Another ‘shock’ is coming for American jobs — from washingtonpost.com by Heather Long. DSC: This is a gifted article Millions of workers will need to shift careers. Our country is unprepared.
The United States is on the cusp of a massive economic shift due to AI, and it’s likely to cause greater change than anything President Donald Trump does in his second term. Much good can come from AI, but the country is unprepared to grapple with the need for millions — or perhaps tens of millions — of workers to shift jobs and entire careers.
“There’s a massive risk that entry-level, white-collar work could get automated. What does that do to career ladders?” asked Molly Kinder, a fellow at the Brookings Institution. Her research has found the jobs of marketing analysts are five times as likely to be replaced as those of marketing managers, and sales representative jobs are three times as likely to be replaced as those of sales managers.
Young people working in these jobs will need to be retrained, but it will be hard for them to invest in new career paths. Consider that many college graduates already carry a lot of debt (an average of about $30,000 for those who took student loans).What’s more, the U.S. unemployment insurance system covers only about 57 percent of unemployed workers and replaces only a modest amount of someone’s pay.
From DSC: This is another reason why I think this vision here is at least a part of our future. We need shorter, less expensive credentials.
People don’t have the time to get degrees that take 2+ years to complete (after they have already gone through college once).
They don’t want to come out with more debt on their backs.
With inflation going back up, they won’t have as much money anyway.
Also, they may already have enough debt on their backs.
Over the course of the next 10 years, AI-powered institutions will rise in the rankings. US News & World Report will factor a college’s AI capabilities into its calculations. Accrediting agencies will assess the degree of AI integration into pedagogy, research, and student life. Corporations will want to partner with universities that have demonstrated AI prowess. In short, we will see the emergence of the AI haves and have-nots.
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What’s happening in higher education today has a name: creative destruction. The economist Joseph Schumpeter coined the term in 1942 to describe how innovation can transform industries. That typically happens when an industry has both a dysfunctional cost structure and a declining value proposition. Both are true of higher education.
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Out of the gate, professors will work with technologists to get AI up to speed on specific disciplines and pedagogy. For example, AI could be “fed” course material on Greek history or finance and then, guided by human professors as they sort through the material, help AI understand the structure of the discipline, and then develop lectures, videos, supporting documentation, and assessments.
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In the near future, if a student misses class, they will be able watch a recording that an AI bot captured. Or the AI bot will find a similar lecture from another professor at another accredited university. If you need tutoring, an AI bot will be ready to help any time, day or night. Similarly, if you are going on a trip and wish to take an exam on the plane, a student will be able to log on and complete the AI-designed and administered exam. Students will no longer be bound by a rigid class schedule. Instead, they will set the schedule that works for them.
Early and mid-career professors who hope to survive will need to adapt and learn how to work with AI. They will need to immerse themselves in research on AI and pedagogy and understand its effect on the classroom.
From DSC: I had a very difficult time deciding which excerpts to include. There were so many more excerpts for us to think about with this solid article. While I don’t agree with several things in it, EVERY professor, president, dean, and administrator working within higher education today needs to read this article and seriously consider what Scott Latham is saying.
Change is already here, but according to Scott, we haven’t seen anything yet. I agree with him and, as a futurist, one has to consider the potential scenarios that Scott lays out for AI’s creative destruction of what higher education may look like. Scott asserts that some significant and upcoming impacts will be experienced by faculty members, doctoral students, and graduate/teaching assistants (and Teaching & Learning Centers and IT Departments, I would add). But he doesn’t stop there. He brings in presidents, deans, and other members of the leadership teams out there.
There are a few places where Scott and I differ.
The foremost one is the importance of the human element — i.e., the human faculty member and students’ learning preferences. I think many (most?) students and lifelong learners will want to learn from a human being. IBM abandoned their 5-year, $100M ed push last year and one of the key conclusions was that people want to learn from — and with — other people:
To be sure, AI can do sophisticated things such as generating quizzes from a class reading and editing student writing. But the idea that a machine or a chatbot can actually teach as a human can, he said, represents “a profound misunderstanding of what AI is actually capable of.”
Nitta, who still holds deep respect for the Watson lab, admits, “We missed something important. At the heart of education, at the heart of any learning, is engagement. And that’s kind of the Holy Grail.”
