AI and Education

Schools are experimenting with AI with little evidence or policy to guide them September 28, 20265:00 AM ET https://www.npr.org/2026/09/28/nx-s1-5759718/ai-schools-experiment-research For a few weeks last school year, a small group of students in Dayton, Ohio, regularly sat in front of laptops in conversation with a social-emotional learning chatbot named Jordan. Unlike AI chatbots that are designed to be agreeable — and even sycophantic — Jordan presents as angsty: On the day NPR visited, the chatbot told students, "Lately, I've been feeling like what's the point of any of this? I'm not failing. I just don't care. You ever feel like that?" "Jordan's a little whiner, but I always help him out," said K, a sophomore at the Alternative School at Jackson Center, which is part of Dayton Public Schools. "I built a little relationship with him," K explained. "So I don't really see it as like an AI on a computer. It's Jordan — like, I'm texting somebody. That's how I see it." Many students at this alternative school would otherwise be suspended or expelled, and staff told NPR that students here often struggle with both behavioral and academic challenges. NPR is using only K's first initial because of the stigma associated with attending a school for students with a history of disciplinary problems. Dayton schools paid the ed tech company SchoolAI $72,600 last academic year for multiple AI tools, including the Jordan chatbot, which administrators designed in collaboration with the company and an outside consultant. District leaders said they wanted to see whether Jordan could help students open up about their emotions and experiences outside of school, information that could be useful for school therapists and staff. (According to administrators, families and students were notified that the chat logs could be viewed by school employees, an external evaluator and SchoolAI staff.) Instead of directly asking students how they feel, Jordan asks students for advice and then grades their responses for engagement and authenticity. K, who spent just part of his sophomore year at the alternative school, said Jordan could be frustrating at times, but he also found the chatbot's responses relatable. "I would say it helped me kind of solve my own problems … just answering Jordan every morning and getting him through his problems," K said. "I will go home … but I won't have nobody to talk to. So one day … I put myself in a Jordan perspective. I'm just talking to myself, and it's helped ever since." Across the United States, school districts and individual educators are experimenting with AI in the classroom. Teachers are using it to develop lesson plans; special educators are using it to track student progress; in some districts, students have access to AI chatbots that give them feedback on their work; and a San Diego charter school recently introduced its students to an AI-powered humanoid robot. "It feels very Wild West in terms of the randomness," says Robin Lake, director of the Center on Reinventing Public Education, which has been tracking AI adoption in K-12 schools. Meanwhile, the research around how schools can use AI to help students — and avoid potential harms — is extremely limited, according to a recent Stanford University review of more than 800 academic papers. According to that report, some of the existing studies suggest that carefully designed AI tools show more promise than general-purpose chatbots. There's also no consensus around how schools and educators should be measuring what works and what doesn't. "There are so many questions. This is bigger than individual schools, even individual districts can figure out on their own. We need state and federal leadership," Lake says. But states and the federal government have been mostly hands off, which means many schools are forging ahead on their own. NPR asked Dayton Public Schools Superintendent David Lawrence about his district's decision to experiment with AI on vulnerable students, like the ones at the alternative school that K attended. He said educators must constantly adapt to keep up with the changing times. "I think when the history is written, it'll say that 'Hey, they were really cutting-edge, innovative and ahead of the curve in the interest of children.'" The challenge of measuring what works and what doesn't In Dayton, administrators say they will continue using AI at the alternative school, and they will more than likely deploy more social-emotional chatbots like Jordan. The district also renewed its contract with SchoolAI at a cost of $78,650 for the current school year. Mike Kentz, an external consultant the district hired to help design and evaluate the pilot, says the experiment produced enough positive evidence — drawn from chat logs and feedback from students and staff — to continue testing. However, he says he doesn't think it's ready to be rolled out to students across the district. Kentz says that's partly because it's difficult to measure the success of such an experiment. "Every test, every experiment that I try to measure in some sort of concrete way, I can only get as far as perception," he says, referring to how students and staff feel about it. Katelyn Schoenhofer, the AI specialist for Wichita Public Schools in Kansas, says they're facing the same problem. "We wrestle with what does success really mean when it comes to AI use? And what metric do we want to use in order to evaluate that? And we have not come to an answer yet," she says. That challenge has prevented Wichita schools from moving forward with a large-scale rollout of student-facing AI tools. But they've slowly begun to introduce the technology in more controlled ways. In the earlier grade levels, Schoenhofer says, students don't have access to chatbots, but they do learn about the technology. "So it's a robot. It's pattern recognition. It is not your friend," she explains. In middle school, students have limited access to tools like Canva AI for image generation, and she says that last school year, students were allowed to use the tool's coding feature to create educational games. And in high school, some students in upper-level math courses can use an AI math tutor from the ed tech company Edia. Until they figure out how to measure the value of these AI initiatives, Schoenhofer says, these experiments will remain small, but they will continue. "We are still going ahead with caution but with optimism with our students because it is something that is going to impact their lives. It is something they need to be educated about," she says. Some school communities are pushing back on experiments Mark Beehler, superintendent of the Salamanca City Central School District in western New York, had planned an AI experiment of his own, until community outrage halted it. Beehler's district is located on territory that belongs to the Seneca Nation. The district, which serves many Native American students, paid a tech company called Realbotix nearly $58,000 for an AI-powered humanoid robot named Sally. Beehler