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unitedhealthcare warns of possible coverage loss – selfemployed.com
UnitedHealthcare has notified Medicare Advantage patients in Rhode Island that they may lose coverage at several local hospitals if a deal is not reached with Brown University Health by July 1. The potential loss of coverage would impact Hasbro Children’s, Newport, Miriam, and Rhode Island Hospitals, but not the physicians of Brown University Health.
A spokesperson for Brown University Health said, “In addition to a modest reimbursement rate increase to cover the costs of caring for their members, we asked United to eliminate their administrative policies that deviate from traditional Medicare, such as unnecessary prior approval and utilization management, that cause frustration for patients and result in extra cost to our healthcare system.
Since both parties held firm in their positions, we mutually decided to end our Medicare Advantage hospital contract effective June 30, 2025.”
UnitedHealthcare stated that its top priority is to reach a long-term agreement that is both affordable and maintains competitive benefits for its Medicare Advantage members. They hope Brown University Health shares their commitment to reaching an agreement that provides continued network access to its hospitals for people enrolled in Medicare Advantage plans.
If an agreement is not reached, UnitedHealthcare’s Medicare Advantage members may find themselves paying more to get care at Brown University Health’s Rhode Island-based hospitals. The change would affect subscribers relying on Brown University Health’s hospitals, but physicians from Brown University Health will remain in the Medicare Advantage network regardless of the ongoing contract negotiations. The current agreement between UnitedHealthcare and Brown University Health remains effective through June 30, 2025.
Should the negotiations fail, Brown University Health’s hospitals will exit the network for all Medicare Advantage plans, including Dual Special Needs Plan and Group Retiree plans, effective July 1, 2025. Saint Anne’s and Morton Hospitals in Massachusetts, both owned by Brown University Health, will not be impacted by the potential contract impasse.
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Indiana University Taps Ecore for Fitness Center Flooring, Sees Strong Return – Athletech News
Indiana University (IU) selected Ecore Athletic, a leading manufacturer of performance flooring and athletic surfaces, as its flooring partner for the recent renovation of its Student Recreational Sports Center on the school’s flagship Bloomington campus. The university is seeing positive early results from the change, including increased student engagement at the facility.
Driven by student demand for more strength and functional training areas, the renovation included the installation of Ecore Athletic’s Performance Beast Plus flooring system, paired with Modzilla 32 ShockPad tiles. IU chose Ecore’s flooring solution for its high durability, impact absorption and brand-customizable design, all of which are critical elements for a facility that sees over one million visits annually.
“The Ecore floor allows us to take the impact of any activity, protect the subfloor and keep students focused on their well-being – not on whether the floor is holding up,” said Nick Horton, IU’s director of service operations.
A key aspect of the installation includes 16 custom lifting platforms, each featuring IU’s logo inlaid directly into the surface. These platforms are in near-constant use, underscoring rising student interest in strength training.
“There was some concern early on that 16 platforms might be too many,” said Brady Bowdoin, assistant director of personal training and wellness at IU. “It turns out 16 is not enough.”
In addition to performance upgrades, the renovation focused on improving space utilization and inclusivity. Former racquetball courts were converted into open training zones outfitted with turf and rubber flooring (another move in line with fitness industry trends). The result has been broader student engagement and increased diversity in facility users, IU reports.
“One of the biggest changes is our user group,” Bowdoin said. “Before, it was mostly traditional gym-goers. Now, we’re seeing students from all backgrounds using the space. What we thought might deter some users has made the space more welcoming.”
Ecore, which upcycles waste rubber into high-performance flooring solutions, has worked with top athletic, wellness and commercial fitness facilities including GymNation and East Bank Club.
Ecore’s Performance Beast Plus product is a 10.5mm performance flooring system featuring a 2.5mm wear layer fusion-bonded to an 8mm vulcanized composition rubber (VCR) base, and is slip-resistant to reduce injury risk in heavy-use zones.
Underneath, Modzilla ShockPad tiles provide an additional layer of impact absorption and subfloor protection with 32mm interlocking tiles that float over existing flooring. The IU team chose the Modzilla underlayment in part because they needed to float the new flooring over an existing court.
“This project is a great example of what can be accomplished when manufacturers, dealer partners and facility leaders are all aligned,” said Ryan Clavenna, Ecore Athletic’s territory representative.
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Service costs aren't exploding anymore – Noahpinion | Noah Smith
In the 2010s, economics discussions went mainstream. Blogs and (especially) social media meant that data-driven, high-level debates about economic issues were no longer confined to the op-ed pages of the Wall Street Journal and the talking heads on CNBC. This was a good thing, but I think it had some unintended consequences. One is that a lot of the narratives that made sense in 2012 or 2015 got embedded into the popular consciousness, and have stayed there even though the underlying reality has changed.
One big example of this is wage stagnation. In the early 2010s, lots of people “knew” that American middle-class wages had stagnated since the early 1970s, with only a brief temporary revival in the late 90s. And so naturally, a lot of discussions revolved around how to fix that. But even as we were having those arguments, wages accelerated again. Now, when we look back with the benefit of ten more years of hindsight, the years since the mid-1990s look like a bumpy but substantial increase:
Another big narrative, related to the wage stagnation idea, is that service costs are relentlessly rising in the U.S. economy. You’ve probably seen some version of Mark Perry’s famous “price changes” chart:
This chart tells a simple, powerful story: Services get more expensive, while physical goods get cheaper. Health care, education, and child care went up in price faster than wages, while cars, clothing, electronics, and toys got more affordable.
