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‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field

‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field ‘The reality, for better or worse’: Columbia comp sci students and faculty grapple with AI’s disruption of the field A field that once seemed like a direct path to stable, lucrative work is becoming less certain under AI, students and faculty told Spectator. By Ria Vasishtha and Arjun Menon May 3, 2026 Shanying Liu / Deputy Illustrations Editor Asia Genawi, SEAS ’29, first encountered artificial intelligence during her sophomore year at her high school in Indiana. Back in 2023, policies on AI varied widely—even within the same district—and some schools had no guidance at all. As Genawi began to see the effects of AI trickle into her classroom, she turned to guidance from her home state’s Department of Education, which she said she found “outdated and inaccessible.” Genawi spent the rest of her high school career dedicated to the issue, including writing a 15-page memo exploring varying AI policies across Indiana schools, which she sent to every Indiana state senator and representative whose contact information she was able to find. She later helped draft a bill that would have required public high schools to establish and share their own AI policies with students in an accessible format. But with so many other bills already awaiting referral, hers never made it to committee. When Genawi arrived at Columbia to study computer science, she found that the gaps she had spent years trying to address in Indiana had followed her there. Many students and professors were also grappling with what AI meant for the field. Across Columbia’s undergraduate schools, computer science has become the most popular major—accounting for around 11 percent of degrees awarded in Columbia College, 32 percent in the School of Engineering and Applied Science, and 12 percent in the School of General Studies in 2024. While the number of computer science majors in SEAS grew from 166 to 173 during the 2024-25 academic year, the total number across the three schools fell around 4.5 percent from 393 to 375, driven by declines at Columbia College and General Studies. At Barnard, it has grown to become the second most popular major as of 2025, up from third the year prior. The number of degrees awarded have grown fivefold since 2016. Faculty members and students in the department told Spectator that the surge in the major’s popularity has been driven in large part by its apparent promise of a secure, well-paid career path. However, they noted that the recent rise of generative AI has compromised the sense of stability that once defined the field, even as interest in technical skills among students persists. According to data from the Federal Reserve Bank of New York in 2024, out of 74 majors tracked, computer science had the fifth highest unemployment rate among majors at 7 percent, while computer engineering had the second highest at 7.8 percent. “Anecdotally, people are moving away from CS as a major,” Daniel Bauer, a senior lecturer in the computer science department, said. “They’re still taking some of our classes, right, because they think they need that, but they’re instead majoring in other things.” Bauer described a field that had shifted from what he called a “nerdy outlier discipline” to one that “everyone needs,” a sign that technical skills have become a baseline expectation across industries with the emergence of AI. “A lot of people thought, ‘Oh, it’s a guaranteed path to a stable income. You get a six-figure job right out of your undergrad,’” Bauer said. Now, companies may see AI as a way to reduce demand for entry-level programmers, especially in what he calls “code monkey jobs,” roles where a large number of employees are “just writing out code nine-to-five.” Chris Murphy, a senior lecturer in the computer science department, described the current moment as the convergence of two forces: the downturn of the job market and generative AI coming onto the scene. “Things kind of started to really pick up in 2014, 16,” he said, recalling the years after the weaker 2010 market. Murphy added that this was also a period where “students were getting more experience outside of class than they were inside of class” through internships, jobs, and side projects. Murphy suggested that the earlier momentum helped make computer science feel like both an academic program and a reliable pathway into work. That feeling is harder to sustain now as the industry reconfigures, which is a shift that students are seeing firsthand. Rebecca Yu, SEAS ’27, said that during a recent internship in Big Tech, she saw that “every single tech company was racing to integrate” large language models. She added that her manager said her intern class was the first to complete their assigned projects, which she attributed to the increased efficiency that comes with AI. Frank Liu, SEAS ’29, said that with AI lowering the barrier to coding, companies now expect everyone to write code. “A lot of companies outright say if you’re not using coding in your job, you might get fired for not being productive enough,” Liu said. Yu similarly expressed that students increasingly have to accept AI being a part of industry workflow, adding that many also “make use of it to maximize their productivity.” Richard Li, CC ’28, described a “franticness” among his peers as the pace of change accelerates. He explained how “some new tool” is released regularly, noting that tools rise and fall in prominence within weeks. He has come to believe that he doesn’t need to “match that speed all the time” and keep up with every development. Li has learned that AI tools allow him to “take a breath” and “get back into the loop much easier than before” when he needs to. While some companies specifically target Columbia when hiring, sending representatives to campus career fairs and recruiting large numbers from Columbia, a computer science degree cannot be treated as a static credential, Yu described. “You can’t just get your degree and stop learning after that. You have to always be learning,” Yu said. “That is something you basically have to expect for your job.” AI has not only affected students’ decisions to major in computer science, but also reshaped how the subject is taught. Across departments, faculty members no longer treat work done outside the classroom as a reliable measure of understanding, shifting instead toward in-person exams, quizzes, and attendance checks. While homework once made up as much as 60 to 70 percent of a student’s grade in computer science classes, Murphy said that breakdown has since flipped, with exams and quizzes now accounting for the majority. “The assumption—especially among pessimists—is that they’re using it to do their homework,” Murphy said. “They take the homework assignment. They put it into generative AI. Out comes the solution. Submit solution. The end.” Murphy said that faculty members ranged in their responses from fully prohibiting AI use to actively teaching students how to effectively work with AI. He said he shifted his approach this year after his teaching assistants called his belief that students weren’t using the technology “naïve,” and now permits students to use AI on assignments. His surveys of students in his introductory classes have told a more complicated story than the one so-called pessimists offer: Around 60 to 70 percent of students who reported using AI said they used it to have concepts explained to them, to clarify assignment instructions, to generate test cases, or to create practice questions. “Those are all ways that you might have had a tutor in the past to do that, and now you have this AI essentially as your tutor,” he said. Bauer has taken a different approach, teaching students how to use AI productively without sacrificing the core principles of the discipline. “People who are trained to actually use AI tools productively, while being in charge of designing the overall project, will be very much in demand in the next couple of years,” he said. Over the past year, a working group of computer science faculty has been redesigning the introductory and intermediate programming sequence to integrate generative AI as both a subject and a tool, representatives from SEAS wrote in a statement to Spectator. The effort is “coordinated” across the department, “not course-by-course,” with a systematic assessment of how AI integration is affecting student outcomes underway to shape the next round of changes. The goal, the department explained, is for students to be able to “read, verify, and reason about code, whether they or a model wrote it.” Tony Dear, senior lecturer in the computer science department, is piloting individualized AI feedback in a discrete mathematics course, while a machine learning course is also testing a Socratic AI dialogue system designed to “guide inquiry rather than supply answers,” the statement reads. Beyond individual courses, SEAS funded seven cross-departmental faculty projects in generative AI this past academic year, spanning biomedical engineering, chemical engineering, industrial engineering, and computer science, according to the statement. This phenomenon extends beyond the computer science department. SEAS’ new AI minor, which it announced in November 2025, reflects the University’s attempt to adapt. The minor is specifically designed for noncomputer science majors and aims to provide “essential AI knowledge” while emphasizing practical and responsible use across disciplines, according to the SEAS website. At the center of the minor is AI in Context, a course taught by a team of faculty from the departments of computer science, applied mathematics, philosophy, music, literature, and the Writing Center, the representatives told Spectator. Bauer described it as targeted at students who want to bring AI into fields like economics or biology, rather than as a path into software engineering itself. At the graduate level, SEAS announced a new Master of Science in artificial intelligence in February, with the inaugural cohort starting in the fall. While recognizing how AI has helped them navigate coursework, students also described its rise as isolating, even among members of the Application Development Initiative, one of Columbia’s largest computer science clubs. “As people start to ask AI for questions that they would normally ask students and members, it starts to isolate people” Li said. Alexa Kafka, BC ’27, echoed Li’s sentiment, pointing out that computer science has always been a collaborative discipline with code reviews and pull requests, even as AI makes independent work easier. Despite this, Kafka noted that she hasn’t been to office hours “in at least a year.” Bauer added that faculty are exploring long-term solutions to the assessment problem. “One of the things that we’re trying to do at the department or school level is to maybe move towards computerized testing facilities,” Bauer said, referring to ideas in the department to revitalize computer labs as an alternative to pen-and-paper exams. “We have to accept that this is the reality, for better or worse.” But more exams, students say, does not mean better learning, nor does it reflect how computer science is actually done. “Code is so variable and can be approached in so many directions, there’s never just going to be one correct answer. There can be multiple optimal solutions,” Kafka said. Students also expressed concern that the shift toward exam-heavy grading pulls focus away from the applied, project-based work that better reflects both discipline and industry expectations. ADI has tried to respond more quickly than the curriculum can. Through a vibe coding workshop this past semester, club members said they wanted to help students understand not just that AI exists, but how to use it deliberately. “Vibe coding” refers to the practice of prompting AI to write code for a task or project, and has become widespread enough that ADI felt the gap in formal instruction was worth addressing, according to Sophia Huang, BC ’29. The workshop introduced students to the concept of context engineering, which Shaina Sahu, SEAS ’27, described as not just writing a prompt, but optimizing “the rest of the relevant information that you would feed into the model.” Without that, students said that AI-generated code can fail at scale or introduce difficult-to-detect bugs. Genawi said the shift toward AI has changed what it means to be good at computer science. “I think the shift has kind of gone towards what can you create and what can you do, instead of, what do you know,” she said. Indeed, during ADI DevFest, its annual hackathon, Li said more teams are trying to complete their projects than in years past. While sign-ups have historically outpaced submissions, Li said this is beginning to change because teams “have a tool that completes the vision for them.” While many students see AI as an equalizer that lowers the barrier to entry for coding and technical work, Murphy said it also creates new equity concerns inside the classroom around who can afford stronger tools and who already knows how to use them. “The equity issues I worry about are students who have access to paid versions of things versus free versions of things,” he said. Although popular AI models like ChatGPT and Claude have free versions available, both have paid models that can reach over $100 per month, which output different qualities of code. Murphy also pointed to differences in prior exposure to AI literacy itself. “Students who go to high schools or K-12 education, where they’re taught AI literacy, prompt engineering, context engineering, they understand how to do this, as opposed to students who go to schools who don’t teach that,” he said. “Then they come in, and then they’re somehow expected to know how to use these tools.” For Genawi, those disparities begin long before students arrive on campus. “It’s very interesting to consider how lucky you were geographically,” she said. “To be born where you were is influencing your ability to get access to these spaces.” Students like Yu, though broadly apprehensive about the future of computer science, are not without hope. “I’m optimistic, because I think if you’re truly passionate about CS, there will definitely be a place in the field to do something you want to do,” she said. Senior Staff Writer Ria Vasishtha can be contacted at ria.vasishtha@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Staff Writer Arjun Menon can be contacted at arjun.menon@columbiaspectator.com. Follow Spectator on X @ColumbiaSpec. Want to keep up with breaking news? Subscribe to our email newsletter and like Spectator on Facebook. Produced with Spectate by Emily Ta

