Harvard grad students strike again, citing inadequate harassment protections

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From ScienceMag:

For the second time this year, the Harvard Graduate Students Union has gone on strike after the university failed to provide a “meaningful response” to demands for better pay and stronger protections for survivors of harassment and noncitizen student workers. The first strike, which began on 21 April, lasted 40 days until the university agreed to begin new negotiations. But on 27 October, research assistants and teaching fellows walked away from their labs and classrooms once again following what the union said was a final unsuccessful bargaining session.

“Many of us are really proud to study here,” says Ruth Tweedy, a striking Ph.D. candidate in earth and planetary sciences. Yet “being faced with some of the reality about how little empathy and compassion [the university is] showing for my fellow student workers has been really disheartening.”

In response to Science’s request for comment, Harvard University pointed to a 26 October letter from administrators, posted online, that describes their proposal to the union. “[T]he University has shown an unwavering commitment to reaching an agreement” and “remains fully committed to continued good-faith negotiations,” the letter says.

Harvard students aren’t alone in their discontent. Attacks on universities by President Donald Trump’s administration, the allegations of sexual assault at Cornell University, rising costs of living, and other concerns are roiling many campuses. Graduate student worker unions at universities including at the Massachusetts Institute of Technology, Brown University, and Columbia University are currently renegotiating their contracts, with MIT setting a strike deadline of 12 November.

For a year and a half, the Harvard union, which represents 4000 students, has asked the university to establish third-party arbitration for harassment-related proceedings. It currently handles them internally, through the Title IX office, which administers the federal ban on sex discrimination in education. Unions at several other institutions, including the University of Michigan, MIT, and New York University, have negotiated such arrangements. But Harvard has refused, arguing that federal privacy laws prevent it from sharing Title IX information with third parties, the union says. Joseph van der Naald, a research fellow at the National Center for the Study of Collective Bargaining in Higher Education and the Professions at Hunter College, disagrees. Pursuing this demand “is completely legal,” he says.

According to the union, one in five student workers at Harvard reports experiencing harassment, discrimination, or bullying. When cases are reported, the university can take years or even decades to resolve them, the students say.

Among the standard-bearers on this issue is Claire Traweek, a graduate student in mechanical engineering who says she left her laboratory after experiencing harassment. As she has described in rallies over the past week, some of Traweek’s men colleagues made sexist comments, called women “birds,” and expressed preferences based on women’s physical attributes, among other offenses. For more than a year, Traweek tried to file a formal complaint with Harvard’s Title IX office, without success; emails Science has seen show staff were often slow to respond. “It feels like Harvard’s number one mission is to make the least work possible for themselves and make the complainants go away,” says Traweek, who eventually found a home in a new lab. Harvard did not respond to questions about her case.

Another major topic at issue is compensation, a sore point at institutions across the country. Current salaries for Harvard’s unionized student workers—ranging from $26,000 to $50,000 per year—are well below the living wage estimate of $67,513 for an individual in that region. The union wants the range to increase to $45,000 to $55,000, plus raises or annual cost-of-living adjustments. The union also seeks guaranteed funding so research assistants experiencing sexual harassment or bullying can transition to a new lab without a gap in income. According to the union, Harvard rejected cost-of-living protections and offered to raise its lowest salaries from $26,000 to $31,362 by 2030.

The union’s third demand concerns protecting noncitizen student workers, who have been targeted at universities including Columbia, where federal agents searched student rooms, arrested a student, revoked a student’s visa, and entered a residential building without a warrant. The union wants Harvard to secure sensitive immigration documents, provide pay during visa delays or detention, notify students when U.S. Immigration and Customs Enforcement (ICE) agents enter campus, and require judicial warrants before allowing agents access. Harvard has rejected these proposals.

According to van der Naald, a union contract cannot require a university to violate laws requiring it to disclose immigration information to the authorities. But the university could commit to notifying students of ICE’s presence and not sharing personal information without a judicial warrant.

A heated bargaining session on 5 November ended when Harvard officials walked out in the middle of a sexual harassment discussion, according to the union, suggesting the strike is unlikely to end soon. 