And the story was compelling because it came with a simple theory to explain it. This was the notion that manufacturing productivity naturally increases faster than service productivity. Conceptually, it seems easier to figure out how to rearrange production processes in a factory, and apply new machine tools, than to figure out new ways to educate kids or take care of Grandma.
And during the 20th century, this principle held true. For example, from 1987 to 2011, manufacturing productivity more than doubled, while overall productivity increased by only 70%:
In fact, if you look on Wikipedia’s page for “Baumol’s Effect”, also known as Baumol Cost Disease, it lists this productivity divergence as an explanation for diverging costs.
If service costs rise relentlessly while manufacturing costs fall, it portends a grim future — one where we have cheap gadgets, but where the big necessities of modern middle-class life are increasingly out of reach. And in fact, that was the story a lot of people were telling in the mid-2010s.
That story led to a certain techno-pessimism. If technology could give us cheap gadgets, but couldn’t make the basics of modern life any cheaper, what good was it? The failure of educational technologies like online education only seemed to drive the point home — it seemed like we’d always just be stuck with a teacher giving lectures on a board to 20 or 30 kids. Though some people dreamed of robot nurses and nannies, these seemed very far from materializing.
It also fed into cynicism about trade. If China gave us cheap gadgets but we were still struggling to pay for health care and education, wasn’t globalization sort of a booby prize? I think we see echoes of that sentiment in the GOP’s willingness to embrace Trump’s tariffs.
On the policy side, rising service costs led to two different big ideas.
First, if technology couldn’t make services cheaper, some people (including myself) reasoned, we should use policy to make them cheaper. Perhaps deregulation was the key — many libertarians blamed rising service costs on a policy of “cost disease socialism” that restricted supply while subsidizing demand, implying that we just had to eliminate the supply restrictions and cut the subsidies and the market would do its thing. Progressives advocated a more statist approach — after all, most other countries have some form of national health insurance, and they all have cheaper health costs than America does, so perhaps government bargaining power was the key to driving costs down. (Personally, I supported doing both approaches in parallel.)
The second big policy idea said that what we want isn’t necessarily for services to cost less to produce; what we want is for services to cost less to the people who consume them. Productivity improvements in the service sector would just throw human beings out of work, as they had done in manufacturing; instead, a future where everyone gets a high-paying job taking care of everyone else sounded pretty good to some progressives.
So how do we make services cheap to consume, but keep using “care jobs” as the future of good-paying middle-class work? Taxes and subsidies were how progressives planned to square that circle. If rich people could be taxed at much higher rates, that money could be used to create higher wages and more jobs for care workers and lower prices for consumers. For example, here’s what Heather Boushey, one of Biden’s most influential economic advisors, told the Aspen Institute in 2021:
“This year has taught us all, across the nation, how the care economy is the foundation of our economy,” Boushey remarked…Boushey reflects on the twin crises of a lack of good care and a lack of good jobs and notes that investing in the care economy creates a positive feedback loop that allows family caregivers to find quality care and care workers to find quality jobs.
Natalie Foster and Amanda Newman wrote that “policy [should] contribute to building a care economy that dignifies the work of caregivers and expands access to quality, affordable care”. Felicia Wong of the Roosevelt Institute endorsed the idea of universal child care as part of a new New Deal.
This idea represented a substantial portion of Biden’s economic plans. The Build Back Better bill — which never made it into law — would have created a national family and medical leave program and a universal pre-kindergarten education, while heavily subsidizing child care and various in-home services. The total price tag would have been in the hundreds of billions of dollars. This big push for service subsidies was mostly defeated in Congress, though some health care subsidies did make it into the (misnamed) Inflation Reduction Act.
In other words, the trend of increasing service costs defined many of our economic debates for a decade. There was just one small problem — by the time we started talking about how to address this trend, the trend had changed.
I’ve been meaning to write this post for a while, but what prompted me to finally do it was when Matt Yglesias posted a very nice chart of health spending as a percentage of GDP. Here’s a version of that chart with two different measures of health spending:
Note that “personal consumption expenditures” includes spending on behalf of consumers by the government and by nonprofits, so this isn’t just household spending on health care — it’s all of it.
We also see the same pattern when we look only at hospital services — the item whose cost went up the most on the Mark Perry chart:
So what we see is that until around 1990, health spending rapidly ate up a bigger and bigger portion of our national income. Then the increase slowed down, but it did go up some more until around 2009. But after that, it leveled off; in 2024, Americans didn’t spend a greater percent of their income on health care than they did in 2009. And in fact, the increase since 1990 has been pretty modest — if you look only at the service portion of health care (the blue line), it’s gone up by about 1.5% of GDP over 34 years.
OK, so, this is total spending, not the price of health care. Is America spending less because we’re getting less care? No. In cost-adjusted terms, Americans have been getting more and more health care services over the years:
What’s happening is that although health care prices have still been going up, they’ve been going up more slowly than before. Here are health service prices relative to the overall price level, as measured with the PCE:
You can see that costs level off in 2009, and then actually drop after the pandemic relative to other costs. This doesn’t mean health care got cheaper after 2020; what it means is that health care prices rose more slowly than other prices did.