May 2 • 8:00 PM EDT • Science • columbiaspectator.com

Calls grow over hospital care for jailed Iranian Nobel laureate Narges Mohammadi

On Friday her family said the 54-year-old had been taken from prison to a local hospital after a sharp deterioration in her health.

May 2 • 1:55 PM EDT • Health • bbc.com

Red Bluff science student named

Elli Norton was recently honored as the Red Bluff High School’s Spring semester student after the 5th grading period. Norton, a junior, has earned a 4.43 grade point average. Among the science classes she has taken are…

May 2 • 5:49 AM EDT • Science • redbluffdailynews.com

Punk Politics/Camp Costume is a fashion exhibition curated by (some of my) brilliant Parsons students!

I have the most amazing students. I teach Fashion Journalism at Parsons, as part of its MA Fashion Studies degree, though I have students of all different disciplines throughout the New School in my class — from fine-art photographers to investigative journalists to textile designers. And I learn about all sorts of fascinating things from them, like that designers are adding faux sweat stains to their garments now (part of a trend piece about “anatomy core”) and that real “French girl style” is actually about being “cunti cunta” (aka loud, rude, too much, liberated). So when I found out that some of my students were curating a fashion exhibition opening tonight(!!!), I just knew that it would be brilliant too. Wearable Art is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Subscribe It’s called Punk Politics/Camp Costuming1, and it’s up through May 10 at La Sudestada, the wonderful gallery and concept store in Greenpoint, Brooklyn. I asked the exhibit’s lead curator, Ella Birney (a talented costume and knitwear designer from Belfast who also happens to be in my class), all about it. This conversation has been edited for length and clarity. Tell me about the idea of this exhibition and how it came about. Ella Birney: For our Fashion Curation class, we had to pitch [exhibition] proposals to our professor, Jessica [Glasscock], and I really wanted to continue on the themes that I was exploring in my BA when I was studying in London a couple of years ago. My BA was very punk-inspired and very political. Everything I do, as you know from my writing, always has a slight Irish, political twist to it2. So in my BA project, it was looking at knitwear as a conveyor for exploring political identity in somewhere like Ireland, where identity is such a point of contention. And looking at the images that I generated from that project, there was something so camp about the whole thing. Like, it’s so playful and in bad taste to do a political message — like a knitted Union Jack — out of mohair. There’s something very camp about that. So that’s where it kind of became punk politics/camp costuming — looking at how from the 1970s to now there’s been protest through costume and clothing. What was your BA in? It was fashion textiles, knitwear. Very craft heavy, which — craft is never taken seriously either. That’s also a kind of spin [on the punk/camp thing]. The Union Jack knit that you made is included in the show — what is camp about knitting a Union Jack out of mohair? The whole ethos of camp is kind of bad taste, doing things that are tongue in cheek and a bit wink, wink, nudge, nudge. Like, this is a bit silly. Everything I do is like, this is a bit silly. Like, being from the North of Ireland, everything you do is political. So it’s like, everything is going to be looked at in a certain lens anyway, so we may as well lean into it. So the Union Jack was because I come from a mixed marriage — Protestant-Catholic. And in the North of Ireland, that’s still a big deal. And even though I’m a Catholic and brought up in a very like Catholic Nationalist family, there [were] Union Jacks [the symbol of the United Kingdom] on my street. So I was like, then I’m gonna make your Union Jack out of knitwear. And then that kind of all linked back to the punk movement that Vivian Westwood forefronted in the late 70s, [with her stores] Let It Rock and Seditionaries. How did you source your items? Once we decided on this exhibition idea, everyone in the class was put to [think about] what do you think can fit into punk politics/camp costuming and finding designers that fit that brief. Me and my co-curators, Dulcinea Flores and Allison Gramando, made a brief to send out — with a mood board and color stories, stuff like that — and then everyone kind of got to work emailing people. We reached out to other Parsons grads. Even through Instagram stories we’ve been able to reach so many people who were like, Yeah, of course, I’ll write something for this, or Please — let me submit stuff. It actually was quite easy sourcing things. … The Parsons thing gets you quite far. What were some great pieces you got? There’s a Brooklyn-based, nonbinary artist called Buzz Slutsky. I can’t even remember how I found them, but I came across this crazy, shoe thing — they had made all these different shoes out of papier-mâché, and the story behind them is so fantastic, so interesting. They were just so obliging, like, Of course, you can have these for a few weeks. I was really happy about that. And then we have art from a collective here called Art Comes First. And they lent loads of really amazing pieces that just tied everything together. You have your Union Jack knit in the show too. Any other pieces that you made? There’s three of my BA mohair knits. There’s the Union Jack. There’s a mohair with the word “No” — which is based on an old political campaign in Ireland that was “Ulster says no to sodomy.” And then there’s another one that is red, white and blue, like the Union Jack, but has the word “Catholic” on it and lots of holy medals. I’m so happy I got to include those. How many pieces are in the show? Between 49 and 52, something like that. A load of clothing and accessories, shoes. There’s a Brooklyn-based Irish photographer who’s given us photos. There’s also a shopping cart that is an art piece by Art Comes First that has gold knuckle dusters as the handles. There’s also lots of T-shirts, original pins from the 70s and 80s that were from people’s dads. I also brought my record player, and all of [co-curator] Allison’s dad’s original albums so everyone could play records. Oh my gosh! Yeah, it’s cool. Anything else you would like to add? If we get to do an exhibition, why would we not make it political in this day and age? I hope that people come. There’s a lot of history, because it starts back in the 70s. It’s not like chronological or anything, but there are historical objects. I hope people come out of it thinking, out of all the really horrendous decades of the 70s and 80s and 90s, all these amazing subcultures happened. There are horrible political times, but there’s art that comes out of it that lasts. Punk Politics/Camp Costume is on view May 1-10 at La Sudestada, 67 West St. Suite 513, Greenpoint, Brooklyn. RSVP for the opening Friday May 1 6pm-8pm here. There’s also a button-making and patch-making workshop and artist talk May 9. Follow the show’s Instagram page @punkxcamp.parsons. Special shout out to all the students who put on this show: Ella Birney (lead curator), Dulcinea Flores (curator), Allison Gramando (curator), Pierre Sanon (lead exhibition designer), Eliana Daneshvari (exhibition designer), Reilly Lowell (editor), Jess Gayo (researcher/writer), Joyce Gayo (researcher/writer), Maria Magdalena Ugarte Montero (researcher/writer), Cassidy Colarik (exhibition press officer), Shelby Shovein (educator), Sarah Mahnke-Baum (educator), Trinidy Coleman (graphic designer), and Leonie Soravia (project manager). Jessica Glasscock was the faculty advisor. 1 The website is definitely worth checking out. 2 This is true!