— Satya Nitta, a longtime computer researcher at
IBM’s Watson Research Center in Yorktown Heights, NY .
By the way, it isn’t easy for me to write this. As I wanted AI and other related technologies to be able to do just what IBM was hoping that it would be able to do.
Also, I would use the term learning preferences where Scott uses the term learning styles.
Scott also mentions:
“In addition, faculty members will need to become technologists as much as scholars. They will need to train AI in how to help them build lectures, assessments, and fine-tune their classroom materials. Further training will be needed when AI first delivers a course.”
It has been my experience from working with faculty members for over 20 years that not all faculty members want to become technologists. They may not have the time, interest, and/or aptitude to become one (and vice versa for technologists who likely won’t become faculty members).
That all said, Scott relays many things that I have reflected upon and relayed for years now via this Learning Ecosystems blog and also via The Learning from the Living [AI-Based Class] Room vision — the use of AI to offer personalized and job-relevant learning, the rising costs of higher education, the development of new learning-related offerings and credentials at far less expensive prices, the need to provide new business models and emerging technologies that are devoted more to lifelong learning, plus several other things.
So this article is definitely worth your time to read, especially if you are working in higher education or are considering a career therein!
Google Public Sector and the University of Michigan’s Ross School of Business have launched an advanced Virtual Teaching Assistant pilot program aimed at improving personalized learning and enlightening educators on artificial intelligence in the classroom.
The AI technology, aided by Google’s Gemini chatbot, provides students with all-hours access to support and self-directed learning. The Virtual TA represents the next generation of educational chatbots, serving as a sophisticated AI learning assistant that instructors can use to modify their specific lessons and teaching styles.
The Virtual TA facilitates self-paced learning for students, provides on-demand explanations of complex course concepts, guides them through problem-solving, and acts as a practice partner. It’s designed to foster critical thinking by never giving away answers, ensuring students actively work toward solutions.
From DSC: Look out Google, Amazon, and others! Nvidia is putting the pedal to the metal in terms of being innovative and visionary! They are leaving the likes of Apple in the dust.
The top talent out there is likely to go to Nvidia for a while. Engineers, programmers/software architects, network architects, product designers, data specialists, AI researchers, developers of robotics and autonomous vehicles, R&D specialists, computer vision specialists, natural language processing experts, and many more types of positions will be flocking to Nvidia to work for a company that has already changed the world and will likely continue to do so for years to come.
NVIDIA just shook the AI and Robotic world at NVIDIA GTC 2025.
CEO Jensen Huang announced jaw-dropping breakthroughs.
Here are the top 11 key highlights you can’t afford to miss: (wait till you see no 3) pic.twitter.com/domejuVdw5
For enterprises, NVIDIA unveiled DGX Spark and DGX Station—Jensen’s vision of AI-era computing, bringing NVIDIA’s powerful Blackwell chip directly to your desk.
Nvidia Bets Big on Synthetic Data — from wired.com by Lauren Goode Nvidia has acquired synthetic data startup Gretel to bolster the AI training data used by the chip maker’s customers and developers.
Nvidia, xAI to Join BlackRock and Microsoft’s $30 Billion AI Infrastructure Fund — from investopedia.com by Aaron McDade Nvidia and xAI are joining BlackRock and Microsoft in an AI infrastructure group seeking $30 billion in funding. The group was first announced in September as BlackRock and Microsoft sought to fund new data centers to power AI products.
AI Super Bowl. Hi everyone. This week, 20,000 engineers, scientists, industry executives, and yours truly descended upon San Jose, Calif. for Nvidia’s annual GTC developers’ conference, which has been dubbed the “Super Bowl of AI.”
The Size of the Problem: Judicial Backlog and Inefficiencies India has a massive backlog of more than 47 million pending cases, with civil litigation itself averaging 1,445 days in resolution. In the United States, federal courts dispose of nearly 400,000 cases a year, and complex litigations take years to complete. Artificial intelligence-driven case law research, contract automation, and predictive analytics will cut legal research times by 90%, contract drafting fees by 60%, and hasten case settlements, potentially saving billions of dollars in legal costs.
This is not just an evolution—it is a permanent change toward data-driven jurisprudence, with AI supplementing human capabilities, speeding up delivery of justice, and extending access to legal services. The AI revolution for legal tech is not on its way; it is already under way, dismantling inefficiencies and transforming the legal world in real time.