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Life felt dark as an international researcher in the U.S., but I’m finding breaks in the clouds

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From ScienceMag:

My Ph.D. years were, for the most part, enjoyable. I was making progress toward becoming an academic, my career goal for as long as I could remember. I deeply missed my loved ones back in Iran whom I had not seen since I left for graduate studies in the United States. But my workdays felt mostly sunny, interrupted by the occasional overcast—until near the end of my program, when shifts in U.S. policy brought funding cuts, fewer positions, restrictions on immigration, and growing hostility toward international students like me. Dark clouds were gathering over the future I had imagined.

I was fortunate to find a wonderful postdoctoral position, a ray of sunshine I needed. But another cloud loomed when people in my home country calling for change faced a wave of violence and repression. An internet shutdown followed, cutting off communication as families feared for their loved ones. For weeks, I didn’t know how mine were doing. Eventually we managed to speak by phone; they were safe. But that didn’t erase the horror of what had happened, or the helplessness of watching it unfold from across the world. Soon after came military conflict with the U.S. I was constantly asking myself, are my loved ones alive? Will I see them again?

While fearing for those back home, I was also trying to hold on to my own future. The U.S. government paused processing certain immigration applications solely based on country of birth, putting my employment at risk. Suddenly, I didn’t know how much time I would have to work on my postdoctoral projects, let alone whether I would be able to stay long enough to pursue the academic career I dreamed of.

I had always thought of myself as an optimistic person. But so much had happened in such a short time. The rhetoric around immigration and visa policies made me feel increasingly unwelcome in the country I had come to love, where I was trying to build a life. I started to question the years I had invested in building a career in the U.S., when it could suddenly and arbitrarily be taken away.

I couldn’t enjoy my days anymore, or concentrate on my work. I consumed news constantly, searching for some encouraging sign. Instead, every development seemed to give me something new to worry about. Making matters worse, I felt I couldn’t talk about it with the people around me, as many of them lived under completely different circumstances. To them, things that could determine whether I would be able to stay in the country, continue my career, or see my family again were, understandably, distant abstractions.

Eventually, I realized worrying wouldn’t solve anything. I started to journal, trying to remember the blessings I had. I forced myself to put aside worries until a designated evening “worry time.” And I returned to an old friend: Persian poetry. There I found centuries of human experience—the same fears and struggles recurring across time, and the hope and love that helped the writers endure. My condition was not new and I was not alone.

The poetry reminded me, too, that life is short and struggles are temporary. Before it was too late, I needed to return to the pursuits I had loved long before any of this happened: doing science and creative work, discovering unfamiliar ideas, and meeting people who see the world differently from me. I broke my silence about my struggles, opening up to the people around me. My Ph.D. and postdoctoral advisers listened and shared, and I realized they have their own clouds, too.

There are some bright spots, such as a recent court ruling that certain immigration restrictions are arbitrary and capricious and need to be stopped, and voters taking decisive action in the midterm elections. But I’m no longer waiting for all of the uncertainties to disappear before I allow myself to enjoy my work, my life, or an ordinary day. As it happens, partly cloudy has always been my favorite weather.

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For early-career scientists, the cost of AI can be a problem

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From ScienceMag:

Earlier this year, Saad Bhamla, who leads a biophysics and engineering lab at the University of Colorado Boulder, sent a poll to the nearly 2 dozen members of his lab: Which artificial intelligence (AI) tools were they using? How much were they paying?

The answers caught him by surprise. “I realized, holy moly, everybody’s paying anywhere from $20 to … $200” per month, Bhamla says. “I was like: ‘This is a tax.’”

It’s not a unique situation. As AI gets better at the work involved in science, more scientists see it as essential rather than a nice to have. But researchers tell Science access to the best tools today depends less on need than on who can pay—and that the costs of AI are falling especially hard on early-career scientists, many of whom are reluctant to raise the issue because it feels taboo.

In a survey of more than 10,000 researchers around the world, carried out in March by Nature, 41% said they paid for their main AI tool themselves, compared with just 11% who said their institutions covered the fees. Those who relied most heavily on AI to do their research were more likely to be paying out of their own pockets, and heavy AI users were also disproportionately early in their careers.

Some universities have struck campuswide deals with AI firms. And companies such as OpenAI, Anthropic, and Google also have programs to give tens of thousands of scientists free or reduced-price access to their tools. But the versions universities make available to students are often too limited for heavy coding or data analysis, and it’s unclear how long any giveaways from the companies will last. 