May 1 • 3:59 PM EDT • Politics • raquellaneri.substack.com

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Apr 27 • 9:54 AM EDT • Health • orange.floridahealth.gov

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Apr 27 • 8:00 AM EDT • Science • sciencedaily.com

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Apr 26 • 6:00 AM EDT • Technology • wired.com

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Apr 26 • 5:19 AM EDT • Politics • nytimes.com

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Apr 26 • 2:48 AM EDT • Sports • formula1.com

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Apr 25 • 5:20 AM EDT • Technology • forbes.com

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Apr 24 • 7:00 AM EDT • Sports • cbssports.com

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Apr 24 • 1:29 AM EDT • Sports • foxsports.com

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Apr 23 • 4:28 PM EDT • Technology • forbes.com

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Apr 23 • 8:00 AM EDT • Science • sciencedaily.com

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Apr 22 • 3:20 PM EDT • Science • thehill.com

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Apr 22 • 12:06 PM EDT • Sports • cbssports.com

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Apr 22 • 9:38 AM EDT • Science • science.nasa.gov

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Apr 22 • 8:00 AM EDT • Business • hodinkee.com

Pokémon Doubles Down on Decision to Penalize Pro Player

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Apr 22 • 5:17 AM EDT • Technology • ign.com

Adversaries may have taken missing US scientists, lawmaker says

Nearly a dozen researchers or people with links to aerospace or defense programs have disappeared or died in circumstances that some observers have deemed suspicious.

Apr 21 • 1:47 PM EDT • Science • newsnationnow.com

On the Hill: Health Care Reauthorizations, Congressional Hearings

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Apr 21 • 12:09 PM EDT • Health • essentialhospitals.org