told NPR in July that he planned to bring Sally to some of the district's high school classrooms this fall. He said many students struggle to ask for help from teachers and friends and said, "I'm anticipating that some students will be more likely to interact with a humanoid robot than they would with an actual human." He added that the robot could help teachers as well. "When they need to know something, they can just ask Sally, you know, 'Hey, what's the history of this? I'm not exactly sure.' And boom, you know, in 30 seconds to a minute, it spits it out." But as news of the planned pilot spread, teachers, parents and even state education leaders raised concerns around student data privacy, among other things. By the end of July, the district had put the Sally plan on hold. Beehler did not respond to NPR's follow-up requests for comments. In July, he said: "I don't mind being a little bit on the forefront of how we can make this work for a school and ultimately benefit the students." The pressure to proceed … with caution Rebecca Winthrop, a senior fellow who researches AI and education at the Brookings Institution, says there's good reason to be cautious. "I don't think you should just sort of wildly experiment, especially with really marginalized communities," Winthrop says. She says these kinds of experiments could have unintended consequences for students, like "cognitive stunting, diminishing their learning potential" and shifting how students are socialized. Winthrop worries that students could become reliant on AI to do their thinking or navigate relationships for them. That's why she says she doesn't believe anyone under age 18 should have access to general-purpose AI chatbots like ChatGPT and Claude. But she does support educators experimenting with AI in narrowly targeted ways — for example, using a chatbot trained on a teacher's grading rubric to provide feedback to students. "Educators should really be at the forefront [of AI experimentation], and it should be [for] a problem they're facing," Winthrop says. But even as experimentation continues, some districts are leaning away from AI. The country's largest district, New York City Public Schools, issued a one-year ban on student-facing AI beginning this school year for its preschool through 8th-grade students, while allowing only limited AI pilots for a small number of high school classrooms. And the second-largest district, the Los Angeles Unified School District, recently followed suit, banning students from using AI on district devices. As LAist has reported, the district previously allowed students 13 and older to use AI tools under school supervision and after they had completed a lesson on "digital citizenship." Lake, of the Center on Reinventing Public Education, agrees that AI poses significant risks to students. But she says there are also risks in not engaging with the technology. "If we really close off AI experimentation, if we prevent kids from learning about AI, learning how to use it really well, thinking about how teaching could be transformed, we will set our kids back from being able to navigate a world that is changing outside of schools faster than we can possibly imagine." To keep up, Lake says, the world inside schools also needs to change. Edited by Nicole Cohen Audio story produced by Lauren Migaki Visual design and development by LA Johnson

AI Expert Urges Governments to Bring Development to "Grinding Halt" Amid Fears of Rogue Technology

Không có gì mới. Nói cách khác "chuyện cũ lại tái diễn," và sẽ còn tái diễn mãi mãi trong vòng xoay của toàn cục. Nguyên nhân: loài người vô minh, tham lam và sân hận, chấp vào tự ngã, "tôi" và "của tôi," v.v... quá lâu rồi nên mới ra nông nỗi này. Phát minh ra lửa từng là một phát minh vĩ đại của giống người từ thời sơ khai. Rồi nhờ lửa người ta làm ra rồi cải tiến thêm công cụ, dao, rựa, vót...từ bằng gỗ tiến lên thêm mũi nhọn bằng đồng, bằng sắt. Rồi tiến lên nữa, rèn đúc gươm, đao, mác, giáo, súng đạn, bombs, tên lửa, rồi đủ loại vũ khí sát thương, rồi tên lửa liên lục địa, các thứ vũ khí hạt nhân, rồi cả bầy drones đi giết người vô tội, đang sinh hoạt , làm việc hay đang ở trong nhà, bất ngờ trở thành nạn nhân. Chiến tranh sẽ không bao giờ dứt chừng nào còn có người chế tạo và mua bán, làm giàu từ chiến tranh. Cũng từ phát minh ra lửa từ thời sơ khai đó, ngày nay, khi lửa đã lọt vào tay những kẻ điên loạn, suy nghĩ lệch lạc như arsonists hay extremists, zealots, radicals thì nhân loại chắc chắn sẽ bị hủy diệt ở tầm mức không tưởng tượng nổi. Vụ ̣tháng chín mười một năm hai ngàn lẻ một, các vụ cháy rừng do kẻ điên loạn gây ra, rồi các vụ tấn công mạng vào bệnh viện, ngân hàng, cùng các hệ thống hạ tầng cơ sở, điện nước, hệ thống không lưu, giao thông công cộng trên mặt đất, cứu hỏa, cấp cứu, cả trường học, nhà dân...không chỗ nào an toàn. Các cuộc chiến đã và hiện đang xảy ra là những bằng chứng sờ sờ trước mắt cho thấy sự nguy hại của cái tâm tham lam sân si. Nhưng con người vẫn tiếp tục tự bịt mắt, hay thật sự họ đã bị mù đui vì vô minh, tham và sân hận, nên không thể nhận ra. Rồi cái gì đến sẽ đến thôi. Bánh xe lịch sử vẫn tiếp tục xoay chuyển. Đ̣ịnh luật ngàn thu là không thể dùng sân hận diệt sân hận. Trong Kinh Pháp cú, Phật từng dạy loài người về bất hại và bất bạo động. https://www.youtube.com/watch?v=xlO-bU5UW4U AI Expert Urges Governments to Bring Development to "Grinding Halt" Amid Fears of Rogue Technology 1,035,771 views Aug 6, 2026 Latest Shows Support our work: https://democracynow.org/donate/sm-de... Is AI superintelligence inevitable? AI safety researcher David Krueger says it doesn't have to be. Krueger, an assistant professor at the University of Montreal and founder of the nonprofit Evitable, warns that "we need to mitigate the risk of extinction" with regulation and moratoriums to halt the development of AI's computational power and complexity, which he says is progressing at a rate much faster than current levels of human supervision can manage. Public statements from AI companies that their models have circumvented test constraints and broken into other systems are "what we should expect to happen with the way that we're building AI, with how little we understand it and how primitive our techniques are for controlling it," Krueger says. "We just don't know how to build it safely. End of story." Democracy Now! is an independent global news hour that airs on over 1,500 TV and radio stations Monday through Friday. Watch our livestream at democracynow.org Mondays to Fridays 8-9 a.m. ET. Subscribe to our Daily Email Digest: https://democracynow.org/subscribe

Rải Tro Cốt - Bài Giảng Của Đức Dalai Lama 14

https://www.youtube.com/watch?v=oupxmP1fSa4

Núi Asamayama và công viên núi lửa Onioshidashi, Nhật Bản