If you use the CPI (as Mark Perry’s chart does), things look a little different — medical costs keep rising faster than overall costs during the 2010s, but then slow down quite a bit after the pandemic:
Why the difference between CPI and PCE? Two main reasons. First of all, health care itself is a bigger component of PCE than of CPI, while CPI weights housing more heavily instead. So the fact that health care prices have gone up faster than housing prices means that CPI will show a greater increase of health prices relative to the total. Second, PCE tries harder to adjust for quality improvements. Health care has gone up a lot in quality over the years, and this has been hard to capture with traditional price measures. This is from the conclusion of a Brookings literature review from 2016:
Traditional measures of productivity growth in the health sector most likely understate it, because they don’t adjust prices for substitution from higher to lower cost inputs and because they don’t take account of changes in quality over time…The evidence to date suggests that adjusting health care expenditures for changes in quality leads to a significant reduction in the rise in health prices over time, and, indeed, these prices may even have declined relative to other prices.
PCE has this problem less than CPI does, so it shows more of a cost slowdown.
OK but anyway, what we really care about at the end of the day is affordability — i.e., how much health care an average America can buy. A good way of measuring affordability is to look at median income divided by an index of health care prices — in other words, how much health care the typical American can buy with their annual income.
When we look at this, we see that health care got steadily less affordable until around 1990, then leveled off, and now has been getting more affordable since around 2012:
So overall, health care is probably now more affordable for the average American than it was in 2000 — in fact, it’s now about as affordable as it was in the early 1980s. That doesn’t mean that every type of care is more affordable, of course. But the narrative that U.S. health costs just go up and up relentlessly hasn’t reflected reality for a while now.
Why have health care costs stopped going up rapidly? Some credit the cost control provisions of the Affordable Care Act of 2009 (aka Obamacare). This is from 2019:
March 23, the ninth anniversary of the ACA’s passage, presents a good opportunity to examine its legacy on cost control…Fast forward to December 2018, when [the Office of the Actuary of the Department of Health and Human Services] released the official tabulation of health care spending in 2017. The bottom line: cumulatively from 2010 to 2017 the ACA reduced health care spending a total of $2.3 trillion…[H]ealth care spending in 2017 was $2,000 less per person than it was projected to be. And for the 176 million Americans who have private employer-sponsored insurance, their lower premiums averaged just under $1,000 per person.
Another possibility is that Americans just got tired of paying more and more for health care, and started balking at higher prices. People who made excuses for high American health costs claimed that it was just an income effect — that as nations get richer, they simply spend a higher and higher percent of their income on health care. But as I pointed out, at some point this explanation has to fail, because it can’t be true that health care eventually consumes all of a rich nation’s income, to the exclusion of everything else.
It could just be that Americans were willing to pay more for health care as they got richer, up to a point, but that at some point they said “OK, that’s enough.”
It’s not just health care whose costs have leveled off. College tuition is no longer getting more and more expensive every year. In fact, in inflation adjusted terms, tuition has actually fallen since the pandemic:
Here’s another way of visualizing that same data, and you can see that adding in housing and food doesn’t really change the story:
Of course this doesn’t include financial aid (nor does Mark Perry’s chart, nor do official inflation numbers). Financial aid has been going up, especially at private schools. When you include that, it turns out that private four-year nonprofits are actually less expensive in inflation-adjusted terms than they were in the mid-2000s, even without accounting for rising incomes:
For public schools it’s about the same:
In other words, higher education has been getting more affordable for years, and the decrease in affordability in the late 2000s and 2010s was significantly overstated. The popular narrative that college is getting less and less affordable is wrong, and it needs to change.
Why are college costs going down now? It’s basically a story about demand. College enrollment peaked in 2010 and began to fall:
This enrollment decline happened for every age group of students. It wasn’t just because the number of young people in America plateaued, either; enrollment fell as a proportion of young people.
As for why enrollment rates declined, that’s an open question. My own hypothesis is that college costs rose and the college wage premium fell until a market equilibrium was reached.
It’s not just true that service costs have stopped exploding in America. The narrative that service productivity is stagnant, while manufacturing experiences fast productivity growth, has been flipped on its head since 2008. Manufacturing productivity abruptly flatlined around the time of the Great Recession, while overall productivity has risen:
This implies that service productivity growth has accelerated. And indeed, if you look at specific industries, you see a lot of services where productivity is going up quickly in America:
Now, these changing trends don’t mean that services are cheap and we can stop thinking about service costs. First of all, there are still some services that are getting less affordable over time — most notably, child care. Second, the recent mild increases in affordability for health care and higher education haven’t erased the big cost increases that happened in the 1980s, 1990s, and early 2000s; Americans still pay a lot more for these things than Europeans or Asians do, relative to their incomes. So there’s still probably scope to bring down the costs of health care and college.
But with all that said, the change in the trends in service costs and service productivity mean that our debates about these topics need to change.
First of all, services don’t look as resistant to technological improvement as we once thought. The increased adoption of IT in health care is probably having a big effect. We can probably apply that insight to child care and K-12 education as well. And the introduction of AI into education — and everything else — will probably accelerate the trend even more.
The possibility of technology-driven productivity improvements in service industries also means that we don’t have to resort to expensive subsidies in order to make services both better-paying for workers and cheaper for consumers. Instead, we can encourage technology adoption, and enjoy higher wages and lower prices, just like we did with manufacturing in the 20th century.
(As for where the jobs of the future will come from, it’s looking more likely that professional jobs, rather than care jobs, are the next big thing.)
Falling service costs should also make us more optimistic about capitalism, and about the future of the middle class. For the last decade and a half, a lot of our economic debates have been premised on the idea that the American economy is fundamentally broken, and that life just keeps getting more and more expensive for regular people. That’s looking a lot less true than it did in 2012.