Shaky political science: using "simulated" elections over real-world elections

[Dear DSOS readers – this article is the latest in our “Shaky Political Science” series. In our 38 page report, “Shaky political ‘science’ misses mark on ranked choice voting,” released in early December, we examined over 40 studies focused on ranked choice voting. We found that many of these studies suffered from puzzling research methodologies, poorly constructed surveys, unrealistic simulated elections, cherry picked data, and faulty analyses that often were contradicted by results from real-world elections (a link to our full paper is here). Here are links to the first three articles in our series: the first one summarizing the overall results of our report, the second one analyzing a study co-authored by University of Minnesota academic Larry Jacobs, which was one of the most error-prone of all the research we reviewed in our report, and a third article showing an admirable example of two political scientists holding two other political scientists accountable for their flawed, sloppy research]. In this fourth article in our “Shaky Political Science” series, we shine a spotlight on seven studies that were web-hosted and funded by New America’s Political Reform Program and its Electoral Reform Research Group (the ERRG is an ad hoc committee headed by New America’s Political Reform Program and joined by the American Enterprise Institute, the Unite America Institute and Stanford University’s Center on Democracy, Development, and the Rule of Law). This research consortium has been led by Lee Drutman, senior fellow with New America’s Political Reform Program. These seven studies are simply not credible from any objective standard about how political “science” is supposed to illuminate our understanding of either ranked choice voting or politics in general. The feature that six of these seven studies have in common is that they all used surveys – artificial, simulated elections -- to attempt to say something cogent or interesting about ranked choice voting (RCV) elections. None of them used real world data from actual RCV elections – either the 1000+ elections in the US or the many thousands of elections from places like Australia, Ireland and elsewhere where RCV has been used for 100 years. While a few of these studies conclude with some mixed positives about RCV, our analysis here is content neutral. The idea that, with a political reform like RCV, you can ask respondents in a mock, artificial election to vote with that method, with only the barest of explanation about how RCV works or its likely impacts (i.e. no spoiler candidates, majority winners, voters liberated to pick their favorite candidates, coalition-building), and then ask them their thoughts/reactions about voting in that system, with fake candidates and no real campaigning, no real exposure to an actual election or actual candidates, rests on some very puzzling assumptions. The findings of these seven studies actually are contradicted by the findings from many other studies based on real-world RCV elections. These New America studies also failed to list the real-world RCV studies in their own citations, instead including those studies that reinforced their conclusions. The seven studies featured in this article were chosen because they form a cohesive cohort which precisely illustrates one of the main points of our research paper, namely that using surveys, i.e. artificial elections, or mathematical/theoretical models, instead of real-world data, is in fact “shaky political science.” Below are summaries of our analysis of five of the seven New America studies. You can read our complete analysis of all seven studies at our paper, “Shaky political ‘science’ misses mark on ranked choice voting.” Choosing to “Vote As Usual” by Andre Blais, Carolina Plescia, and Semra Sevi. New America. (Blais et al., 2021). This study, web-hosted and funded by New America’s Political Reform Program and its Electoral Reform Research Group, used two surveys in which respondents completed ballots for simulated elections using plurality, approval, RCV and point (Score) voting. In both cases the authors provided the respondents with only minimal explanation of each method. For example, the entire explanation for RCV was “For this vote, rank the candidates from your first to your last choice (you do not need to rank them all). This is called the ranked vote.” That’s it. The study did not provide any context or explanation to survey respondents about why she/he might want to rank multiple candidates. Participants were not even told that ballots would be tabulated using an “instant” runoff, not to mention any description of RCVs ability to eliminate the spoiler effect or liberate voters to rank their favorite candidates without fear of helping the “greater evil” candidate to win. That’s like taking an iPhone back in time to 1970 and asking someone if they like it better than their rotary phone without explaining how it works. Their first survey targeted states that held 2020 Super Tuesday Democratic primaries and used the real candidates’ names in the survey; the second survey used fictitious candidates. In other words, they surveyed respondents who had only ever participated in plurality elections, had no history or background with using RCV or any of the other methods, had no clue about its likely impacts, and did not communicate how the alternative methods would be counted, and then asked them: “How satisfied are you with using each system?” Predictably, the winner was plurality elections, the system used for president, Congress, gubernatorial and state legislative elections – in other words, the method they have been using, year after year, all their voting lives. With so little explanation of RCV and its impacts, this study is simply not credible in discovering anything useful about real-world RCV elections. It merely shows that a basic voter education campaign is needed when adopting a new election system. Additionally, the result contradicts many other post-election surveys following real RCV elections, asking opinions from voters who had just participated in a RCV election, that showed a great deal of satisfaction with RCV (see details on that in Studies 22-25 in our paper, as well as the four studies cited in the review for Study 28). Share Other studies on “satisfaction” and “understanding” make similar mistakes, in terms of basing their surveys on inadequate explanation to respondents and lack of education about context. How could any survey ever hope to measure accurately, in essence simulate a real-world election, without actual campaigning candidates, the media writing about those candidates, organizations endorsing candidates and voters being inundated with crucial information? More than anything, what these “studies” based on surveys show is that if you ask voters about something they don’t know very much about, and fail to adequately educate them, their responses will unsurprisingly reflect their confusion. Equally puzzling is that New America’s Electoral Reform Research Group, headed by political scientist Lee Drutman, found this to be a credible enough study that they not only published it but highlighted it in Drutman’s own discussion of research related to ranked choice voting. This pattern was repeated in study after study featured by New America’s Electoral Reform Research Group. For example in Ranked-Choice Voting and Political Expression: Voter Guides Narrow the Gap between Informed and Uninformed Citizens by Cheryl Boudreau, Jonathan Colner, and Scott MacKenzie, the researchers based their analysis on a survey which found that respondents who were asked to vote in a simulated RCV election, with minimal explanation of RCV or how it works, displayed less evidence of being informed about how to use RCV effectively, with the least informed voters ranking fewer candidates. As pointed out under the study above, in a real election voters are informed by a wide variety of methods, including public education by the election administration, by interested political groups, the media, and the candidates themselves who benefit from voters being aware of how to vote in the new system. In Support for Ranked-Choice Voting across Race and Partisanship by Joseph Anthony, David C. Kimball, Jack Santucci and Jamil Scott, the researchers used respondents from different parties and races voting in simulated plurality and RCV elections, who indicated their satisfaction with each voting method. Instead of using real world election results, the authors fell back on the easy, armchair and less reliable academic research methodology of making up mock elections. As with the other studies, little explanation was given of how RCV works or what its implications might be (electing majority winners or eliminating spoilers, for example). Unsurprisingly, this study found that respondents were not very satisfied with RCV. However, when the authors added an explanation that RCV has a tendency to elect more women and people of color, they found that this greater explanation increased the preference for RCV. The more voters were familiar with it, and the more they understood potential positive impacts – surprise! -- the more they were open to switching away from the status quo. Of note, the results from this study are thoroughly contradicted by a number of other studies whose data was obtained from real RCV elections with real voters. Those studies show a great deal of satisfaction with RCV. More “fake election” research An interesting wrinkle on this “research by fake elections” approach, which only served to illustrate how unreliable such “research” can become, was taken in Ranked-Choice Voting, Runoff, and Democracy: Insights from Maine and Other U.S. States by Joseph Cerrone and Cynthia McClintock_,_ also web-hosted and funded by New America’s ERRG. It gets high marks for creativity, but an eye-roll for thinking this could possibly add anything meaningful to our understanding of real world RCV elections. This study tried to determine whether RCV, plurality or two-round runoff elections provided greater voter satisfaction and acceptance of election results. To determine that, the authors conducted a survey asking if voters were satisfied with a fictional newspaper report of an election, with three different versions given to respondents – plurality, runoff and RCV, with variations of Republican/Democrat winners and variations of “come-from-behind” winners,” i.e. candidates not initially in first place but who win the “runoff.” Again, a minimal explanation of RCV or how it works was given, and the survey showed that respondents had the greatest unfamiliarity with RCV than the other methods. The unsurprising result? Respondents were much more satisfied with “come-from-behind” victories in a traditional two-round runoff election than in RCV, even though RCV is also a runoff system but with a single round of counting. Interestingly, the dissatisfaction with RCV disappeared for those who were more familiar with RCV. In fact, among those respondents who were “very familiar” with RCV, they were equally satisfied with RCV, runoff and plurality. Surprise, surprise. Again, what this study revealed, more than anything, is not only the inadequacy of the explanation for RCV given by the authors of this study, but the failure of the research format itself, thinking that such an artificial mock election could somehow simulate what actually happens in the real world in a real RCV election. Those four studies reviewed above are fitting examples of inadequate and shaky political “science.” Other studies reviewed in our paper from the New America/Electoral Reform Research Group cohort which also used mock elections included: Ranked-Choice Voting is an Acquired Taste by Joseph Anthony and David C. Kimball. New America. (Anthony et al., 2021). Ranked-Choice Voting is No Refuge for Extreme Candidates by Melissa Baker. New America. (Baker, 2021). Also included in this New America cohort is Does Ranked-Choice Voting Reduce Racial Polarization? by Yuki Atsusaka and Theodore Landsman, which actually did use real-world election results data but applied an odd and unconventional methodology to the data which relied on shaky assumptions and non-real-world scenarios that were too divorced from reality. To determine levels of “racially polarized voting,” the researchers imagined “ethnic parties,” by which they mean political parties for each ethnic group, which was especially odd since the election data they were using came from nonpartisan RCV races. But then they made an even odder assumption, namely that since race and ethnic characteristics of studied voters were not available, the authors tried to infer that information based on who voters selected and the racial make-up of voters in each district. This amounted to little more than vague and ambiguous guesswork dressed up with a bunch of mathematical equations used to give it a veneer of scientific appearance. Indeed, it seemed to assume racial polarization in order to prove racial polarization. Based on this questionable methodology, the authors concluded that RCV doesn’t reduce racial polarization. But the premise of this study missed an obvious reality: since RCV incentivizes more candidates to run and can result in more diverse fields of candidates, one would expect more racially-polarized voting in voters’ top rankings, not less, because more voters would have someone on that ballot who represents their racial or ethnic identity and more freedom to vote for their real first choice. By encouraging more diverse candidates and eliminating the spoiler effect, RCV facilitates voting for a favorite candidate of your own race and then selecting a second choice with the best likelihood of winning. The real measure is what voters do with their additional rankings – do they consider other candidates and vote “for the best of the rest”? This study didn’t tell us anything useful about that. But readily available data shows this is common in real RCV elections, and candidates act on this knowledge by engaging with voters outside their racial group. So the authors of this study failed to consider or account for what actually happens in real-world elections, and their conclusions are tainted by this failure. New America has contributed a great deal over the past 2.5 decades to our understanding of many policy areas, including politics and political reform (full disclosure: Steven Hill, one of the authors of this article and of the “Shaky Political Science” research paper and series, is a former senior fellow and former director of New America’s political reform program, 2005-2010). So it was especially disappointing that New America funded and published such a large batch of dubious studies about ranked choice voting. The stated praiseworthy goal of its Electoral Reform Research Group was to inspire new academic research about ranked choice voting that would shed light and help the public better understand the impacts of RCV. Instead, the ERRG research did just the opposite. It produced dubious research that created more confusion and misinformation. In so doing, New America’s political reform program contributed to “shaky political science.” Steven Hill and Paul Haughey Share Upgrade to $5 subscription Thanks for reading DemocracySOS, a reader-supported digital portal for the pro-democracy movement. Subscribe for only $5 per month to receive full benefits and to support our work. Subscribe