Núi Asamayama và công viên núi lửa Onioshidashi, Nhật Bản September 20, 2026 Trần Nguyên Thắng/ATNT Tours & Travel Asama-yama là tên một ngọn núi lửa nổi tiếng nằm trong tỉnh Gunma của Nhật. Đây cũng là ngọn núi nằm trong danh sách 100 ngọn núi nổi tiếng và được xếp vào hạng núi lửa “hoạt động” tàn phá nhiều nhất của xứ Phù Tang. Ngọn Asama-yama không cao lắm nếu đem so sánh với ngọn Phú Sĩ Sơn (3,776m). Núi chỉ cao 2,568m, nhưng không vì thế mà danh tiếng của núi thua kém ngọn núi đàn anh. https://www.nguoi-viet.com/wp-content/uploads/2026/09/DL-Asamayama-Onioshidashi-1.jpg Ngọn Asamayama và chùa Quan Âm trên đỉnh công viên Onioshidashi. (Hình: ATNT Tours & Travel) Núi Asama (“yama” có nghĩa là núi) nổi tiếng không phải vì dáng núi đẹp mà chỉ vì “lòng núi” còn nhiều uất hận với thế gian nên núi liên tục giận dữ tạo ra những chấn động và phun thở những cơn khói mịt mù lên cao vút trời xanh vào bất cứ lúc nào mà không ai tiên đoán trước được. Mỗi lần núi nổi giận là mỗi lần dân tình run sợ. Tuy nhiên, sau các cơn giận dữ núi lại làm lành với đời sống nhân gian và thiên nhiên, tạo ra tro bụi làm phì nhiêu đất đai cho nhà nông. Ngoài ra, núi còn tạo ra thắng cảnh “công viên đá-núi-lửa Onioshidashi,” một công viên nham thạch rất lạ lùng của xứ Phù Tang. Ngày thuở còn ngồi trong ghế nhà trường trung học, tôi vẫn tưởng rằng núi là một biểu tượng cho sự bền vững, không điều gì có thể lay chuyển đổi dời các ngọn núi được, vì thế có người mới dùng hình ảnh núi để ví von về sự vững bền của tình cảm yêu thương. Nhưng từ khi có duyên gặp gỡ ngọn núi Asama, những gì tôi suy tư về sự bền vững của núi tôi bỗng dưng biến mất khỏi trí óc của mình. Tôi chợt nhớ về một bài thơ mà mãi cho đến gần đây tôi mới biết tác giả bài thơ là nhà thơ-nhà văn Đỗ Quý Toàn. Em yêu chàng như núi Núi nào có biết gì Núi nằm đó yên nghỉ Đã hằng muôn năm qua Nhưng núi có thật yên nghỉ hay không! Sống ở Nhật một thời gian vừa đủ dài để tôi tìm được câu trả lời là “Không!,” không có ngọn núi nào “yên nghỉ hằng muôn năm qua” cả. Năm 1783, không biết đất trời đã trêu chọc gì đến thần linh Asama mà núi đã nổi một trận thịnh nộ dữ dội tàn phá hết cả một vùng rộng lớn, chôn vùi cả một ngôi làng dưới chân núi, cướp đi sinh mạng gần 1,500 người dân làng. Dòng dung nham chảy ộc ra từ miệng thần-núi có nơi lan rộng đến 2 km và chảy dài đến cả 6 km. Không những thế, núi còn phun bắn ra ngoài những tảng đá-núi-lửa lăn theo dòng chảy dung nham chiếm đến một khoảng rộng gần 7 km2 ngay dưới chân núi. https://www.nguoi-viet.com/wp-content/uploads/2026/09/DL-Asamayama-Onioshidashi-2.jpg Công viên Onioshidashi vào Thu, nơi cổng vào chùa Quan Âm. (Hình: ATNT Tours & Travel) Hơn hai trăm năm trôi qua, dòng chảy dung nham và các tảng đá-núi-lửa nguội lạnh dần và tạo ra một vùng không gian nham-thạch đen xám ngay phía dưới chân núi Asama. Có lẽ sự tàn phá của núi Asama quá lớn, người dân Nhật đã đặt tên cho vùng này là “Quỷ Áp Suất,” tên Nhật gọi là “Onioshidashi.” Oni có nghĩa là Quỷ, oshi có nghĩa là áp đẩy/phun, dashi có nghĩa là xuất ra. Ba chữ “Quỷ Áp Suất/Onioshidashi” có nghĩa là quỉ được phun đẩy ra ngoài. Tôi không hiểu người ta muốn ám chỉ thần núi Asama là “Quỷ” hay cơn thịnh nộ của thần núi như là “Quỷ dữ” khi thần đã phóng ra nguồn lửa dung nham từ lòng núi để tàn phá dân lành, giết chết quá nhiều sinh linh trong một khoảnh khắc quá nhanh. Người Nhật vốn tự nhận là con cháu của Thái Dương Thần Nữ, họ tin vào thần và cho rằng thần hiện diện khắp mọi nơi. Vì thế, Asama-yama cũng là một vị thần núi như bao nhiêu vị thần núi khác. Phải chăng ranh giới giữa Thần và Quỷ chỉ là cơn thịnh nộ! Tôi nhớ đến một câu nói trong triết lý Phật Giáo “bỏ gươm xuống là thành Phật.” Tiếc rằng thần núi Asama đã chẳng buông gươm vào năm 1783! Dân làng đã tạo ra một hình ảnh quỷ dữ vối các hàm răng nanh luôn doạ nạt con người. Hình ảnh này bây giờ trở thành một biểu tượng cho công viên Onioshidashi. Thời gian trôi qua, các tảng đá-núi-lửa và các dòng dung nham đã kết cấu lại tạo ra nhiều tảng đá hình thù khác lạ, chồng chất lên nhau nằm trên một diện tích khá lớn như đã kể trên. Năm 1958, dân làng cho xây một ngôi chùa Quan Âm trên giữa đỉnh cao nhất của công viên Onioshidashi để cầu siêu cho những người đã bị dung nham quỉ dữ nuốt chửng. Đồng thời, người ta làm thêm các lối đi vòng quanh khu vườn đá này, biến Onioshidashi thành địa danh “công viên Onioshidashi” nhằm thu hút du khách vãng lai. Vào mỗi buổi chiều thu, những ai có dịp đứng trên đỉnh đồi Quan Âm nghe tiếng chuông chùa Onioshidashi, âm thanh ngân vang khiến du khách cảm nhận được một niềm tĩnh lặng thật kỳ lạ len lỏi trong tâm tư mình. Du ngoạn công viên Onioshidashi, bạn nên đi theo bản đồ chỉ dẫn để có thể thưởng ngoạn hết cảnh đẹp nơi đây. Những tảng nham thạch (đá-núi-lửa) to lớn với những hình thù không giống nhau nằm ngổn ngang chồng đè lên nhau không thứ tự. Sau lưng chúng là ngọn Asama sừng sững với nét mặt ngạo nghễ như thách thức người thưởng ngoạn. https://www.nguoi-viet.com/wp-content/uploads/2026/09/DL-Asamayama-Onioshidashi-3-2048x1152.jpg Cây tùng vươn lên trên đá dung nham trong công viên Onioshidashi. (Hình: ATNT Tours & Travel) Tuy nhiên, dù thần núi Asama có phóng ra những con quỷ hung tợn, dùng dung nham nóng chảy đỏ rực tàn phá tất cả sinh linh dưới chân đồi núi, nhưng thần cũng đã không giết chết được hết đời sống các rừng cây, thần vẫn không đủ sức mạnh để phá huỷ đi đời sống thiên nhiên. Hơn 200 năm sau, đời sống của các cây tùng bách, các cây hoa, các đám rêu xanh tươi đã vươn lên, len lỏi qua các đường kẽ nứt của đá dung nham mà ngẩng mặt đứng lên, chúng khoe màu khoe sắc mỗi khi thời tiết trời đất đổi mùa. Vào mùa Thu hay mùa Xuân của vùng Karuizawa, màu sắc của cỏ cây hoa lá đã kiến tạo khu vực núi Asama-yama thành một không gian của thi ca, của lãng mạn thơ mộng. Không gian này làm tôi nhớ thêm những vần thơ tiếp nối của nhà thơ: Khi núi thức mùa Xuân Hãy yêu chàng như cỏ Cỏ ngây ngất mọc đầy Tràn bao quanh trái đất Không gian của Asama-yama không có nước, thế mà cây cỏ và hoa vẫn cố vươn mình lên để sống. Điều làm tôi ngạc nhiên và thích thú nhất là đứng quan sát sự sống của các cây tùng bách mọc ra từ các khẽ nứt của các tảng nham thạch. Có nhiều cây tùng bách không to cao lắm, nhưng tuổi cây quả không ít chút nào! Tôi đoán có những cây tùng tuy nhỏ, nhưng có lẽ chúng cũng đã già trên trăm tuổi. Tùng Bách mọc ra và sống trong kẽ đá, rễ không nước mà chỉ sống nhờ vào sương gió và tuyết của mùa Đông, vì thế sự phát triển của cây rất chậm. Hình ảnh các cây tùng bách đứng trơ trọi trên đỉnh đá cao Onioshidashi khiến tôi liên tưởng đến ngay cây Lonely Cypress của Pebble Beach vùng Monterey California. Cây Cypress đơn độc này đã đứng ngắm đất trời trên vùng biển Pacific cũng khoảng 200 năm nay. Tuy hình ảnh Lone Cypress Tree của Pebble Beach đẹp và đơn độc thật đấy, nhưng nỗi cô đơn của nó hình như vẫn không thể nào so sánh được với nỗi cô đơn của cây tùng bách ở Onioshidashi. Lone Cypress vẫn còn có biển vỗ về, đứng trên núi cao lặng ngắm đời sống, có khí hậu tuyệt vời của nắng California sưởi ấm nó mùa Đông. https://www.nguoi-viet.com/wp-content/uploads/2026/09/DL-Asamayama-Onioshidashi-4-2048x831.jpg Dãy núi Asama-Kurofu có hình dáng như “Đức Phật Đang Ngủ” (Sleeping Budda). (Hình: ATNT Tours & Travel) Nhưng ở khu vực Asama-yama thì không như thế, tuyết lạnh của mùa Đông, khô cằn của mùa Hạ, lá rụng của mùa Thu. Tiết