We spent a long time talking about how service costs were eating the world, and I don’t expect that narrative to disappear overnight just because I posted one blog post with a lot of charts. But it’s well past time for our discussions on this topic to start shifting in response to new information.
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Years ago a network scientist named Samuel Arbesman wrote a book about this kind of thing. How there are facts that change constantly — the weather — so we know we need to check the latest. And there are facts that never change — the names of the planets — so we know we don’t need to bother checking on them. But there’s another category of fact he called "mesofacts" (a term which obviously failed to catch on) for facts that change over the span of a few decades and people seem poorly suited cognitively to deal with because nobody puts a Google Calendar reminder for 2035 to check the current consensus on Industrial Policy.
One unclear aspect of this interesting essay is whether it is written from the point of view of the average American household income or the median American household income. In other words, are we talking about households making $106,270 or $80,610? There’s a great gap in disposable income between those two figures.
Also, I see a recurring insensitivity to past inflation. The idea that prices haven’t gone up in the last five years doesn’t mean that the pain has gone away. it just means that the thumb screws are no longer being tightened, after reaching the level of torture in the past. Economists seem to think that the pain of past inflation and (a continuing inflated status) evaporates instantaneously.
OTOH, it is refreshing to learn that both American higher education and American health care are somewhat responsive to market forces.
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How to navigate the future of AI in education and education in AI – EY
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In brief
Artificial intelligence (AI) has the potential to transform teaching, learning, and assessment while easing the administrative workload for teachers. Education departments across the world face the urgent challenge of preparing citizens to live and work safely while effectively engaging with AI. They must also explore how AI can enhance educational equity and improve outcomes. With its capacity to analyze large amounts of data, create personalized learning materials and engage in natural language interactions, AI offers significant opportunities. This potential prompts innovative education leaders to reevaluate their systems and adopt new learning methods..
One of the best ways for people to understand the capabilities, limitations, and ethical use of AI is through regular interaction and application in educational settings. While AI has the potential to transform learning in the long run, several challenges must be addressed in the short term. Strong safeguards need to be implemented before the technology can effectively enhance learning outcomes.
Governments must be ready to address these issues while promoting the ethical development and use of AI in education. They should also focus on building a workforce that can harness its transformative power.
Navigating the future of AI in education and education in AI
How governments can forge more effective and equitable learning systems and develop workforces with future-ready skills.
Chapter 1
AI can transform education by enhancing learning experiences and reducing administrative tasks. However, it is crucial to address equity and ethical challenges to ensure its effective implementation.
AI can transform education by enhancing learning experiences and reducing administrative tasks. However, it is crucial to address equity and ethical challenges to ensure its effective implementation.
A similarly high proportion of parents — 81% doubt whether AI is currently integrated into their children’s curriculum.
Firas Qoussous
EY MENA Government and Public Sector Leader
The shift to online learning during the COVID-19 pandemic paved the way for personalized, self-paced learning, continuous assessment, and the ability to provide quality learning experiences to students. AI-driven tools are a natural extension of this digital learning approach.
The EdTech industry has quickly responded to this opportunity by integrating AI and generative AI (GenAI) into a wide range of teaching and learning tools that support student learning and classroom management. The rise of AI-driven digital education tools has been referred to as the “fourth educational revolution” or Education 4.0, paralleling Industry 4.0.
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A study conducted by EY teams surveyed 3,030 university students across eight regions and found that nearly half had used GenAI tools to support their studies, while an additional one-third expressed a willingness to use such resources. However, there were significant differences at the country level: 68% of students in Singapore and India were already using GenAI tools, compared to just 22% in Japan.
Similar student-led use cases were highlighted in the 2024 Digital Education Council Global AI Student Survey. The survey found that 68% of students used AI for research and 42% used it to check and improve their writing.
AI has the potential to accelerate progress toward Sustainable Development Goal 4 (SDG 4), which aims to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.” AI-powered tools can help tackle some of the critical challenges facing education systems worldwide. However, it is essential to develop and adopt AI tools in a way that genuinely enhances the learning experience without compromising the quality of education or academic integrity.
AI’s positive impact on education will not be equitable unless we address the digital divide. In many emerging economies, students and schools face barriers such as limited internet access, inadequate infrastructure, and a lack of digital skills. Bridging these gaps requires coordinated efforts, including investing in digital infrastructure, ensuring affordable internet and device access, and equipping educators with the skills to implement AI effectively. By addressing these disparities, we can promote AI-driven educational advancements that benefit students globally, creating a more equitable future where every learner has the opportunity to thrive.
Such initiatives need policies that promote equitable and inclusive access to digital technologies and AI. Additionally, these policies should encourage the ethical and inclusive use of AI for the public good.
The UN Educational, Scientific and Cultural Organization (UNESCO) suggests that “to fully unleash opportunities and mitigate potential risks, system-wide responses to the following key policy questions are needed:
Chapter 2
Discover how AI is transforming K-12 education (from Kindergarten through the 12th grade) with personalized learning experiences and AI-driven tools, transforming teaching and boosting student engagement.
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According to an analysis by EY-Parthenon in February 2024, K-12 is the most popular market for AI tool development. The most common use cases in this sector are study tools and virtual tutors, which account for approximately 40% of tool development activity.