Apr 21 • 9:31 AM EDT • Science • democracysos.substack.com

Salmon contract signing another great step for young defender

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Apr 21 • 7:34 AM EDT • Sports • sports.yahoo.com

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Apr 16 • 2:28 PM EDT • Sports • sports.yahoo.com

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Apr 14 • 8:00 PM EDT • Science • sciencedaily.com

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“AI polls” are fake polls

A few weeks after Donald Trump’s second presidential win, I took the train up from London (where I was living at the time) to Oxford to attend a conference on polls and forecasts of the 2024 election. Most of the attendees were pollsters or academics, but I also watched presentations from Aaru and Electric Twin, two companies that do what is interchangeably called synthetic sampling, silicon sampling, or synthetic audiences. Stripped of startup jargon, that means they use large language models (LLMs) to simulate responses to public opinion polls by having AI agents take on the role of survey respondents. I had already heard of Aaru thanks to some articles with eye-catching headlines like “No people, no problem: AI chatbots predict elections better than humans” in the months leading up to Election Day. The founders were making some big, some might even say far-fetched claims, such as: “within two years, we will simulate the entire globe — from the way crops are grown in Ukraine to how that impacts production of oil in Iraq, trade through the strait of Malacca, and elections for the mayor of Baltimore.” When Semafor asked Aaru’s cofounders — Cameron Fink and Ned Koh — about my boss, they said “we respect all those who came before us.” Nate (as he so often does) shared his thoughts on Twitter: Fink and Koh were relatively good-natured about this back-and-forth when we spoke at Oxford. They even offered to mail me one of the t-shirts featuring Nate’s quote they apparently had made. I never took them up on the offer, which I now somewhat regret. These synthetic sampling companies fell off my radar for a while, but they do still exist. In fact, Aaru recently received a $1 billion valuation. Is what they’re doing anywhere close to the most important frontier in AI development? Not by a longshot, especially when Anthropic just developed a model so adept at exploiting software vulnerabilities that it’s only being released to 40 companies. Still, silicon sampling is increasingly finding its way into public polling. Axios reported in March that “a majority of people trust their own doctors and nurses” based on findings from Aaru — without mentioning that the “people” in that sentence were actually LLMs. Around the same time, the Public Sentiment Institute “boosted” their online sample of 373 real survey respondents with 114 AI agents.1 (Spoiler alert: even the co-founder of Electric Twin doesn’t think that’s a particularly defensible approach.) Polling companies like Qualtrics and Ipsos are also developing synthetic data panels. So, what should we make of these … “polls”? Let’s get one thing out of the way: whatever they are, they’re not polls in the way that term is usually defined. Subscribe You can’t replace polls with AI On one hand, using LLMs to essentially make up fake survey respondents sort of sounds like the dumbest idea ever, one that will at best imperfectly replicate real polls while introducing all sorts of biases. On the other hand, with LLMs improving at a remarkable, perhaps even alarming rate, maybe that means I’m a dinosaur at the ripe old age of 24 because I still want to rely on polls that talk to actual people. I’m not going to argue that synthetic samples are completely useless. In fact, as I’ll return to later, there is evidence that some techniques can replicate topline survey results quickly and cheaply. But the marketing from certain companies can be slightly optimistic. “No traditional poll will exist by the time the next general election occurs,” said Fink in 2024. We’re just 206 days away from the midterms, and based on the fact that I still have to collect a bunch of polls every day, I’d say he should have run that prediction by a sample of AI agents before the interview.2 To see why synthetic samples can’t replace polls, here’s a quick primer on how they work. The simplest version of these models involves taking a LLM (like ChatGPT or Claude), giving it a demographic profile (e.g., a white, college-educated woman who lives in Utah and makes $70k a year), and then asking it to respond to a survey question. You repeat that process a few thousand times using different demographic profiles and end up with a sample of synthetic survey responses. The actual models used by private companies are more sophisticated than this, usually because they incorporate more hypothesized demographic characteristics for each agent and provide them with extra information. Aaru, for example, feeds agents a diet of news and information they’d be likely to consume, while Electric Twin incorporates their customers’ proprietary data about the audience they’re trying to replicate. The way Ben Warner, the co-founder of Electric Twin, explained it to me was “we have a large amount of data on […] for instance, 5,000 people. Can we make an accurate prediction of how they would respond to another question?” Still, it should be obvious why synthetic samples can’t replace polls. Polling is fundamentally a data collection process. We might use surveys to make predictions by feeding them into election forecasts, but the main purpose of a poll isn’t prediction, it’s gathering new data about what people think and how they feel. Silicon sampling, on the other hand, produces no new data. It’s simply a model: you input LLM training data, demographic prompts, and a bunch of other information, and it spits out a prediction for what a poll would say. We love models here, but models aren’t polls. That difference is an important philosophical sticking point for most pollsters I talk to. “I think politics should stay away from [synthetic sampling], because we’re trying to […] represent the voice of the people,” said Natalie Jackson, a vice president at GQR Insights. Democratic pollster John Hagner told me: “I think I’m just incredibly skeptical of this idea. I don’t think it’s research. At that point, you’re asking the machine to tell you what you already believe.” Hagner has seen some presentations of early synthetic sampling experiments, but so far, “if it’s being used in a campaign, people are keeping it incredibly quiet.”3 But Eli, I hear you saying, aren’t polls themselves increasingly governed by modeling decisions? Indeed they are: pollsters’ choices on which sampling method to use, how to define their likely voter models, and how to weight their samples can and do lead to dramatic differences in the results they publish. Aaru even referenced these limitations in the methodology statement included with that maternal mortality “poll” — although I’m using the term “methodology statement” loosely here, because it doesn’t really explain how the model works at all. We can ignore the (frankly preposterous) implication that synthetic sampling isn’t subject to a separate set of biases. The important point is that there’s still a meaningful difference between using weighting and other statistical techniques on actual polling data and using a model to predict what a poll would say. The latter is far closer to election forecasts or techniques like MRP — potentially useful models, but not a replacement for polls.4 To be fair, other synthetic sampling companies are perfectly happy with the distinction between polls and models. Warner compared polling and synthetic sampling to different tools in a toolbox. “The mistake I think we make is we think that these new tools should either work in exactly the same way or somehow replace these old tools,” he said. “Rather than thinking of it as, okay, so we’ve always had the hammer, we’ve always had the screwdriver, now we’ve got a saw. But don’t use a saw to try [to] do the job of a hammer.” A quick comment from Nate Eli didn’t ask me for a comment — rather rude of him, don’t you think? But since I’m editing this story, I figured I’d add a few quick thoughts rather than putting words in his mouth. Beyond the frequently misleading marketing, what bothers me about the AI “poll” hype is that as AI tools make statistical inference cheaper and/or better (note that these are not synonyms) that actually increases the comparative value of collecting original data. You might be able to train a model to make a reasonable estimate of what some hard-to-reach poll respondent would say — say, a young Black man who voted for Trump. (Such a person checks a number of boxes for a voter who is usually hard to reach in surveys.) Indeed, this is closely related to what models like the Silver Bulletin forecast already do. They essentially smooth out the kinks in noisy survey data by making inferences based on past voting patterns or national polls or surveys of other states. But you don’t actually know what these voters think unless you’re reaching them directly. If there’s a shift in opinion among this subgroup, you’re not going to detect it. So if I were running a campaign, I’d invest more in going the extra mile to find a representative sample of those voters. And then I’d hire some smart quants — or Claude? — to figure out the implications for campaign strategy based on proprietary data that my competitors didn’t have access to. -Nate Silver Are these models any good? If synthetic surveys are just a new type of model, the next obvious question is whether the models are at least accurate. The answer very much depends on who you ask. On one end of the spectrum, you have the maximalist argument that synthetic sampling is more accurate than actual polls. “It’s an incredibly challenging problem to go to someone and say ‘hey, we’re going to be more accurate at predicting human behavior than you, even when you talk to your customers directly’,” Koh recently told CNBC. In his view, synthetic sampling isn’t a saw to polling’s hammer, it’s “magic.” There’s certainly evidence that synthetic samples can replicate certain survey toplines. But if Aaru does have any examples of their approach outperforming the polls, they’re keeping those to themselves.5 Aaru’s 2024 election model, for example, had Kamala Harris leading in Michigan, Nevada, Pennsylvania, and Wisconsin on November 4th. And although they’ve since taken down their forecast page, they gave Harris a 50.5 percent chance of winning the race on November 2nd.6 After the election, Fink told Semafor he was happy enough with those results because they were “within margin of error,” a term that is completely meaningless when applied to a “sample” of AI agents. And of course, Aaru says their models have improved since 2024, so supposedly now they’d be more accurate than the polls? Still, their stronger argument is on cost: “We are significantly faster and cheaper than traditional polling, and still more accurate,” said Fink. The first two claims are undeniably true, but the third brings us to the opposite end of the spectrum. Both Jackson and Hagner are skeptical that these models are reliable for anything beyond replicating common survey toplines. “I just […] don’t think the machines are what we want when we’re looking for nuanced views. My example on this is people in Arizona and Nevada in 2024 who voted for Trump and voted for expanding abortion in their states on ballot initiatives,” said Jackson. Hagner identified another issue. Maybe the synthetic respondents, like sycophantic LLMs, are inhuman in one important way: they’re too nice. “The reports that have come through at the meetings that I’ve been at are that the early experiments on this, they cannot get respondents to be as racist or sexist or, frankly, as negative as human respondents,” he said. Academic research mostly agrees on this point. While there are some papers that show promising results when using LLMs to replicate polling data, most show that LLMs suffer from various quirks like producing too few “don’t know” responses and can seriously overpredict the favorability of politicians like Donald Trump and Kamala Harris. They also seem to struggle with too little variation between demographic subgroups, so the difference in predicted opinion between Democrats and Republicans, for example, is too small. When I asked Warner about these studies, his response to these papers was that just because academics can’t get synthetic sampling to work doesn’t mean that the technique doesn’t work in general. “Actually, the argument is, okay, yours does not [work]. That does not mean […] for this complex set of machinery, which uses a lot of investment, a lot of time, a lot of money, you can’t get it to work.” Cards on the table, I’m somewhat sympathetic to this argument because academics aren’t exactly great at making election forecasts. Usually, the people with skin in the game are the most accurate. Warner’s argument is that the approach Electric Twin takes — which includes, for example, making multiple predictions for each synthetic respondent using different models and prompts and subsequently averaging those to get a final prediction in a sort of ensemble forecast — produces better results than the simpler academic models. Warner shared a comparison between his method and the method from a recent academic paper with me, and Electric Twin was indeed able to get more accurate replication. But even still, he acknowledged that synthetic sampling “is not a crystal ball.” “If you asked me, do I think using other data sources will be more accurate than asking somebody who they will vote for, I would probably say no. But if you asked me ‘would your system be useful for our turnout modeling today?’ I would say yes.” For better or worse, it looks like the method is already getting more popular in the market research world. Most of the clients Aaru touts these days are businesses like EY and McDonald’s. And AI will probably begin to pop up in other parts of the political polling process. Pollsters are already using it to code open-ended survey responses, and some firms, like YouGov, are testing using LLMs to ask survey respondents questions. More worryingly, one danger to actual polls is that AI agents can be used to infiltrate online surveys. Most online polls use various checks to prevent that from happening, but there’s conflicting evidence on how effective those filters are and how prevalent AI agents currently are in online panels. If those agents ever become impossible to detect, it might spell the end of online polling, but the solution isn’t to replace all of your respondents with ChatGPT. Silver Bulletin is a reader-supported publication. To receive new posts and support our work, consider becoming a subscriber. Subscribe 1 That particular poll obviously doesn’t meet Silver Bulletin standards for aggregation. But we exclude all Public Sentiment Institute polls from our averages because we classify them as an amateur polling firm. 2 You could argue that Fink meant the next presidential election, but (a) I’m also confident we’ll still have real polls in 2028 and (b) in that case he should have asked an LLM to define “general election.” 3 Quick caveat: that’s reporting from a Democratic pollster. It’s possible that Republicans are more willing to use AI in political campaigns. 4 Indeed, Silver Bulletin does not include “polls” produced by MRP in our forecasts or averages, and we think it’s extremely misleading when their practitioners describe them in a way that suggests original data had been collected among a large number of states or Congressional districts. 5 A recent report from Aaru and EY did show two examples of a synthetic estimate being closer than a survey to a real-world benchmark — but I’d take those findings with a grain of salt because the report reads more like an ad and didn’t involve any sort of prediction being made ahead of time. 6 For comparison, our odds for Harris on the same day were 48.2 percent.