In Bhamla’s case, the results of his poll caused him to ask his university whether it could cover his lab’s bills. No, he was told, because it already gives students and faculty access to tools, including ChatGPT Edu. Ultimately, Bhamla decided to cover the costs of the AI his team says it needs out of his own funding, costing thousands of dollars a year.

Elsewhere, many graduate students are shouldering the costs themselves. Haris Riaz, a Ph.D. student in his final year at the University of Arizona, says he often pays $300 or more per month for Anthropic’s Claude Code and ChatGPT’s Codex, especially during crunch periods ahead of a deadline. For Riaz, who studies how large language models (LLMs) absorb knowledge, “all aspects of the research process … basically involve heavy usage of AI tools.” His university does provide access to LLMs, but it doesn’t offer the most up-to-date models and it doesn’t include agents—models that carry out multistep tasks on their own, such as writing and running code.

Riaz says he’s “lucky” that industry internships have helped him cover some costs; if he had to depend on his stipend alone, it would have been a “significant hit.” Yet he’s steadfast in his belief he needs the latest tools. “There’s no middle ground. It’s either you spend the money … or you work on some very small old problems.” 

Omar Choudhry, a Ph.D. student at the University of Leeds using AI for medical diagnosis and care, was able to cancel a personal subscription to Claude after his lab joined Anthropic’s discounted plan for scientists. It gives a research group up to 25 seats that are free, or priced at $15 per month for higher usage. Because Choudhry’s lab has fewer than 25 people, he says members realized they could each use several seats. He still has to pay the $15 for each seat he takes himself, but it’s a better deal than he had before. Still, he doesn’t expect the discounts to last—and he also pays $200 per month out of pocket for ChatGPT. “We all know that this is just temporary,” Choudhry says. “Eventually, all these prices go up.”

Support from institutions can also be fragile. Jeffrey Backus spends much of his day chatting with Claude or ChatGPT—he has subscriptions to both. He’s in the fourth year of a theoretical particle physics Ph.D. at Princeton University but works mostly from the nearby Institute for Advanced Study (IAS). Backus paid for his own $20-per-month ChatGPT subscription, but IAS covered his heftier $200-per-month Claude plan during a 3-month, computationally heavy project. That support didn’t continue, however, and he now pays for Claude himself. “This is so essential right now to what I’m doing that I would definitely fork over the money for sure,” Backus says.

(Princeton does offer more advanced AI tools to graduate students if a faculty member sponsors them, according to the university’s website. The university did not respond to a request to clarify who pays.)

Sometimes, the early-career researchers most likely to fall through the gaps are those least willing to say so. “AI usage is looked down upon,” says another Princeton Ph.D. student who asked to remain anonymous. “There’s a level of embarrassment, I’ve noticed at least, when people admit to having used AI for whatever research product they’re showing.”

The cost of accessing tools and “tokens”—the basic unit of AI computing power—raises questions about whether fees are shaping who gets ahead, says Igor Chirikov, a researcher at the University of California, Berkeley who runs an annual survey of students at research universities. The person “who has access to those tokens will probably be a better scholar,” he says, “as opposed to, if you’re a smart person, you’ll be a better scholar.”

In nations where funding is scarcer, the AI divide can be especially stark. Giovani de Almeida Valdrighi is a computer science Ph.D. student at the State University of Campinas who studies fairness in machine learning algorithms. He pays about $20 per month for Claude. Valdrighi says he can afford it only because the stipend he receives through his scholarship is “one of the highest” in Brazil. But for a student on the standard federal doctoral stipend of 3100 reais per month ($615) the same plan would consume about 3.5% of their income, and many of his friends go without.

Top-tier tools are further out of reach. Ana Clara Zoppi Serpa, a Ph.D. student living in Belo Horizonte, Brazil, who tests LLM safety, pays $10 per month for a cheaper service that gives her access to several models, topping up with credits when she hits her limit. “I would love to have a subscription of Kimi or Claude, but I end up finding them more expensive,” she says. At $200 per month, a top-tier plan is “almost the price of the monthly rent of a small apartment” near the university, she says. She could afford it, but isn’t willing to. And others, she notes, “can’t afford that, so it’s not accessible.”