AI tutors and teaching assistants provide personalized learning support by adapting to individual needs, learning styles, and preferences in real time. They offer immediate feedback and track progress, encouraging students to take ownership of their learning. By analyzing data from interactions, such as response times and accuracy, these tools suggest exercises, hints, or explanations tailored to each student's understanding. If a student masters a topic quickly, the AI presents more challenging material to maintain engagement.
Many countries are experiencing shortage of teachers, with educators facing increasing workloads and burnout. AI tools can enhance efficiency in various job aspects, giving teachers more time to support student learning. For example, AI can assist with curriculum development, lesson planning, content creation, automated grading, feedback, and performance analytics, allowing teachers to focus on hands-on teaching.
A range of AI-driven learning management systems (LMS) is already available across education sectors, with established providers like Canvas, Blackboard Learn, and Moodle integrating AI features such as personalized learning paths and predictive analytics. This will lead to significant short-term adoption, particularly in K-12, as AI improves teacher workflows. By empowering teachers to become AI specialists, they can guide students in using AI responsibly, fostering an environment that emphasizes critical thinking and digital fluency.
Educational institutions are seeking to deploy AI to automate and streamline business processes in areas such as admissions, finance, human resources, marketing, communications and facilities management. This approach can enhance the experience of both employees and students while potentially leading to cost savings through increased productivity.
Examples include:
AI helps researchers by quickly scanning literature, identifying relevant papers, summarizing findings and highlighting research gaps. It analyzes large data sets to uncover patterns, creates synthetic data, and automates lab work, including experiments and data collection. Additionally, AI reduces the administrative burden of research by automating grant applications, compliance, reporting, and publishing.
Many universities globally are utilizing AI to enhance academic research across disciplines. For instance, Stanford University’s AI Laboratory (SAIL) conducts advanced research in AI, machine learning, and robotics while supporting AI applications in fields like health care, environmental science, and social sciences.
The innovation and adoption of AI in enterprise and continuous learning are rapidly accelerating. Unlike K-12 and higher education, where quality, accuracy, and security are paramount, enterprise learning has lower stakes and easier content creation. Enterprise users are more willing to take risks for potential rewards like cost savings and improved employee productivity.
Asynchronous digital learning solutions can transform enterprise learning and academic courses. These tools convert live course content into engaging, self-paced digital experiences, guided by the course owner. AI analyzes content elements to create interactive materials, such as reflection questions, games, and quizzes, eliminating the need for manual preparation. They can also recommend missing instructional items and produce accessible materials for learners with diverse needs or disabilities.
Chapter 3
The rapid development of AI poses ethical and practical risks for education systems, mainly due to the evolving policy and regulatory frameworks.
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Policymakers and education leaders play a crucial role in mitigating risks and challenges associated with AI in education. They can achieve this by implementing robust policy frameworks. While adopting AI-driven digital tools has the potential to widen the educational divide, it also introduces various risks, including impacts on academic integrity, with concerns about plagiarism, cheating in assessments, and the loss of critical skills. Additionally, there are risks related to inaccuracy, discrimination, bias and data privacy.
Teachers will remain essential in education, even with AI-powered tutors. AI lacks the nuanced understanding and empathy of human educators, making it less effective in addressing complex learning needs. Additionally, AI tools have limitations in content recency and accuracy, often "hallucinating" or fabricating information. Students and teachers must learn to navigate these limitations and fact-check AI outputs. Consequently, AI tutors cannot yet be trusted to educate young children who may not recognize errors or hallucinations.
AI models can function as "black boxes," with their inner workings often hidden or poorly understood. This lack of transparency complicates users' ability to understand the rationale behind decisions related to learning pathways, grading, or student performance, potentially introducing bias or errors. Without transparency and explainability, students, parents, and teachers cannot assess the fairness or accuracy of AI-based recommendations.
To promote widespread acceptance and effective use of AI in education, it's essential to establish protocols for model development that clarify how AI recommendations are generated and validated. Building transparency and explainability into AI models is vital for fostering confidence.
Privacy and data security are foundational for building confidence in AI-powered educational tools, promoting technology that enhances learning without compromising the safety and rights of students. In education, AI tools often rely on large amounts of student data to provide personalized learning experiences, track progress or adapt to individual needs However, collecting and storing sensitive information, such as academic performance and behavioral patterns, raises concerns about who has access to this data and how it can be used.
Educators are concerned that over-reliance on AI tools, particularly GenAI, may undermine students' skills in research, critical thinking, and effective communication. GenAI raises academic integrity issues, as it can produce essays, solve math problems, and complete tests that seem acceptable. Consequently, the focus has often been on prohibiting AI use or detecting AI-generated submissions. However, students need clear guidance and policies on the ethical and effective use of AI.
As schools and universities adopt AI-driven approaches, they should regularly monitor and evaluate outcomes while gathering stakeholder feedback, especially regarding equity. This enables necessary adjustments to enhance effectiveness and address any gaps.
Most teachers have not yet integrated AI into their daily workflows, primarily due to a lack of knowledge on how to do so. They urgently need guidance, support, and resources to effectively use AI tools to enhance learning. A 2024 report by EdWeek Research Center found that the primary reason US teachers have not incorporated AI into their practice is a "lack of knowledge and support”.
To leverage AI in education, teachers and learners need access to digital devices, high-speed internet, and secure platforms. Without universal technology access, the digital divide and educational inequity will worsen, particularly in underserved communities lacking reliable internet and resources for computers. Promoting equitable AI-enhanced education requires investment in high-speed internet, connected devices, and, in some regions, stable electricity.