Apr 11 • 11:38 AM EDT • Technology • natesilver.net

Atlético Madrid ‘astounded’ by Barcelona’s refereeing complaints

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Apr 11 • 10:00 AM EDT • Sports • sports.yahoo.com

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Apr 10 • 8:00 PM EDT • Business • altoonamirror.com

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Apr 10 • 1:28 PM EDT • Business • universe.byu.edu

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Apr 9 • 6:35 PM EDT • Sports • foxsports.com

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Real Madrid’s search for defensive reinforcements has taken another unexpected turn, with one of their previously monitored targets now looking increasingly out of reach. As the club continues to a...

Apr 9 • 2:25 AM EDT • Sports • sports.yahoo.com

The World’s First Computer Sank 2,000 Years Ago. Science Finally Solved One of Its Biggest Mysteries.

This ancient technological marvel was staggeringly far ahead of its time.

Apr 8 • 10:41 AM EDT • Science • popularmechanics.com

Dem Missy Hughes announces health plan aimed at countering Trump

Democrat Missy Hughes released a health care proposal that would serve in many ways as a buffer against actions taken by the federal government.

Apr 8 • 9:58 AM EDT • Health • jsonline.com

Week 11 and First Adjournment of the 2026 Session

This edition of Health at the Capitol reviews health policy issues considered by the Kansas Legislature the week of March 23 and actions taken by Gov. Kelly ahead of the veto session.

Apr 8 • 8:00 AM EDT • Health • khi.org

Artemis 2 science gets underway as Orion begins its return trip

As Artemis 2 begins its return to Earth, scientists are just starting to review the images and observations taken by the crew as they flew around the moon.