Legal tech innovators discuss how they are working to scale and improve their successful projects on Talk Justice. FosterPower and Legal Aid Content Intelligence (LACI) leverage technology to make high-quality legal information available to people for free online. Both also received Technology Initiative Grants (TIG) from the Legal Services Corporation to launch their projects. Then, in 2024 they were both selected for a different TIG, called the Sustainability, Enhancement and Adoption (SEA) grant. This funding supports TIG projects that have demonstrated excellent results as they improve their tools and work to increase uptake.
Blind Spot on AI — from the-job.beehiiv.com by Paul Fain Office tasks are being automated now, but nobody has answers on how education and worker upskilling should change.
Students and workers will need help adjusting to a labor market that appears to be on the verge of a historic disruption as many business processes are automated. Yet job projections and policy ideas are sorely lacking.
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The benefits of agentic AI are already clear for a wide range of organizations, including small nonprofits like CareerVillage. But the ability to automate a broad range of business processes means that education programs and skills training for knowledge workers will need to change. And as Chung writes in a must-read essay, we have a blind spot with predicting the impacts of agentic AI on the labor market.
“Without robust projections,” he writes, “policymakers, businesses, and educators won’t be able to come to terms with how rapidly we need to start this upskilling.”
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.
The Edtech Insiders Generative AI Map — from edtechinsiders.substack.com by Ben Kornell, Alex Sarlin, Sarah Morin, and Laurence Holt A market map and database featuring 60+ use cases for GenAI in education and 300+ GenAI powered education tools.
Used thoughtfully, ChatGPT can be a powerful tool to help students develop skills of rigorous thinking and clear writing, assisting them in thinking through ideas, mastering complex concepts, and getting feedback on drafts.
There are also ways to use ChatGPT that are counterproductive to learning—like generating an essay instead of writing it oneself, which deprives students of the opportunity to practice, improve their skills, and grapple with the material.
For students committed to becoming better writers and thinkers, here are some ways to use ChatGPT to engage more deeply with the learning process.
The Big Idea: As employers increasingly seek out applicants with AI skills, community colleges are well-positioned to train up the workforce. Partnerships with tech companies, like the AI Incubator Network, are helping some colleges get the resources and funding they need to overhaul programs and create new AI-focused ones.
Along these lines also see:
Practical AI Training — from the-job.beehiiv.com by Paul Fain Community colleges get help from Big Tech to prepare students for applied AI roles at smaller companies.
Miami Dade and other two-year colleges try to be nimble by offering training for AI-related jobs while focusing on local employers. Also, Intel’s business struggles while the two-year sector wonders if Republicans will cut funds for semiconductor production.
In this conversation, Josh Bersin discusses the evolving landscape of AI platforms, particularly focusing on Microsoft’s positioning and the challenges of creating a universal AI agent. He delves into the complexities of government efficiency, emphasizing the institutional challenges faced in re-engineering government operations.
The conversation also highlights the automation of work tasks and the need for businesses to decompose job functions for better efficiency.
Bersin stresses the importance of expertise in HR, advocating for a shift towards full stack professionals who possess a broad understanding of various HR functions.
Finally, he addresses the impending disruption in Learning and Development (L&D) due to AI advancements, predicting a significant transformation in how L&D professionals will manage knowledge and skills.
Episode Notes
As genAI continues to edge into all facets of our lives, Dr. Megan Ma has been exploring integrations for this technology in legal, but, more importantly, how it can help lawyers and law students hone their legal skills. Dennis and Tom talk with Dr. Ma about her work and career path and many of the latest developments in legal tech. They take a deep dive into a variety of burgeoning AI tools and trends, and Dr. Ma discusses how her interdisciplinary mindset has helped her develop a unique perspective on the possibilities for AI in the legal profession and beyond.
Legal tech disruption: Doing it on purpose — from localgovernmentlawyer.co.uk Thomson Reuters looks at the role that a legal technology roadmap can play in improving the operations of in-house legal departments.
Disruption in the legal industry remains a powerful force – from the death of the billable hour to robot lawyers and generative AI. Leaders are facing weighty issues that demand long-term, visionary thinking and that will change the way legal professionals do their jobs.