AI educational tools like adaptive learning platforms and intelligent tutoring systems require significant financial investment for setup, maintenance, updates, and data security. Implementing AI necessitates sophisticated data systems for managing student data, which must adhere to strict privacy standards, increasing costs for software, data protection, and staff training. Many schools, especially in underserved areas, struggle to fund traditional resources, let alone advanced technologies and their security needs.
Chapter 4
Education is a key policy area for governments seeking to improve socioeconomic outcomes. Policymakers play a crucial role in ensuring the safe adoption of AI, to enhance educational outcomes and prepare the future workforce.
Based on the Beijing Consensus, UNESCO developed a set of guidelines and resources to support governments as they plan for AI in education policies, suggesting that policymakers consider providing national guidance around:
The following seven steps outline a comprehensive framework for effectively integrating AI into education.
Countries need robust AI and data governance frameworks for education, with clear guidelines on the safe, ethical and responsible development and use of AI tools in education. The goal is to facilitate AI in enhancing learning experiences without compromising safety or privacy or increasing inequities.
Important areas for consideration include:
To develop strong frameworks and build public trust, consultations should involve ethical AI experts, EdTech providers, the education community, and broader society. Given the rapid pace of technological change and the potential for new risks and opportunities, any AI policy frameworks must be flexible and regularly reviewed and adapted
AI in education has been implemented in a fragmented and experimental way, often lacking a clear institutional or jurisdictional strategy. Education authorities are essential in guiding more deliberate AI adoption by creating a strategic roadmap with a clear vision, objectives, targets, timelines, resources, and responsibilities.
This roadmap would align stakeholders around common goals and support AI initiatives to enhance educational outcomes, equity, and inclusion while addressing ethical and practical risks. A comprehensive plan must ensure that investments in AI innovation are paired with capacity-building efforts to equip teachers and students to use AI safely, ethically, and equitably.
To promote equitable access to AI benefits, governments must invest in digital tools and reliable, high-speed internet in all schools and universities, especially in underserved communities. While some countries have made progress in providing connectivity and devices, many still need improvement. Education systems should also invest in AI software, platforms, and robust data management systems for safe learning data processing. Collaborating with international partners like the Edison Alliance can help share financial burdens, access advanced technology, and adopt best practices for educator training, ultimately scaling digital and AI education initiatives.
Emerging economies have a unique opportunity to bypass traditional educational development models and adopt modern, AI-enhanced systems for greater efficiency and better outcomes. Once connectivity and devices are established, these countries can implement the latest educational innovations from the start, avoiding outdated methods and benefiting from global best practices in AI-driven education.
Education departments must undertake the challenging yet essential task of adjusting school pedagogy and curricula to effectively teach students about AI and equip them with the skills necessary for success in an AI-infused world. This adjustment requires continuous review and updates to curricula to keep pace with rapid advancements in AI technology. By integrating AI literacy into the national curriculum, students will gain a foundational understanding critical for almost every workplace. This curriculum should encompass the ethical and effective use of AI, allowing students to experiment with AI tools in a controlled environment. Such hands-on experiences will demystify AI and illustrate its real-world applications while promoting critical thinking and problem-solving skills essential for deep understanding and long-term knowledge retention.One effective strategy for adapting higher education curricula is to implement interdisciplinary programs that combine technical skills with humanities or social sciences. For instance, courses could integrate psychology with AI or ethics with data science, preparing students to manage AI responsibly in their chosen fields. This approach not only broadens students' perspectives but also equips them with the diverse skill set needed to navigate the complexities of an AI-driven world. By reinforcing the development of complementary skills that AI cannot replace, such as creativity, teamwork, and real-world problem-solving, education systems can foster a more adaptable and innovative workforce ready to thrive in an AI-infused future.
Pedagogy and curriculum reform represent one of the least developed areas of AI-in-education policy. Current efforts have primarily focused on controlling the use of GenAI tools among students, with limited emphasis on teaching their safe and effective use. To adapt to an AI-infused world, educators require comprehensive frameworks, training, and resources that enable them to update their curricula, teaching content, and methods effectively.
Establishing a central government task force on AI in education can expedite this crucial reform. The task force would facilitate collaboration among educators, industry, and EdTech providers to develop curricula, facilities, and digital tools that leverage AI to meet future industry demands. Additionally, it could support research and development (R&D) and innovation in AI pedagogy, curriculum, and administration. While many governments have created national AI-related task forces to support broader AI strategies, few are specifically dedicated to education. In some countries, national digital education or eLearning task forces are beginning to focus on the integration of AI in educational settings, highlighting the need for targeted efforts in this area.
All teachers across the education system, not just those in computer science, urgently require training and support to develop AI literacy before they can effectively utilize AI-driven tools or adapt their teaching methods in response to AI advancements. Comprehensive training programs are essential for equipping educators with the skills necessary to teach students about the safe and ethical use of AI.
These programs will also assist educators in integrating digital technology and AI into their teaching and working practices. To facilitate this, governments can collaborate with the private sector to develop AI-focused teacher training programs, materials, and qualifications. Such partnerships can ensure that educators receive the relevant knowledge and resources needed to navigate the complexities of AI in education, ultimately enhancing the learning experience for students.
The EdTech sector is rapidly developing AI-driven tools for education, and governments play a crucial role in shaping this sector to support national education outcomes. They must establish clear regulations and guidelines to ensure that AI tools are safe, ethical, and effective in improving learning outcomes while promoting equality and productivity. Additionally, governments can support innovation and commercialization by providing funding for research and development in EdTech and AI, encouraging collaboration between educational institutions and technology companies.