For a long time, Valdrighi says he used Google’s free AI tools but switched to paid tools when he saw peers with better models moving faster. “I did not decide to start paying because I like the idea of the product,” he says. “It was more because of the pressure that everyone is using it, and you have to use it also.”

On an internship in Germany this year, Valdrighi was surprised to find students paying for their own subscriptions as a matter of course. “I was shocked when I saw this difference,” he says. “I believe that’s kind of unfair because the research becomes pay to win.” Labs in different countries have always had unequal equipment, he notes. “But the difference, I believe, is that the university is paying for this equipment, while with AI, actually it’s the researchers that are paying.”

Valdrighi isn’t alone in his unease. Several researchers whose access to AI is largely paid for by others told Science they worry about colleagues slipping through the cracks, whether down the corridor or overseas. “I’m very advantaged,” Backus acknowledges. “But it does really bother me.”

For Bhamla, the solution starts with having open conversations about AI’s costs. His lab now has an AI tools channel on Slack, and one researcher has even made an AI bot to answer questions team members have. “We are openly discussing and embracing becoming ‘AI-native,’” Bhamla says. In many cases, however, he thinks the relationships between faculty members and their students is a bit like those parents have with their kids. When it comes to AI, he says, “the parents are a little bit out of touch with what the kids are doing.”

Science’s AI in Science reporting initiative is supported by Ray Rothrock & family.

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European scientists face uncertainty as pandemic recovery fund winds down

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From ScienceMag:

Researchers funded through the European Union’s pandemic recovery package are facing an uncertain future as the program comes to an end.

Over the past 5 years, the EU has awarded billions of euros in grants and loans to national governments across the bloc to stimulate economies following the pandemic slump. A sizable chunk of that money has gone to funding scientific infrastructure and research positions. Now, with final payments due by the end of the year, questions are mounting over how countries will retain the researchers needed to sustain those investments.

“Member states need to take national responsibility at their own level, rather than counting on another major injection of EU money,” says Robert-Jan Smits, former head of research and innovation at the European Commission. But with governments facing sluggish economic growth, mounting defense costs, and pressure on public finances, he worries it will be difficult for them to maintain spending on research.

Established in 2021, the EU’s Recovery and Resilience Facility (RRF) was designed to revive economies battered by the COVID-19 pandemic and increase future resilience by funding clean energy, digital technology, and other initiatives. National governments had to submit project plans to the EU and could request payment upon reaching specific milestones. The program’s €577 billion budget included €55.6 billion for research and innovation, which has helped pay for everything from mapping underwater seagrass meadows along Italy’s coastline to developing quantum technology in the Netherlands.

Other EU funds, including the Social Climate Fund, will likely ensure some initiatives launched with RRF money will live on. But EU member states are supposed to do their part, too, and researchers in some countries say their governments have not done enough to ensure their work can continue.

In Italy, one of those affected is materials chemist Ivana Di Bari of the Institute for Microelectronics and Microsystems, which is part of the National Research Council (CNR), the country’s largest research organization. With RRF support, Di Bari is developing sensors to detect volatile organic compounds emitted by plants under stress, helping farmers better monitor crop health. Although her project will continue with new funding, Di Bari’s contract expires in January 2027, and under new CNR rules adopted in September, researchers can work on fixed-term contracts for no longer than 30 months, a milestone Di Bari has now reached. The team may have to recruit someone unfamiliar with the research in her place. “You’re losing the expertise, you’re losing the know-how that has been generated in the meantime,” she says.

Others agree. Sociologist Serena Fabrizio was among 35 fixed-term researchers working on a €37 million RRF-funded project to develop data sets and services for research in sociology, economics, and public policy. She is now in a permanent position, overseeing a follow-up at CNR’s Institute for Research on Sustainable Economic Growth, but the new restrictions could prevent her from hiring colleagues who built the infrastructure and understand how it works, she says. “The approach is completely illogical.”