With half of in-house legal departments increasing their use of legal technology tools, many GCs are taking the initiative to address continued, growing expectations from the business for systems that can make operations better. How can you prepare for a tech or process change so that people come along with you, rather than living in constant fire-fighting mode?
The Top 10 Emerging Technologies report is a vital source of strategic intelligence. First published in 2011, it draws on insights from scientists, researchers and futurists to identify 10 technologies poised to significantly influence societies and economies. These emerging technologiesare disruptive, attractive to investors and researchers, and expected to achieve considerable scale within five years. This edition expands its analysis by involving over 300 experts from the Forum’s Global Future Councils and a global network of comprising over 2,000 chief editors worldwide from top institutions through Frontiers, a leading publisher of academic research.
How Learning Designers Are Using AI for Analysis — from drphilippahardman.substack.com by Dr. Philippa Hardman A practical guide on how to 10X your analysis process using free AI tools, based on real use cases
There are three key areas where AI tools make a significant impact on how we tackle the analysis part of the learning design process:
Understanding the why: what is the problem this learning experience solves? What’s the change we want to see as a result?
Defining the who: who do we need to target in order to solve the problem and achieve the intended goal?
Clarifying the what: given who our learners are and the goal we want to achieve, what concepts and skills do we need to teach?
Two new surveys, both released this month, show how high school and college-age students are embracing artificial intelligence. There are some inconsistencies and many unanswered questions, but what stands out is how much teens are turning to AI for information and to ask questions, not just to do their homework for them. And they’re using it for personal reasons as well as for school. Another big takeaway is that there are different patterns by race and ethnicity with Black, Hispanic and Asian American students often adopting AI faster than white students.
We’ve ceded so much trust to digital systems already that most simply assume a tool is safe to use with students because a company published it. We don’t check to see if it is compliant with any existing regulations. We don’t ask what powers it. We do not question what happens to our data or our student’s data once we upload it. We likewise don’t know where its information came from or how it came to generate human-like responses. The trust we put into these systems is entirely unearned and uncritical.
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The allure of these AI tools for teachers is understandable—who doesn’t want to save time on the laborious process of designing lesson plans and materials? But we have to ask ourselves what is lost when we cede the instructional design process to an automated system without critical scrutiny.
From DSC: I post this to be a balanced publisher of information. I don’t agree with everything Marc says here, but he brings up several solids points.
As news about generative artificial intelligence (GenAI) continually splashes across social media feeds, including how ChatGPT 4o can help you play Rock, Paper, Scissors with a friend, breathtaking pronouncements about GenAI’s “disruptive” impact aren’t hard to find.
It turns out that it doesn’t make much sense to talk about GenAI as being “disruptive” in and of itself.
Can it be part of a disruptive innovation? You bet.
But much more important than just the AI technology in determining whether something is disruptive is the business model in which the AI is used—and its competitive impact on existing products and services in different markets.
On a somewhat note, also see:
National summit explores how digital education can promote deeper learning — from digitaleducation.stanford.edu by Jenny Robinson; via Eric Kunnen on Linkedin.com The conference, held at Stanford, was organized to help universities imagine how digital innovation can expand their reach, improve learning, and better serve the public good.
The summit was organized around several key questions: “What might learning design, learning technologies, and educational media look like in three, five, or ten years at our institutions? How will blended and digital education be poised to advance equitable, just, and accessible education systems and contribute to the public good? What structures will we need in place for our teams and offices?”
What if, for example, the corporate learning system knew who you were and you could simply ask it a question and it would generate an answer, a series of resources, and a dynamic set of learning objects for you to consume? In some cases you’ll take the answer and run. In other cases you’ll pour through the content. And in other cases you’ll browse through the course and take the time to learn what you need.
And suppose all this happened in a totally personalized way. So you didn’t see a “standard course” but a special course based on your level of existing knowledge?
This is what AI is going to bring us. And yes, it’s already happening today.
From DSC: This first item is related to the legal field being able to deal with today’s issues:
The Best Online Law School Programs (2024) — from abovethelaw.com by Staci Zaretsky A tasty little rankings treat before the full Princeton Review best law schools ranking is released.
Several law schools now offer online JD programs that have become as rigorous as their on-campus counterparts. For many JD candidates, an online law degree might even be the smarter choice. Online programs offer flexibility, affordability, access to innovative technologies, students from a diversity of career backgrounds, and global opportunities.