Apr 8 • 6:23 AM EDT • Science • spacenews.com

The Boundless Deep: Young Tennyson, Science, and the Crisis of Belief by Richard Holmes

Pantheon Review by Walter Cummins The image of Alfred Tennyson I’ve carried for decades goes back to the childhood card game of Authors that depicts him with a stately continence sharpened by a jutting black beard. He’s formidable, his aura superior. Holmes opens his biography of the youthful Tennyson by describing the similar formality of the imposing Tennyson statue at Trinty College Cambridge, sharing the honor with other Trinity greats, including Isaac Newton, Francis Bacon, and Thomas Babington Macaulay. Holmes doesn’t want to chip away at that statue but rather reveal its inner youthful core of the man—tall, handsome, and talented but unformed, emerging from a disturbed family of addicted or insane male siblings and four unusual sisters struggling under a violent alcoholic clergyman father. Alfred was certainly statuesque, but would he end up a block of unformed stone like his equally promising brothers? He was youngest of three equally regarded Tennyson brothers at Cambridge, all bright, handsome, and talented, in fact Alfred regarded by some as less promising than his elders who also wrote poetry. Yet Alfred wrote one of his major poems, “The Kraken,” at twenty, revealing both his talent, his interest in geological forces, and the haunting creature that embodied his anxieties. While Holmes focuses on Tennyson of the 1830s and 1840s, he can’t tell his story without exploring his involvement with the Victorian intellectual upheaval. Tennyson was fascinated by new scientific perspectives, following the latest findings as soon as books and articles were published. He was especially taken with Charles Lyell’s deep studies of geology and the discovery of fossils and a timeline of the planet’s development that did much to question fundamental religious assumptions. The impact of these discoveries is reflected in Tennyson’s poetry and led to the crisis in belief he shared with so many contemporaries. He was especially taken by the cycles of destruction and renewal that informed the struggles he confronted in In Memoriam, Maud, and Idylls of the King. Tennyson was only one of the eventual major figures at Cambridge at the same time, young men just beginning to realize their potential. Charles Darwin was at Christ College, although there is no evidence that he and Tennyson even met as students or later in life. Yet evolution became significant in Tennyson’s thinking and the issues of his poetry. One of Tennyson’s best and most important Cambridge friends was Edward FitzGerald, who became the translator of The Rubáiyát of Omar Khayyám and in their on and off relationship served as Tennyson’s harshest critic. FitzGerald was also a friend of the novelist William Makepeace Thackeray, the two of them partying in Paris as undergraduates. That connection led to a friendship between Thackeray and Tennyson. Others who came to play significant roles in Tennyson’s life were Thomas Carlyle, the Brownings, and the Pre-Raphaelites. Tennyson’s deepest friend at college was Arthur Hallam, who at twenty wrote a glowing review of Tennyson’s first poetry collection, travelled on European adventures with him, and fell in love with his sister Emily. Hallam was also regarded as one more very promising Cambridge student. His sudden death at twenty-two in Vienna from a stroke while travelling with his father devastated many friends, but perhaps Tennyson most of all. He did not write immediate poems of grief but took years to compile those collected in In Memoriam A.H.H., published in 1850, almost twenty years after Hallam’s death For all of Tennyson’s early poetic successes and successes, Holmes reveals him as an often troubled young man suffering periods of depression, fearing planetary upheaval, concerned about supporting himself, disappointed in romances, and worried that he would inherit the family’s mental illness tendencies. Yet despite his seeming withdrawals, he was always writing poetry that he kept private and would not let go, constantly revising. 1850 became a transformative year for Tennyson. He finally consented to publishing In Memoriam with a last-minute prologue that acknowledged God and perhaps convinced the religious Emily Sellwood to marry him after years of pursuit.. He opened up to Emily, revealing his struggles with fears of depression and “weird seizures.” The devastating event of that time was the stillborn death of his unnamed first son. It shook him, but Emily’s faith brought them closer and convinced him to believe in an afterlife. Two later sons survived. With the death of William Wordworth in April of 1950, Tennyson was named poet laureate at age forty-one, reluctantly accepting. It’s as if Tennyson’s life split in half in that year. He lived another forty years, now a recognized success, with the prestige of being an official poet writing patriotic verse, wealthy and revered, no longer the insecure young man seeking an outlet for his immense talent. He earned a place in the Authors deck, now dignified and in 1884 elevated to the peerage as Arthur, Lord Tennyson. Richard Holmes is the author of twenty previous books on the Romantics and Victorians, several of which received awards. The Boundless Deep was shortlisted for the 2025 Baillie Gifford Prize for Non-Fiction. He captures the complex vicissitudes of Tennyson’s youth, illustrated by frequent excerpts from the poetry, placing that life in the full context of the shattering discoveries that led to an upheaval of thought in the Victorian age.

Apr 7 • 12:35 PM EDT • Science • calirb.com

The world’s “oldest octopus” was never an octopus

A famous “oldest octopus” fossil has been exposed as a case of mistaken identity. Advanced imaging revealed hidden teeth showing it was actually related to a nautilus, not an octopus. The confusion came from decay that altered its shape before fossilization. This discovery rewrites part of evolutionary history, pushing the true origin of octopuses much later in time.

Apr 7 • 8:00 AM EDT • Science • sciencedaily.com

Trump says God supports U.S. cause in Iran war as he threatens wider bombing

The president offered a new rationale for the costly, unpopular conflict: “God wants to see people taken care of,” he said.

Apr 6 • 7:14 PM EDT • Politics • washingtonpost.com

Iran rejects latest ceasefire proposal as Trump’s deadline approaches

TEHRAN, Iran (AP) — Iran on Monday rejected a 45-day ceasefire proposal and said it wants a permanent end to the war, while President Donald Trump appeared to widen his threat from civilian targets to the whole Islamic Republic and his ultimatum ticked closer. “The entire country can be taken out in one night, and […]

Apr 6 • 3:17 PM EDT • Politics • coloradopolitics.com

YouTube’s copyright system strikes again.

Nvidia’s own DLSS 5 trailer was taken down from YouTube after an Italian TV channel — which reportedly used the footage in a segment about the upscaling tech — issued copyright takedown requests for videos using the same clips. The takedown requests impacted some creators using the footage as well. [Image: https://platform.theverge.com/wp-content/uploads/sites/2/2026/04/nvidia-copyright-takedown.png?quality=90&strip=all]

Apr 6 • 9:58 AM EDT • Technology • theverge.com

Scientists may finally detect hidden ripples in spacetime

Scientists have taken a major step toward probing one of physics’ biggest mysteries—how gravity and quantum mechanics fit together—by creating the first unified way to detect tiny “ripples” in spacetime itself. These subtle fluctuations, long predicted but poorly defined, are now organized into clear categories with specific signals that real-world instruments can search for. The breakthrough means powerful tools like LIGO and even small tabletop experiments could start testing competing theories of quantum gravity much sooner than expected.

Apr 6 • 8:00 AM EDT • Science • sciencedaily.com

NVIDIA's DLSS 5 trailer has been taken down due to 'copyright' infringement

NVIDIA's DLSS 5 announcement trailer is currently offline on YouTube due to a copyright infringement claim from an unlikely source.

Apr 5 • 10:02 PM EDT • Technology • tweaktown.com

Tori Spelling and 7 Children Hospitalized After Car Crash

The ‘Beverly Hills, 90210’ star and the children — including four of her own — were reportedly taken to the hospital with injuries including cuts, bruises, contusions, and concussions.