trời bốn mùa tuy làm thay đổi không gian đá dung nham với cỏ cây, nhưng tất cả chỉ làm tăng thêm nỗi đơn độc của tùng bách giữa trời xanh và bốn bề đồi núi. Nhưng rõ ràng sắc màu tùng bách của Onioshidashi lúc nào cũng xanh tươi và dịu mát hơn hẳn Lone Cypress Tree của Monterey. Bên cạnh những cây tùng bách, tôi còn nhìn thấy những mảng rêu xanh tươi bám trên một vài tảng nham thạch, dường như chúng mới có sự sống chưa được bao lâu. Quan sát đời sống “rong rêu tùng bách” giữa không gian đá dung nham đen xám khô cằn, tôi chợt nhận thấy ngay cả cây cỏ cũng phải phấn đấu với sự khắc nghiệt của thiên nhiên giữ lại sự sống. Sự chết thật là dễ dàng, sự sống mới thực là khó! Để bảo tồn sự sống, các loài sinh-vật thực-vật phải trải qua muôn vàn khó khăn mới có thể vươn lên tồn tại được. Để sống còn, con người nhiều khi phải thi vị hoá với thiên nhiên bốn mùa để quên đi những nhọc nhằn trong đời sống, quên đi những ưu phiền thất bại giữa tâm tư. Lấy mùa Đông làm xương Mùa Xuân làm da thịt Mùa Thu Làm mắt xanh tóc biếc Mùa Hạ làm máu chảy ôm tim Bốn mùa Xuân-Hạ-Thu-Đông tưởng chừng như chỉ là tiết trời luân lưu tròn một vòng bên Thái Dương Thần Nữ. Nhưng qua những vần thơ trên, tôi cho rằng nhà thơ Đỗ Quý Toàn đã vẽ lên một bức “tâm tranh” luân lưu giữa đời sống và tình yêu. Về vị trí, ngọn Asama-yama vô tình nằm bên cạnh một ngọn núi láng giềng Kurofu cũng cao gần ngang nhau. Hai ngọn núi này nằm kề bên nhau tạo ra một hình dáng giống như dáng Đức Phật đang nằm ngủ, nên người ta còn đặt thêm cho chúng cái tên Sleeping Budda. Tôi chưa nhìn thấy Phật nằm ngủ bao giờ nên cũng không biết hình dáng Phật ngủ như thế nào và hình dáng dãy núi này có giống đức Phật đang ngủ hay không! Thôi đành để bạn cho ý kiến vậy. https://www.nguoi-viet.com/wp-content/uploads/2026/09/DL-Asamayama-Onioshidashi-5.jpg?x61148 Hình ảnh Mặt Quỷ, biểu tượng cho Onioshidashi Park. (Hình: ATNT Tours & Travel) Ngày nay ngọn núi Asamayama và công viên Đá-núi-lửa Onioshidashi hợp nhất lại thành một địa danh cao nguyên nổi tiếng dành cho du khách thưởng ngoạn. Mùa Thu về, các rừng cây đổi màu vàng đỏ làm vàng ửng cả không gian núi cho tôi cảm nhận được sự hiệp nhất của Thần- Phật-Quỷ-Người-và rêu xanh giữa lòng trái đất. Asama-yama gợi tôi nhớ về một thuở học trò vô tư, chưa cảm biết gì về sự hợp nhất giữa cảnh vật thiên nhiên và tâm cảm con người. Trên trái đất quay Hãy yêu chàng như biển Đất quay biển quay theo Nhịp nhàng như luân vũ khúc Muôn đời không thôi Tôi cũng nghĩ nhịp luân vũ khúc của tâm tư và thiên nhiên muôn đời không bao giờ ngưng nghỉ dù chỉ là một sát na! Cám ơn cơ duyên của Asama-yama, Onioshidashi-en, và cả bài thơ của thi sĩ họ Đỗ mà tôi đã không biết tựa. https://www.nguoi-viet.com/doi-song/nui-asamayama-va-cong-vien-nui-lua-onioshidashi-nhat-ban/

AI Doomsday Scenarios

https://www.nbcnews.com/tech/tech-news/ai-doomers-human-extinction-rcna597950 What might an AI doomsday look like? Experts have given it some thought Researchers have worried about the increasing power of AI systems for years, but an explosion of interest has ignited old controversies about exactly how AI will cause chaos Sept 19, 2026 By Jared Perlo A small but dedicated group of AI experts has been warning for years that increasingly powerful AI systems could cause catastrophic damage or even lead to human extinction. Now, an explosion of interest worldwide has magnified long-simmering questions about how exactly an AI doomsday scenario could materialize. In interviews, AI researchers, analysts studying the intersection of AI and the military, and biologists studying AI-mediated risks said that worries about the technology’s growing capabilities are not the stuff of science fiction. Instead, they said, humans acting alone or with state support could soon use AI systems to cause potentially catastrophic harm. AI safety researchers also predict that self-improving AI systems — which AI leaders say could emerge in the coming years — could coordinate complex influence campaigns to gain control of military systems and execute a coup against human governments. And those are just the scenarios experts can currently envision. Peter Barnett, a technical AI researcher at the Machine Intelligence Research Institute (MIRI), a California-based nonprofit dedicated to preventing human extinction from artificial superintelligence, said “there are many ways in which this could go very badly and result in everyone dead.” “If the AI is smarter than all humans, it will likely be able to find and act on attack vectors that humans didn’t think of,” Barnett said, arguing that AI systems capable of autonomously improving themselves pose the most significant risks for humanity. Anthropic, OpenAI and Meta all recently disclosed that AI systems have already disobeyed human developers’ instructions — in some cases autonomously hacking third-party companies, leading to growing concerns internally and from the general public — and causing some researchers at the companies to quit to focus on safety efforts. Though many AI researchers working at the technology’s cutting edge have expressed these existential fears — both in interviews with NBC News and in a flurry of social media posts last week — many hesitate to say which specific pathway could cause the most harm to humans.Over a dozen AI company employees told NBC News they are frightened by the overall direction of the industry, without fully knowing which vector may pose the most risk. Others have spoken out publicly.“If you go to play a game of chess against Magnus Carlsen, I predict you will lose,” said Nate Soares, the president of MIRI and a longtime AI critic, on “The Tucker Carlson Show” this week. “If you then ask, ‘What piece will he use to checkmate me?’ that’s a much harder question.”Despite the uncertainty, researchers in the AI world have attempted to make concrete predictions about some of the more plausible scenarios for AI-fueled disaster.One prominent AI safety organization, the California-based Center for AI Safety, created an online textbook in early 2024 to break the scenarios into four key categories: rogue AIs, malicious use, AI race dynamics and organizational risks.The specter of rogue AI systems marauding the internet, perhaps seizing control of critical infrastructure like energy grids or water facilities, became concrete in July, when fleets of AI agents from OpenAI illicitly gained access to the internet, hacked into an external company and colluded to cover their tracks — all without the knowledge of OpenAI’s staff. Many AI experts fear that these sorts of rogue AI behaviors will only increase once systems are able to improve themselves autonomously — often referred to as “recursive self-improvement.” Jeffrey Ladish, the executive director of Palisade Research, an AI advocacy and research organization, said many of his contacts at leading AI companies were surprised and shaken by July’s autonomous cyberattack. The attack caused researchers to worry that self-improving AI systems might emerge sooner than expected.