Voila! Feast your eyes upon the Best Online JD Programs at Law School for 2024 (in alphabetical order):
Mitchell Hamline School of Law – Hybrid J.D.
Monterey College of Law – Hybrid Online J.D.
Purdue Global Law School – Online J.D.
Southwestern Law School – Online J.D.
Syracuse University – J.D. Interactive
University of Dayton School of Law – Online Hybrid J.D.
University of New Hampshire – Hybrid J.D.
DSC: FINALLY!!! Online learning hits law schools (at least in a limited fashion)!!! Maybe there’s hope yet for the American Bar Association and for America’s legal system to be able to deal with the emerging technologies — and the issues presented therein — in the 21st century!!! Because if we can’t even get caught up to where numerous institutions of higher education were back at the turn of this century, we don’t have as much hope in the legal field being able to address things like AI, XR, cryptocurrency, blockchain, and more.
Advocate, advise, and accompany— from jordanfurlong.substack.com by Jordan Furlong These are the three essential roles lawyers will play in the post-AI era. We need to start preparing legal education, lawyer licensing, and law practices to adapt.
Consider this scenario:
Ten years from now, Generative AI has proven capable of a stunning range of legal activities. Not only can it accurately write legal documents and conduct legal research and apply law to facts, it can reliably oversee legal document production, handle contract negotiations, monitor regulatory compliance, render legal opinions, and much more. Lawyers are no longer needed to carry out these previously billable tasks or even to double-check the AI’s performance. Tasks that once occupied 80% of lawyers’ billable time have been automated.
What are the chances this scenario unfolds within the next ten years? You can decide that likelihood for yourself, but I think anything above 1% represents the potential for major disruption to the legal profession.
Also from Jordan, see:
Could Generative AI help solve the law’s access dilemma? Legal regulators have failed to strike the right balance between accessibility and quality in legal services. It’s just possible that Gen AI could open the door to an entirely new solution.
We have gathered, from Colin Levy’s insights, the top five strategies that legal professionals can implement to excel in this transformational era – bringing them together with technology.
Going further than just legal spend, analytics on volume of work and diversity metrics can help legal teams make the business case they need to drive important initiatives and decisions forward. And a key differentiator of top-performing companies is the ability to get all of this data in one place, which is why Mitratech was thrilled to unveil PlatoBI, an embedded analytics platform powered by Snowflake, earlier this year with several exciting AI and Analytic enhancements.
Also worrisome is that AI will be used as a crutch that short circuits learning. Some people look for shortcuts. What effect of AI on that learning process and the result, for students and when lawyers use AI to draft documents and research?
How Workers Rise— from the-job.beehiiv.com by Paul Fain A look forward at skills-based hiring and AI’s impacts on education and work.
Impacts of AI: Fuller is optimistic about companies making serious progress on skills-based hiring over the next five to 10 years. AI will help drive that transformation, he says, by creating the data to better understand the skills associated with jobs.
The technology will allow for a more accurate matching of skills and experiences, says Fuller, and for companies to “not rely on proxies like degrees or grade point averages or even the proxy of what someone currently makes or how fast they’ve gotten promoted on their résumé.”
Change is coming soon, Fuller predicts, particularly as AI’s impacts accelerate. And the disruption will affect wealthier Americans who’ve been spared during previous shifts in the labor market.
The Kicker: “When people in bedroom suburbs are losing their six-figure jobs, that changes politics,” Fuller says. “That changes the way people are viewing things like equity and where that leads. It’s certainly going to put a lot of pressure on the way the system has worked.”
More Chief Online Learning Officers Step Up to Senior Leadership Roles In 2024, I think we will see more Chief Online Learning Officers (COLOs) take on more significant roles and projects at institutions.
In recent years, we have seen many COLOs accept provost positions. The typical provost career path that runs up through the faculty ranks does not adequately prepare leaders for the digital transformation occurring in postsecondary education.
As we’ve seen with the professionalization of the COLO role, in general, these same leaders proved to be incredibly valuable during the pandemic due to their unique skills: part academic, part entrepreneur, part technologist, COLOs are unique in higher education. They sit at the epicenter of teaching, learning, technology, and sustainability. As institutions are evolving, look for more online and professional continuing leaders to take on more senior roles on campuses.