Apr 5 • 10:34 AM EDT • Entertainment • cbs19news.com

7 Science Lessons In The Stunning Astronaut’s Earth Photo

Our breakdown of 7 hidden science lessons in the stunning photo taken by an astronaut on the Artemis II mission.

Apr 5 • 10:12 AM EDT • Science • forbes.com

Commentary: Summer Is too important for politics to steal

If you can get your mind off the wars in the Middle East and Ukraine, if you can stop checking your 401(K), which seems to have taken off for the

Apr 5 • 8:57 AM EDT • Politics • davisenterprise.com

Shroud of Turin, claimed to be Jesus' burial cloth, contaminated with carrot and red coral DNA

An analysis of samples taken from the Shroud of Turin, the cloth thought by some to have been wrapped around Jesus, reveals a rich tapestry of animal and plant DNA. But what does it mean?

Apr 5 • 7:00 AM EDT • Science • livescience.com

Chucklefish on why Witchbrook has taken a decade to release

Donna Orlowski, the COO of Chucklefish, has explained why Witchbrook has taken so long to release. Back in 2016, the project was first teased. A year later, it was announced as Spellbrook, and then became Witchbrook in 2018. We’ve essentially seen the last decade fly by, but the game has still yet to debut. Orlowski gave some insight into the...

Apr 4 • 5:00 PM EDT • Technology • nintendoeverything.com

Grand Theft Auto 6 publisher Take-Two have seemingly laid off their head of AI and several of the department's staffers

It's currently unclear why these layoffs have taken place.

Apr 4 • 1:14 PM EDT • Technology • rockpapershotgun.com

Scientists built a quantum battery that breaks the rules of charging

Scientists have taken a major step toward futuristic energy tech by building a working prototype of a quantum battery—one that can charge, store, and release energy using the strange rules of quantum physics instead of chemistry. This tiny, laser-powered device hints at a future where energy storage is not only faster but actually improves as systems get larger, flipping the rules of conventional batteries.

Apr 4 • 8:00 AM EDT • Science • sciencedaily.com

Why Justice Alito was taken to a hospital last month

Apr 3 • 12:50 PM EDT • Politics • cnn.com

Exclusive: Justice Samuel Alito was taken to a hospital last month in previously undisclosed incident

Supreme Court Justice Samuel Alito was taken to a hospital after becoming ill last month at a Federalist Society dinner in Philadelphia, according to people with knowledge of the March 20 incident.

Apr 3 • 11:41 AM EDT • Politics • cnn.com

Found: Most pristine star in the universe

A record-setting pristine star provides a window into the dawn of stars and galaxies in the universe. This groundbreaking find connects the work of two telescopes at Carnegie Science's Las Campanas Observatory—the du Pont, where spectra for the Sloan Digital Sky Survey-V are taken, and the state-of-the-art Magellan Clay.

Apr 2 • 8:00 PM EDT • Science • carnegiescience.edu

Artemis II blasts off: Humans are on their way back to the moon

NASA's Artemis II rocket has taken off in a historic launch on Florida's Space Coast, sending humans back to the moon for the first time in more than 50 years.

Apr 1 • 6:56 PM EDT • Science • livescience.com

Braves vs. Athletics series recap: A business-like start to the season

Drake Baldwin and the Braves have taken their first two series of the season. Can’t complain about that!

Apr 1 • 5:00 PM EDT • Business • batterypower.com

The Hidden Garden: Science, profit and the human cost of ‘HeLa’ cells

“The Immortal Life of Henrietta Lacks” tells the story of an ordinary African-American whose cells were taken without her knowledge.

Apr 1 • 1:45 AM EDT • Science • stanforddaily.com

She’s Behind the Shutter: Women in Sports Photography

We look at photos taken by women, and so do you. Many who consume The Michigan Daily’s sports content fail to realize that, more often than not, the photo they are looking at was taken by a woman. With a staff made up of a supermajority of women, we are constantly pushing against preconceived boundaries that sports and sports photography belong to men.Our readers watch women compete tenaciously, aggressively and skillfully at every level. The Daily photo staff is honored to capture every moment. From gritty action shots to tender portraits, these women work beyond the bounds of sports photography to create images that reflect the moments others may miss.Working in a male-dominated field presents a host of challenges for young women hoping to make a name for themselves. Our photographers are here to explain the challenges and rewards of fighting for a spot in the action.

Mar 31 • 11:58 PM EDT • Sports • michigandaily.com

Mystery Of Odd Flashes In Pre-Satellite Sky Gets Odder, With Similar Puzzle Found At Separate Observatory In Hamburg

Looking at images of the sky taken before the first satellite was launched, one team believes they may have found objects floating above the Earth. Another study, based on a separate observatory in Hamburg, has now found a similar phenomenon.

Mar 31 • 5:01 AM EDT • Science • iflscience.com

Panicking scientists, canceled experiments: Federal funding cuts turn research dean to crisis management specialist

Fielding frantic faculty emails and panicked texts was not how I had hoped my 2025 would begin. Little did I imagine that my role as a research dean at a medical school would be taken over by navigating ...

Mar 30 • 8:00 PM EDT • Science • phys.org

This new “phonon laser” could measure gravity more precisely than ever before

Scientists have taken lasers beyond light and into the realm of sound, creating a breakthrough “phonon laser” that manipulates tiny vibrations at the quantum level. By dramatically reducing noise in these systems, researchers can now measure motion and forces with unprecedented precision. This advance could unlock new ways to study gravity, probe quantum physics, and even revolutionize navigation with ultra-accurate, satellite-free systems.

Mar 30 • 8:00 PM EDT • Science • sciencedaily.com

A New Compact for Health Financing: From Principle to Practice

Centred on evidence-informed priority setting, domestic-first financing of core services, and consolidated supplementary aid, the New Compact offers a framework to guide health financing reform. This paper examines how the New Compact for health financing can be taken from principle to practice, both as a strategic guide for global reform and as a technical framework at the country-level.

Mar 30 • 8:00 PM EDT • Health • cgdev.org

Barton outlines how politicians exploit voter information fatigue

Dona-Gene Barton, associate professor of political science at the University of Nebraska–Lincoln, was interviewed for a March 26 HuffPost article on how politicians on both sides of the aisle have taken advantage of Americans’ shortened attention spans to sway public opinion in their favor.

Mar 30 • 8:00 PM EDT • Politics • news.unl.edu

Apple Leans Into Little Finder Guy With New TikTok Videos

When promoting the MacBook Neo, Apple found a surprise hit with a tiny anthropomorphized version of the Mac Finder icon, which people have taken to calling Little Finder Guy. Little Finder Guy starred in some of Apple's early March TikTok videos, and Apple is now targeting Finder fans with a trio of new videos. Three tutorials on Apple's TikTok account star Little Finder Guy. Videos feature Stacks on the Mac desktop, ring light for video apps, and dictation.

Mar 30 • 7:47 PM EDT • Technology • macrumors.com

DOJ whistleblower complains to Congress that internal watchdog isn’t doing its job

A former federal immigration prosecutor and whistleblower who has taken issue with Trump administration leadership has now gone to Capitol Hill, saying the internal watchdog offices of the Justice Department are doing nothing to investigate his and other complaints.

Mar 30 • 3:10 PM EDT • Politics • cnn.com

Naked man breaks into Bend business, faces multiple charges

BEND, Ore. (KTVZ) -- A 43-year-old man was arrested Saturday night after police say he broke into a business and smeared feces in two areas of the building. Jajay Allen Findley was identified as the suspect and was taken into custody. Officers responded to the location after a caller reported a naked man had forced

Mar 30 • 1:05 PM EDT • Business • ktvz.com