Governments should also consider granting controlled access to developers to explore extensive learning data for training AI models. Innovation can be fostered through competitions, pilot programs, and regulatory sandboxes. Continuous monitoring of the educational and societal impacts of new technologies is essential to assess their effectiveness and maintain public trust in AI-driven educational tools.
Learners at every level and stage of their working lives will need training in digital skills and AI to adapt to workplaces transformed by AI. Investing in digital and AI skills will enhance productivity and promote socioeconomic equality.
Additionally, countries will need a pipeline of AI engineers trained in advanced mathematics, statistics, and other data sciences to support the development and application of AI-driven tools. Funding will also be necessary for researchers to conduct empirical studies on the impact of AI on educational outcomes and equity in their societies.
By embracing these strategic recommendations, countries worldwide can prepare their young populations to navigate the challenges of an AI-infused digital future and position them to lead innovation and drive economic growth and development. To fully harness the benefits of AI for education while minimizing its risks, governments are encouraged to adopt a multifaceted approach that includes policy innovation, infrastructure development, curriculum reform, and professional development for educators.
The integration of artificial intelligence (AI) in education presents significant opportunities. To harness its benefits, governments must invest in digital skills training, develop AI literacy curricula, and establish ethical guidelines for AI use. Collaboration between educators, industry, and EdTech providers is essential for creating effective tools and resources. Additionally, a national task force can facilitate innovation and monitor the impact of AI on educational outcomes. Addressing challenges such as data privacy, bias, and academic integrity is crucial to ensure equitable access and prepare students for an AI-driven future.
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Republican Lawmakers Target Affordable Care Act Amid Healthcare Reform Talks – geneonline.com
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Republican lawmakers are reportedly shifting their focus to the Affordable Care Act (ACA) as their next major legislative target, following recent debates over Medicaid. Discussions surrounding potential changes to the ACA have gained momentum, with some members of Congress signaling interest in revisiting provisions of the healthcare law. This development comes amid broader conversations about healthcare reform and federal spending priorities.
In related health news, a new report from the Maha Commission has drawn attention to emerging public health concerns. The report highlights issues ranging from improper use of neti pots to risks associated with certain dietary trends, such as increased consumption of beef tallow. These findings aim to inform policymakers and the public about potential health risks while encouraging further research into these areas.
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Opinion: Congress needs to act to keep health insurance affordable for Alaskans – Anchorage Daily News
The Alaska Legislature recently sent a strong and unified message to Washington, D.C.: Don’t let enhanced premium tax credits expire. These credits, expanded through pandemic-era relief efforts and extended under the Inflation Reduction Act, have helped make health insurance more affordable for thousands of Alaskans. Without congressional action, they will expire at the end of the year, putting access to care and financial security at risk for many families across our state.
At Premera Blue Cross Blue Shield of Alaska, we see the real-world impact of these subsidies every day. They’ve helped small-business owners, independent workers, caregivers, and rural Alaskans afford health coverage for the first time. For a state with some of the highest health care costs in the country, this support isn’t just helpful, it’s essential.
We support the Alaska Legislature’s recent resolution urging Congress to extend these enhanced subsidies. It’s a rare and welcome moment of bipartisan consensus in Juneau, because lawmakers understand what’s at stake. If Congress doesn’t act, more than 23,000 Alaskans could see their premiums rise, sometimes doubling, tripling, or worse. Some could see increases up to fivefold, according to Rep. Genevieve Mina, citing state estimates. That would be devastating.
Without these tax credits, many Alaskans will be forced to choose between health insurance and other necessities like housing, food, or fuel. Others may go without coverage altogether. The result? Delayed care, worse health outcomes, and more financial stress, particularly for rural and underserved communities that already face barriers to care.
The expiration of these subsidies would also shift costs in the wrong direction. More uninsured Alaskans means greater reliance on emergency rooms, more uncompensated care, and increased strain on providers and hospitals already under pressure. Let’s not let that happen to our neighbors and loved ones.
At Premera, we are committed to improving access to affordable, quality care for all Alaskans. That means advocating for policies that put people first, especially those that help reduce the cost of coverage while improving long-term health outcomes. The enhanced premium tax credits do exactly that. They are working, and they should be extended.
We are especially grateful to state Rep. Mina and U.S. Sen. Lisa Murkowski for their excellent leadership on this issue. Their advocacy reflects a deep understanding of the real challenges Alaskans face and a commitment to practical, bipartisan solutions.
This is not a partisan issue. It’s a pocketbook issue. It’s a public health issue. And for Alaska’s families, it’s a matter of stability and peace of mind.
We urge Alaska’s congressional delegation to lead the charge and fight for an extension of the enhanced premium tax credits.
Our communities are counting on it.
Kristin Meadows is general manager and vice president of the individual market for Premera Blue Cross Blue Shield of Alaska. The company and its predecessors have operated in Alaska since 1952.
The views expressed here are the writer’s and are not necessarily endorsed by the Anchorage Daily News, which welcomes a broad range of viewpoints. To submit a piece for consideration, email commentary(at)adn.com. Send submissions shorter than 200 words to letters@adn.com or click here to submit via any web browser. Read our full guidelines for letters and commentaries here.
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The Memorial leaderboard: Who missed the cut? – Golfweek
Five days after winning his first individual title on the PGA Tour, which was his second win following a team victory a month ago, Ben Griffin kept things rolling with a 7-under 65 to kick start his 2025 Memorial Tournament.