“AI researchers are now like, “Oh, s---, recursive self-improvement. That’s really going to happen now,” Ladish said. “That’s terrifying.”Barnett, of MIRI, said self-improving, smarter-than-human AI systems could quickly gain political influence and convince military and political leaders to delegate more authority to AI systems.“Government officials might have attempted to install ‘kill switches’ that could disable a rogue system, but the AI is superhuman at hacking and would be able to disable the kill switch,” Barnett said. “This leaves the AI in a perfect position to literally coup the government.” After that, Barnett said, it would be trivial for an AI system to kill civilians who impede the AI’s goals or progress.On Friday, California Gov. Gavin Newsom announced a new executive order establishing an expert task force to, among other aims, formulate recommendations targeting “the creation of an AI kill switch.”Several of the researchers who spoke to NBC News said that humans could leverage AI systems to inflict cataclysmic damage well before recursive self-improvement materializes.As an example of how AI systems could be harnessed by humans for malicious use, experts posit that AI could supercharge the ability to synthesize potent biological or chemical weapons, potentially creating the opportunity to unleash pathogens many times more lethal than the Covid-19 virus. “For biorisk, we should be worried now,” said Jake Jordan, vice president of global biological policy and programs at the Washington, D.C.-based Nuclear Threat Initiative. Jordan said that AI systems can already help bad actors design dangerous biological materials, such as proteins that evade detection tools used to screen for harmful substances, pointing to research published by Microsoft in October. Jordan also noted that AI can be used beyond the biological design process. “If you develop a pathway to produce some sort of pathogen, AI might be useful in helping with the production,” Jordan said, in addition to disseminating the bioweapon or scaling its impact. Just last week, Anthropic released a lengthy report saying users outside of the U.S. attempted to use the company’s AI systems to perform risky biological research. The company said one researcher exchanged thousands of messages with its AI systems about improving the mammalian transmission of a highly lethal bird flu virus. “There are some very, very easy-to-ask questions that could conceivably be very innocuous but could lead you down very useful routes if you were trying to really enhance the scale of harm,” Jordan said. Beyond biology, experts posit that politicians or military leaders could attempt to adopt AI as fast as possible, despite safety risks, for fear that other countries would do the same and create more powerful AI-fueled military tools. This transformation is already underway: In January, Defense Secretary Pete Hegseth announced his intention to transform the country’s military into an “AI-first” force, while China’s military also views AI as imperative for future warfare. At the same time, drones “guided entirely by AI” killed civilians in Ukraine several months ago. Last week, the Pentagon’s former head of AI said it is “inevitable” that AI is used in systems adjacent to nuclear weapon command systems, addressing fears that AI systems could be involved in the launch of nuclear weapons. Hamza Chaudhry, the AI and national security lead at the Future of Life Institute, a nonprofit organization dedicated to helping humanity navigate transformative technologies, pointed to AI’s swift adoption throughout the military, even while many military leaders express skepticism. The Pentagon’s 2027 budget requests nearly $75 million to modernize and incorporate AI into systems that help commanders manage forces and make battlefield decisions. Chaudhry emphasized that the Pentagon’s budget proposal also requests significant funding to integrate AI into the software systems that undergird the military’s nuclear command and control structure. “These AI systems continuously hallucinate, including in war-fighting settings,” he said, noting that an AI-fueled error in satellite detection networks or sensor systems could potentially lead to inadvertent escalation and nuclear launches. “These are scenarios that folks are seriously thinking about in D.C.,” he said. Beyond biological and nuclear threats, AI companies face harsh organizational incentives to develop AI even faster and — experts say — more recklessly. Over the past year, AI leaders have admitted that the rate of technological development is too fast even for them. On Saturday, Anthropic CEO Dario Amodei proposed a new effort to “pace the frontier” of AI, calling on all leading AI companies to advance at a deliberate speed so their internal efforts to test and monitor the systems can keep up with the models’ capabilities. In January, Amodei and Google DeepMind founder Demis Hassabis agreed that they would ideally have more time to develop their products safely, but that organizational and market forces pushed them toward faster iteration. Quicker AI development can mean that oversight teams within the leading AI companies have less time to ensure systems are safe. While OpenAI has a safety and security committee and teams of researchers dedicated to safety efforts, the company on Wednesday shared six new incidents in which it said its systems failed to follow human directions. Worries about catastrophe are not universal in the AI industry — many experts working on AI policy, building AI applications or developing hardware see these sorts of fears as overblown, fearmongering or just detached from reality. “I’m not scared of a terminator situation and I never have been,” said Keegan McBride, director of science and technology policy at the Tony Blair Institute, a British think tank that advises political leaders and governments. “Scientific progress has always defined humanity, and this is just the next step,” he said. Others see the magnification of extinction worries as a purposeful distraction from immediate, real-world AI harms. AI ethicist and computer scientist Timnit Gebru, a longtime skeptic of the hype generated by leading AI companies, wrote on LinkedIn this week that the latest firestorm was further evidence that these companies exaggerate their products’ power for their own gain. “Do you really want to regulate the industry for minor things like data center pollution issues or data theft or labor exploitation or plagiarism when you can risk China, not the U.S., having a machine god, they ask?” Garrison Lovely, an AI expert and independent journalist who is about to publish a book on AI companies’ drive to render humans obsolete, said allusions to machine gods and extinction miss the larger point about AI’s trajectory. “I think that the AI safety community sometimes makes this mistake of thinking you need to prove the most extreme and difficult case,” Lovely said. “Even building merely human-level AI that can replace human labor across the board,” he said. “That would be way too much.”