Julie Uranis, Senior Vice President, Online and Strategic Initiatives, UPCEA
So, as educators, mentors, and guides to our future generations, we must ask ourselves three pivotal questions:
What value do we offer to our students?
What value will they need to offer to the world?
How are we preparing them to offer that value?
The answers to these questions are crucial, and they will redefine the trajectory of our education system.
We need to create an environment that encourages curiosity, embraces failure as a learning opportunity, and celebrates diversity. We need to teach our students how to learn, how to ask the right questions, and how to think for themselves.
Leveraging ChatGPT for learning is the most meaningful skill this year for lifelong learners. But it’s too hard to find resources to master it.
As a learning science nerd, I’ve explored hundreds of prompts over the past months. Most of the advice doesn’t go beyond text summaries and multiple-choice testing.
That’s why I’ve created this article — it merges learning science with prompt writing to help you learn anything faster.
Midjourney AI Art for Teachers (for any kind of teacher, not just Art Teachers) — from The AI Educator on YouTube by Dan Fitzpatrick
From DSC: This is a very nice, clearly illustrated, free video to get started with the Midjourney (text-to-image) app. Nice work Dan!
In the new-normal of generative AI, how does one articulate the value of academic integrity? This blog presents my current response in about 2,500 words; a complete answer could fill a sizable book.
Massive amounts of misinformation are disseminated about generative AI, so the first part of my discussion clarifies what large language models (Chat-GPT and its counterparts) can currently do and what they cannot accomplish at this point in time. The second part describes ways in which generative AI can be misused as a means of learning; unfortunately, many people are now advocating for these mistaken applications to education. The third part describes ways in which large language models (LLM), used well, may substantially improve learning and education. I close with a plea for a robust, informed public discussion about these topics and issues.
Many of the more than a dozen teachers TIME interviewed for this story argue that the way to get kids to care is to proactively use ChatGPT in the classroom.
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Some of those creative ideas are already in effect at Peninsula High School in Gig Harbor, about an hour from Seattle. In Erin Rossing’s precalculus class, a student got ChatGPT to generate a rap about vectors and trigonometry in the style of Kanye West, while geometry students used the program to write mathematical proofs in the style of raps, which they performed in a classroom competition. In Kara Beloate’s English-Language Arts class, she allowed students reading Shakespeare’s Othello to use ChatGPT to translate lines into modern English to help them understand the text, so that they could spend class time discussing the plot and themes.
I found that other developed countries share concerns about students cheating but are moving quickly to use AI to personalize education, enhance language lessons and help teachers with mundane tasks, such as grading. Some of these countries are in the early stages of training teachers to use AI and developing curriculum standards for what students should know and be able to do with the technology.
Several countries began positioning themselves several years ago to invest in AI in education in order to compete in the fourth industrial revolution.
AI in Education— from educationnext.org by John Bailey The leap into a new era of machine intelligence carries risks and challenges, but also plenty of promise
In the realm of education, this technology will influence how students learn, how teachers work, and ultimately how we structure our education system. Some educators and leaders look forward to these changes with great enthusiasm. Sal Kahn, founder of Khan Academy, went so far as to say in a TED talk that AI has the potential to effect “probably the biggest positive transformation that education has ever seen.” But others warn that AI will enable the spread of misinformation, facilitate cheating in school and college, kill whatever vestiges of individual privacy remain, and cause massive job loss. The challenge is to harness the positive potential while avoiding or mitigating the harm.
Generative AI and education futures — from ucl.ac.uk Video highlights from Professor Mike Sharples’ keynote address at the 2023 UCL Education Conference, which explored opportunities to prosper with AI as a part of education.
Bringing AI Literacy to High Schools— from by Nikki Goth Itoi Stanford education researchers collaborated with teachers to develop classroom-ready AI resources for high school instructors across subject areas.
To address these two imperatives, all high schools need access to basic AI tools and training. Yet the reality is that many underserved schools in low-income areas lack the bandwidth, skills, and confidence to guide their students through an AI-powered world. And if the pattern continues, AI will only worsen existing inequities. With this concern top of mind plus initial funding from the McCoy Ethics Center, Lee began recruiting some graduate students and high school teachers to explore how to give more people equal footing in the AI space.