Griffin is still 7 under after an even-par 72 during Friday’s second round, but he’s got some company in the form of Nick Taylor, who is also at 7 under.
Here’s a look at what happened on Friday.
Keep up with the latest scores on our official PGA Tour leaderboard.
The Memorial features a 36-hole cut to the Top 50 plus ties as well as any player within 10 strokes of the lead.
The cut line moved from 4 over par to 5 over par after Cameron Young bogeyed No. 18. The top 50 players plus ties (and anyone within 10 shots of the leader) qualified for the weekend.
These players missed the cut this weekend:
How easy is this game? Scottie Scheffler explained his resiliency after a tough double-bogey on No. 10 during Friday’s round.
“If I get up there and make a poor swing because I’m frustrated, that’s going to make me even more frustrated, so I might as well try and make a good swing. It’s really just as simple as that,” he said.
Scheffler is 2 under.
Sam Burns was looking to get caddie Travis Perkins a little something special for him on his birthday on Friday. He did so by shooting a 65 and getting back into contention at the Memorial, meaning the pair will enjoy a later tee time on Saturday. Burns was four shots off the lead as of 4:30 p.m.
“It’s always fun to try to get him a little extra sleep tomorrow,” Burns said of Perkins. “But, yeah, I think other than the rain the golf course being soft I think helps a lot. Typically this place, especially the greens, get really firm and you have to be really precise, kind of going into the greens where you’re landing in. I think if you drove it well and got in position you could be a little more aggressive, and I think we did a good job of kind of attacking when we could, and then trying to fight for par whenever we were out of position.”
Nick Taylor is off to a great start on Friday, going 4 under through the first 13 holes of play to get to the top of the leaderboard at 7 under. Collin Morikawa is also off and running, as he used birdies on two of his first three holes to also get to 7 under.
The 2010 Memorial Tournament winner, now playing in his 16th tournament here, is pacing for the second-best second day of this year’s tournament. After shooting a 78 on the first day, Rose is 6 under par through 15 holes in the second round to climb back to par.
Rose opened the day with a bogey on the first hole but recorded an eagle on the third hole when his 107-yard shot found the hole. Now on the back nine, Rose has notched birdies on five of six holes to improve to 6 under par today, one short of Sam Burns for the best second-round performance so far.
— Columbus Dispatch
Scottie Scheffler made the turn at 33 on Friday, and had pulled within two shots of overnight leader Ben Griffin, but Scheffler had a rare three-putt on the 10th hole, posting a double-bogey to drop to 3 under for the tournament.
Michael Kim, even par through six holes, already is having a better day than what went down during the first round, when he took a quadruple bogey at the par 3 12th hole, dunking his tee shot into the water then making a mess of his next FIVE shots. He shot 78 for the round. Kim, who has become something of a social media sensation because of his tour insider posts on X, found some respite after his opening round in the company of a couple of canine companions. He also planned to soothe his ills with a clubhouse strawberry Oreo milkshake, which he rated 9.5 out of 10.
— Columbus Dispatch
Collin Morikawa won at Muirfield at the 2020 Workday Charity Open and has twice finished second at the Memorial, including last year. On Thursday, he birdied three holes in a four-hole stretch on the front nine and made six birdies in all en route to posting 5-under 67 in the first round, two off the pace set by Ben Griffin. After working through multiple swing thoughts, Morikawa says he’s just flat out crazy, and it didn’t take his new caddie, Joe Greiner, long to reach the same conclusion.
“He’s already called me crazy a lot. And that’s fine. Like, I think golfers are generally crazy. I know I am. I mean, you give me eight weeks off this off-season, you should hear about the amount of things I tried. Just, I mean I had seven different grips, different wraps on my grips, like I was going through it all,” Morikawa said. “You just give me a little too much time and I just go down rabbit holes.”
— Adam Schupak
Tiger Woods won Jack Nicklaus’s Memorial Tournament a record five times, but Nicklaus said he doesn’t expect Woods to chase a sixth title at Muirfield Village Golf Club ever again.
“I doubt it,” Nicklaus said on Tuesday. “I don’t think that he’ll be able to walk this place. I’d love to have him playing again.”
Woods isn’t the only player to deal with an Achilles injury recently. Last February, two-time Masters champion Bernhard Langer tore his left Achilles playing pickleball. Three months after the surgery, he returned to PGA Tour Champions but was allowed to use a golf cart, and in December teamed with his son, Jason, to beat Woods and son Charlie at the PNC Championship in a playoff. Nicklaus was more optimistic about Tiger’s chances to play next year on the Champions Tour once he turns 50 in December.
“When he gets in a cart, he’ll tear it up, absolutely,” Nicklaus said. “If he plays, he’ll win. He’ll win better than 50 percent of the tournaments he plays in, I think. He’s a good player. You all know how good a player he is, but I mean, his work ethic is so good. He likes to work at it. He loves it.”
Round 2 of the 2025 Memorial Tournament will broadcast nationally on Golf Channel starting at 2 p.m. Featured group and hole streaming from PGA Tour Live is available on ESPN+ starting at 7:45 a.m.Watch PGA Tour live on ESPN+
All times Eastern:
Tournament odds from BetMGM as of Thursday:
AccuWeather predicts a high of 70 degrees with partly sunny skies today in Dublin, Ohio. Winds are expected to blow out of the west-northwest at 10 mph. There is an 85% chance of rain and about a 15% chance of thunderstorms.