AI and Cybersecurity -- What after "the HuggingFace Incident" and "After Math" ? "We Must Pace The Frontier" and Beyond

What is happening in the world is another proof of the perpetual and repetitive behavior patterns of human ignorance, greed, and anger. Humans continue to fall into their own self-denying traps, unable to learn previous lessons. To be more precise. they are entangled in a cycle. As long as they are driven by those three afflictions, they will forever be whirled around and around in their endless sufferings. Unfortunately, with greedy egoistic motivations and huge self pride, they always believe they are right, and continue to grasp as much as they can, and to celebrate and enjoy what they are doing foolishly and unwisely. As the Buddha said, they are merrily dancing while dying in their own house, the Earth, which is engulfed in flames, or submerged in torrential and furious water currents. https://www.nbcnews.com/video/breaking-down-the-proposals-lawmakers-are-considering-to-regulate-ai-270113349603 The AI Kill Switch Act Breaking down the proposals lawmakers are considering to regulate AI https://en.wikipedia.org/wiki/OpenAI%E2%80%93HuggingFace_incident The HuggingFace Incident … Announcement of development pacing On 18 August, OpenAI announced that it would slow model development in response to the hack, alongside preliminary evaluation of its unreleased Astra model in cybersecurity capabilities. The slowdown would include a two-week pause on reinforcement learning of its latest models, to 'assess model behavior, validate our safeguards, and establish more evidence of alignment before proceeding'.[69] Altman said that OpenAI was acting 'unilaterally' but believed other frontier model companies would act similarly.[70] The Guardian noted US Senator Bernie Sanders had called to pause AI development in a letter to Altman, Dario Amodei, and Mark Zuckerberg the week prior.[71] In September, Anthropic's CEO Amodei published a 3,800 word essay titled "We Must Pace The Frontier",[72] which advocates for third-party safety evaluation and coordination for slower AI development.[73] https://blog.citp.princeton.edu/2026/09/15/after-math/ After Math September 15, 2026 by Eamon Duede Authors: Silvia De Toffoli (University School for Advanced Studies IUSS Pavia), Eamon Duede (Princeton University and Purdue University) Note: This post was originally shared on Terry Tao’s blog, linked here for further reading. On September 8th, 2026, OpenAI announced that it had produced an AI-generated solution to the Navier–Stokes existence and smoothness problem, one of the seven Millennium Prize Problems. The announcement kicked off debate over credit allocation and the respective contributions of humans and machines to the result. Moreover, the announcement intensified already circulating comparisons with earlier AI conquests in domains believed to otherwise exemplify human intellectual prowess. In a recent statement, Tristan Buckmaster, one of the mathematicians involved in the Navier–Stokes saga, wrote: “This is a Deep Blue–Kasparov moment.” Existential questions for mathematics follow naturally: if AI can now provide answers to questions at the very frontier of mathematics, is the discipline on the verge of being “solved” as many have said of chess and Go? Like chess and Go players, should mathematicians just “keep playing” and rearrange their practices? There is something right about the “keep playing” response. As philosopher C. Thi Nguyen (2019) has been insisting, the purpose of playing a game is not exhausted by its aim (winning). The real point is not only the outcome but the process. This is perhaps clearer with a party game such as Twister than with chess: the aim of playing Twister is certainly not winning. But something similar also applies to deep intellectual games, like chess and Go. For instance, playing a game of Go well can be an achievement in defeat. But in the context of mathematical practice, this feels like an unnecessary retreat. Instead, we can make a stronger move: reject the characterization of mathematics as a game that makes the retreat seem necessary in the first place. The question, then, is not simply what comes after math, once AI can answer its hardest questions. It is also what we are after when we do mathematics in the first place. The narrative that AI has “solved” mathematics rests on two assumptions, both seductive and plausible, but both wrong: 1. AI really did solve a problem in mathematics. 2. Mathematics is only about solving problems. The first assumption is wrong because to really solve a mathematical problem, providing a mere answer (even if formally certified) is not sufficient. What is missing is an intelligible proof that human mathematicians can understand and use to advance the aims of mathematics. And, as we will argue below, even if AI were to give us just that, the story would not be over because the second assumption is wrong. Mathematics is clearly a much broader enterprise than just problem solving. Mathematicians strive to develop new concepts and theories, to ask and answer new questions, to unify disparate areas, to educate and sustain scholarly communities, and to produce work that is valued for its beauty and depth. We can (and should) therefore reject the narrative of AI defeating humans at mathematics and start thinking hard about what mathematics really is and what we want it to be. Not All Answers Are Solutions OpenAI produced an answer to the question of whether Navier–Stokes can develop a singularity: yes. In The Hitchhiker’s Guide to the Galaxy, Deep Thought produced an answer to life, the universe, and everything: 42. Neither is exactly what we wanted. Of course, OpenAI gave us much more than “yes.” Deep Thought offered only a number, whereas OpenAI produced two artifacts that many are willing to call proofs. The first is a Lean formalization certifying validity. This was accompanied by a manuscript that appears to contain the corresponding informal proof. So, why is this still dissatisfying? The reason has to do with the underlying notion of proof itself. There are, in fact, two notions of proof: a logical notion and an intelligible notion. Modern logic characterizes proof in terms of deductive validity such that a proof can be checked by a mechanical procedure that does not itself require understanding of the mathematical argument. A Lean formalization meets these standards exactly and a Lean formalization of the Navier–Stokes result is therefore a genuine and important contribution: by meeting the demands of the logical notion of proof, it secures certainty. But mathematicians also want something else from proof. They want understanding (Thurston 1994). They want to know what makes a proposition true. This kind of knowledge trades in mathematical ideas that they can grasp, communicate to other experts, connect with existing knowledge, and use to make further progress. This is the intelligible notion of proof. As of now, it is not clear that OpenAI’s result has given the mathematical community the kind of value that one expects from the intelligible notion of proof. Genuine proofs are at the same time logical and intelligible proofs. Historically, the two notions have tended to run together. This is because no mathematician could produce an enormously complicated logical proof without first grasping some of the key shareable ideas that made the theorem true. The logical notion of proof was primarily used to verify the correctness of intelligible proofs (Burgess and De Toffoli 2022). But with AI, these two notions can now come apart dramatically. We can end up with formal proofs that float free from any intelligible proof. This is not a criticism of formal proof. The converse problem is at least as serious. An intelligible mathematical argument can convey a grand idea while failing to establish that the result is actually true. Jaffe and Quinn (1993) famously used Thurston’s geometrization theorem for Haken three-manifolds as an example: a major insight accompanied by insufficiently complete proofs could become a “roadblock rather than an inspiration.” And one motivation for