrive in an AI-augmented workplace. This curriculum should encompass a range of competencies that enhance technical understanding and foster a mindset ready for innovation and responsible use of AI. Key areas to focus on include:

Understanding AI Fundamentals: …
Proficiency with AI Tools: …
Ethical Considerations: …
Cultivating Critical Thinking: …

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.

What Teacher Pay and Benefits Look Like, in Charts — from edweek.org by Sarah D. Sparks

Special education staffing shortages put students’ futures at risk. How to solve that is tricky. — from chalkbeat.org by Kalyn Belsha

The debate comes as the number of students with disabilities is growing. Some 7.5 million students required special education services as of the 2022-23 school year, the latest federal data shows, or around 15% of students. That was up from 7.1 million or 14% of students in the 2018-19 school year, just before the pandemic hit.

It’s unclear if the rise is due to schools getting better at identifying students with disabilities or if more children have needs now. Many young children missed early intervention and early special education services during the pandemic, and many educators say they are seeing higher behavioral needs and wider academic gaps in their classrooms.

“Students are arriving in our classrooms with a high level of dysregulation, which is displayed through their fight, flight, or freeze responses,” Tiffany Anderson, the superintendent of Topeka, Kansas’ public schools, wrote in her statement. “Students are also displaying more physically aggressive behavior.”

Expanding Access, Value and Experiences Through Credentialing — from gettingsmart.com by Nate McClennen, Tom Vander Ark and Mason Pashia
A Landscape Analysis of Credentialing and Its Impact on K-12

Executive Summary

This report examines the evolving landscape of credentialing and learner records within global education systems, highlighting a shift from traditional time-based signals—such as courses and grades—to competency-based signals (credentials and learner records).

Also recommended by Getting Smart, see:

New Goals Learning Experiences and Signals — — from gettingsmart.com by Tom Vander Ark and Carri Schneider

Retrieval practice improves learning for neurodiverse students — from by Pooja K. Agarwal, Ph.D.

In my 15+ years of teaching, I have had students with autism spectrum disorder, ADHD, dyslexia, and a range of learning disabilities. I have grown in my understanding of inclusive teaching practices and I strive to incorporate universal design principles in my teaching.

From my classroom experience, I know that retrieval practice improves learning for all of my students, including those who are neurodiverse. But what have researchers found about retrieval practice with neurodiverse learners?

(Side note: If you’d like an intro on neurodiversity and what it means in the classroom, I recommend this podcast episode from The Learning Scientists and this podcast episode from Teaching in Higher Ed. For teaching tips, I recommend this article from the University of Illinois CITL.)

Instructure Is Ready To Lead The Next Evolution In Learning — from forbes.com by Ray Ravaglia

Learning Management In The AI Future
While LMS platforms like Canvas have positively impacted education, they’ve rarely lived up to their potential for personalized learning. With the advent of artificial intelligence (AI), this is set to change in revolutionary ways.

The promise of AI lies in its ability to automate repetitive tasks associated with student assessment and management, freeing educators to focus on education. More significantly, AI has the potential to go beyond the narrow focus on the end products of learning (like assignments) to capture insights into the learning process itself. This means analyzing the entire transcript of activities within the LMS, providing a dynamic, data-driven view of student progress rather than just seeing signposts of where students have been and what they have taken away.
…
Things become more potent by moving away from a particular student’s traversal of a specific course to looking at large aggregations of students traversing similar courses. This is why Instructure’s acquisition of Parchment, a company specializing in credential and transcript management, is so significant.

Sharpen your students’ interview skills — from timeshighereducation.com by Lewis Humphreys (though higher education-related, this is still solid information for those in K12)
The employees of the future will need to showcase their skills in job interviews. Make sure they’re prepared for each setting, writes Lewis Humphreys

In today’s ultra-competitive job market, strong interview skills are paramount for students taking their first steps into the professional world. University careers services play a crucial role in equipping our students with the tools and confidence needed to excel in a range of interview settings. From pre-recorded video interviews to live online sessions and traditional face-to-face meetings, students must be adaptable and well-prepared. Here, I’ll explore ways universities can teach interview skills to students and graduates, helping them to present themselves and their skills in the best light possible.

Learning Ecosystems

DC: From a box of Post cereal, a deep reflection.

5 items re: AI in general

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