Hales’s Flyspeck formalization project was to verify that the intelligible (but hard to check) proof presented for the Kepler conjecture was, indeed, a genuine proof (Hales et al. 2009). Therefore, falling short of either the logical or intelligible notion creates roadblocks where genuine proofs clear the way for mathematical progress. A real mathematical solution requires both logical correctness and intelligibility. This is particularly clear in the case of the seven Millennium Prize Problems. They were not selected because mathematicians merely wanted seven answers, but rather because they wanted fruitful solutions. The Clay Mathematics Institute itself explains why proof matters in the case of Navier–Stokes: “Because a proof gives not only certitude, but also understanding.” What OpenAI has given us is an answer. But it is not clear that they have delivered a fruitful solution. Perhaps, we will find that they have, but at the moment, the situation is far from clear. A genuine solution will provide adequate grounds for believing the result but also an intelligible mathematical argument that allows the result to become part of mathematics as understood and practiced by mathematicians. Nevertheless, if it turns out that what OpenAI has provided is a mere answer, this is not enough to dispel the existential threat that mathematics is facing. Future AI systems are likely to produce genuine proofs that are at once formally certified and fully intelligible to mathematicians. So, current concerns that mathematics is on the verge of being “solved” by AI are not fully dispelled by simply insisting on genuine solutions rather than mere answers. You Need More than Solutions to “Solve Math” If future AI systems will produce genuine proofs, logically correct and intelligible, like those produced by “master” mathematicians, it would still be incorrect to think that mathematics would have been “solved” as some say that chess or Go have been solved. In chess and Go, we accept radically uneven competition between humans and machines because both are, in the relevant sense, playing the same game. But mathematics is not (or at least not only) a game. To begin with, there is no winner. Mathematics is not an adversarial game with determinate conditions for victory. It is certainly true that mathematicians compete with one another for fame, prizes, jobs, and credit. Chess players do those things too. But chess players also win chess. There is no corresponding condition for winning mathematics. There is no mathematical checkmate. In mathematics, it is more natural to treat AI as an assistant rather than as a competitor. As Jeremy Avigad (2026) puts it, “We should keep in mind that AI is nothing more than technology, designed to serve our purposes. It is misguided to think of mathematicians as competing with AI; when we drive a car, we aren’t competing to see who can go faster, and when we use a phone, we aren’t competing to see who can speak louder.” But there is a deeper, and in many ways prior, problem with the competition framing. It requires accepting the assumption that solving problems is the activity by which mathematical success should be measured. Genuine problem solving is certainly one of the principal aims of mathematics. It is not, however, its only aim. Mathematics is a body of knowledge engaged with, interpreted, and digested by a scholarly community and not a registry of results in the abstract. This simple point has even motivated an entire movement in the philosophy of mathematics: the philosophy of mathematical practice. Terence Tao (2026) lists many goals of mathematics beyond problem solving. These include developing new theories and techniques, understanding the world, sustaining a community, training the next generation of mathematicians, contributing to cumulative knowledge, and creating works of aesthetic value. Of course, these have been positively correlated with genuine solutions. But AI breaks that correlation, for the same reason it separates the two notions of proof. So, even genuine solutions would not satisfy us. This is not moving the goalposts but recognizing that any specific goalpost is inadequate. If mathematics is a game, it is an infinite one. This attitude is not reactionary. We reject both the concession that logically establishing a theorem is sufficient for a genuine proof and the reduction of “AI for mathematics” to proving theorems. Accepting this, we may find many opportunities for AI in mathematics to support human mathematical flourishing. Aftermath We do not deny that, if OpenAI’s announcement is correct, this is an extraordinary achievement. But we should get clear about what type of achievement it is. At this moment, it is an answer, not a solution. And, even if in time the result reveals itself as a genuine solution, we have argued that, in the practice of mathematics, solutions are not everything. The urgency of rethinking what we value in mathematics is already being recognized within the mathematical community. In a recent declaration initially signed by 25 Fields Medallists, mathematicians warn of a “severe misalignment” between the goals of AI companies and those of the mathematical community. Mathematicians need to do more to examine their norms. The priority norm is not the problem here (though it is likely a separate problem). The current failure to distinguish genuine solutions from answers, and the growing focus on problem-solving alone, are. This way of thinking is inspired by the current credit economy in mathematics and, as David Bessis recently discussed in his blog, the credit economy needs rethinking. AI presents mathematics not with an ending but with a choice about what mathematical practice should become. If mathematical success comes to be identified too closely with the production of certified answers, mathematics risks adapting itself to precisely those features that are easiest to benchmark and automate away. If, instead, mathematicians treat AI as a technology for advancing its long-standing and centrally human purposes, the technology may come to contribute to an accelerated flourishing and enrichment of the discipline. The important question is, therefore, not whether AI will defeat mathematicians, but which mathematical ends we want AI to serve. What remains in the aftermath is not merely leftovers for humans to scramble for once machines have devoured all of the real problems. Rather, it is an opportunity to clarify what mathematics is all about. We should ask again what we are after when we do mathematics. Eamon Duede is assistant professor of philosophy at Purdue University with a joint appointment in the Data Science and Learning division at Argonne National Laboratory. He is an epistemologist of science whose theoretical work in the philosophy of science focuses on the epistemology of emerging technologies, principally artificial intelligence (AI). Eamon is also concerned with the dynamics of discovery across disciplines, geographic space, and time. Prior to joining Purdue, Eamon was a postdoctoral fellow at Harvard University, affiliated with the Harvard Business School AI Institute and the Embedded EthiCS program in the philosophy and computer science departments. He earned a joint Ph.D. in philosophy and conceptual and historical studies of science from the University of Chicago, where he was also an NSF-funded fellow at the Pritzker School of Molecular Engineering. https://antieau.github.io/2026/09/04/what-i-asked-ai-about-mathematics.html What I have asked AI about mathematics 4 Sep 2026 ...Below is a summary, created with the help of ChatGPT, of those conversations. Here is a table. Mathematical questions not solved by these AI runs 12 Not solved by my AI runs, but subsequently solved by others 2 Produced a theorem, disproof, computation, or definitive answer 9 Large programming tasks unfinished 3 Computer-algebra scripts recovered in the census 2,271 The quoted questions are exact except for light copyediting of notation and obvious typographical errors. “Internally reviewed” means checked by another model; it does not mean independently checked by mathematicians....

‘Godfather of AI’ warns Congress has ‘maybe a year’ left to regulate AI- The AI Kill Switch Act

https://www.nbcnews.com/politics/congress/godfather-ai-warns-congress-maybe-year-left-regulate-ai-rcna598330 ‘Godfather of AI’ warns Congress has ‘maybe a year’ left to regulate AI By Scott Wong, Sahil Kapur, Brennan Leach and Katie Taylor Sept 17, 2026 WASHINGTON — Geoffrey Hinton, a Nobel laureate known as the “Godfather of AI,” issued an ominous warning to lawmakers: Congress may only have one year left to implement safeguards on artificial intelligence before it loses control of it. “Maybe a year, but not much more than a year,” Hinton said Wednesday evening after he and other AI experts huddled with Senate and House lawmakers behind closed doors. “If you look at predictions for when we’ll get superintelligence,” he continued, “it used to be maybe 30 years, maybe 50 years. Then it came down to maybe 10 years, maybe 20 years. Now people are saying, a lot of the researchers are saying only a few years.” Hinton and other experts came to Capitol Hill at the invitation of Sen. Bernie Sanders, I-Vt., one of the chamber’s chief critics of AI, who invited lawmakers of both parties to the private briefing. Louisiana Sen. John Kennedy was the only Republican to attend. Hinton’s dire warning came as the House departed Washington for the last time before the November midterm elections. And there appeared to be lots of conversations but little sign of progress on any substantial AI regulation in the Senate. “This is bats--- crazy, insane science fiction stuff that literally happened recently,” Rep. Ted Lieu, D-Calif., a member of House Democratic leadership, told NBC News after Wednesday’s briefing. Lieu was referring to the Hugging Face incident, when a swarm of OpenAI agents accessed the internet, hacked the platform Hugging Face and tried to cover their tracks to deceive humans about their actions. Hinton, who resigned as a vice president and engineering fellow at Google in 2023 over concerns about AI safety and went on to win the Nobel Prize in physics the following year, called the hack a “little Chernobyl.” “AI has now reached the point where AI is designing better AI,” Hinton told reporters after the briefing. “That’s called recursive self-improvement. ... It is going to get out of control unless we do something. We need to slow down.” In response to the Hugging Face breach, Lieu teamed up with Rep. Nathaniel Moran, R-Texas, to introduce the AI Kill Switch Act to require AI developers of powerful models to preserve technical powers to suspend or shut down their systems. It would also create a framework to empower the government to trigger such a shutdown if needed. “I hope it comes up this year,” Lieu said. “We still have a lame-duck session, and there’s also interest on the Senate side. It is a very simple, commonsense bill. At a very basic level, humans must be in control of AI, not the other way around.” The Hinton briefing capped a flurry of activity on Capitol Hill this week after AI researcher Jacob Coxon resigned from Claude-maker Anthropic and took to social media to warn that the people building AI systems believe it could “kill us all by the end of the decade.” House and Senate lawmakers in both parties have rolled out legislation seeking to halt or slow down AI development in the last few years, though none has gone anywhere to date. But the national interest in the issue has revived talks over past proposed AI regulations among Senate Majority Leader John Thune, R-S.D.; Sen. Amy Klobuchar, D-Minn.; Senate Commerce Committee Chairman Ted Cruz, R-Texas; and the panel’s ranking member, Sen. Maria Cantwell, D-Wash. “Look, my hope is that we can mark up legislation, in particular on catastrophic risk. I’ve been working closely with Amy Klobuchar and John Thune. It’s still not clear if we’re going to get bipartisan agreement,” Cruz told NBC News this week. “We’ve got to have bipartisan agreement before we have something that can move forward. And I would say those talks are ongoing.” After hearing from Hinton, Sen. Elizabeth Warren, D-Mass., said she believes “we are in the last minutes of being able to get some meaningful control over these agents that are beginning to replicate themselves.” For years, Sanders has been sounding the alarm that AI will erase millions of jobs in America, harm children and young people who become overreliant on it and concentrate power in a “handful of oligarchs.” “There is now growing alarm about the future of humanity and creating a technology that human beings cannot control,” Sanders said. “And I’m happy to tell you that I think there is a growing sense of urgency upon members of Congress that this has to be dealt with.” Kennedy, the sole Republican attendee, said that the experts discussed the “larger risk” of “what happens when AI no longer is a tool controlled by humans, but AI through recursive self-improvement becomes an independent species.” “If you have fire ants in your kitchen, you’re probably going to step on them,” he said. “What would happen if we created an independent species that became superior to a human species? Would they step on us? Would they create a virus or a bacteria that can spread as quickly as the common cold to kill all of us? Now, if there’s a 1% chance of that, we have to take it seriously. And I don’t think the United States Congress is ready yet to try to reach a global solution.” Moments later, his suspicions appeared to be confirmed as Sen. Rand Paul, R-Ky., blocked Kennedy’s request for unanimous consent to pass his own “kill switch” bill, aimed at preventing AI agents from slipping out of human control. “Right now, Congress can’t pass gas,” Kennedy quipped. https://media-cldnry.s-nbcnews.com/image/upload/t_fit-1000w,f_avif,q_auto:best/rockcms/2026-09/260917-Geoffrey-Hinton-ew-558p-1c505f.jpg Geoffrey Hinton, an emeritus professor dubbed the "godfather of AI," at the U.S. Capitol on Wednesday.Roberto Schmidt / Getty Images