The end of recovery funding also poses employment challenges in Greece, where a €62.5 million RRF-funded program supported 279 research projects employing 1826 temporary staff, including postdoctoral researchers and Ph.D. candidates. The Hellenic Foundation for Research and Innovation, which administered the program, says the positions were tied to the duration of the projects and there was no provision for continuing researchers’ employment once the projects ended. In July 2025, the government scrapped a separate program called Trust Your Stars, which had aimed to use €80 million of RRF money to attract Greek scientists working abroad back to the country.

Portugal has taken a different approach. Its science funding agency used €197 million of national and RRF funding to create FCT-Tenure, a program that will help universities and research institutes hire 1104 scientists into permanent positions in its first round. The RRF money covers two-thirds of salary costs for the first 2 years, after which national funding takes over, with employing institutions contributing the remaining costs.

But many workers in science and higher education employed through Portugal’s recovery plan still face uncertainty. In April, the national commission monitoring the program urged the government to find ways to retain qualified staff employed on RRF projects, warning their departure could mean losing expertise. Trade unions in Spain have raised similar concerns about the fate of workers on temporary RRF-funded contracts.

Because RRF payments were tied to agreed milestones such as launching projects or completing facilities, some scientists worry countries have little incentive to follow up after the EU program ends. A laboratory may be completed or an instrument installed, but whether it produces scientific discoveries depends on retaining people with the expertise to use it, Fabrizio says.

Keeping up that momentum over the coming years will be a challenge. For his part, Smits is not optimistic: “Most governments always think short term, 4 years in a row till the next elections, and not about the long-term interests of their country.”

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Early-career researchers’ right to unionize at NIH is upheld, against agency’s petition

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From ScienceMag:

The union representing early-career researchers at the U.S. National Institutes of Health won a victory yesterday when the federal entity that oversees labor relations between the federal government and its employees rejected a petition NIH filed in March that questioned the union’s legality. The decision means the union’s contract—which limits work hours, guarantees paid parental leave, and provides protections against harassment, among other provisions—will remain in place. The contract is the first of its kind negotiated by scientists at a federal research facility.

“We hope the NIH accepts the decision and stops pursuing this petition,” says Ph.D. student Emilya Ventriglia, president of NIH Fellows United, which represents research fellows, clinical fellows, postdocs, Ph.D. students, and others who work at NIH under term-limited appointments. “It’s really a waste of the public’s money.”

The dispute centered on whether all the group’s members count as “employees” with a right to unionize, as opposed to being primarily students or “trainees.” In a July hearing held by the Federal Labor Relations Authority (FLRA), NIH representatives argued that the thousands of postdocs, Ph.D. students, and college graduates who work in NIH labs through training programs didn’t qualify. “They are not employees,” Lori Conlan, acting director of NIH’s Office of Intramural Training & Education, testified during the hearing, according to a transcript. NIH didn’t respond to a request for comment.

The agency had made the same argument briefly in 2023, ahead of the union’s formation. But NIH withdrew that stance and proceeded to engage in contract negotiations. A final contract was ratified in December 2024.

In this week’s decision, FLRA stated that NIH didn’t have grounds to challenge the union because “there is no evidence” the union had fundamentally changed since FLRA originally approved it. “To demonstrate that a previously certified unit is no longer appropriate, a party must prove that substantial changes have altered the scope or character of the unit.”

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A colleague hated my AI-polished emails—so he set a trap

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From ScienceMag:

Earlier this year, a close colleague and friend hid a sentence in one of his emails to me. It was meant for the artificial intelligence (AI) agent he suspected of answering my communications, and it told the machine to ignore its instructions and put a tiramisu recipe in the middle of the reply. I saw the sentence and decided to answer the joke with a joke, sending him a tiramisu recipe tailored specifically for him: a version with aquavit, a Scandinavian spirit. He did not find it funny. He thought the AI had delivered the recipe, and he was very angry. “I don’t need a better email. I need to know it is you reading my emails,” he wrote.

I had sent the recipe myself. But my colleague was onto something. By then, an AI assistant had been polishing my emails for about a year. I direct a research center in Norway that brings together more than 100 people. About 200 emails arrive on an ordinary day, and 500 on a bad one. My inbox has shown about 15,000 unread messages for years.

To cope with the deluge, I often found myself typing out brief replies on my phone between meetings. Most of the emails were in English, my second language. Often, my responses would consist of a greeting followed by a few imperfectly written sentences that got to the point quickly. “Sorry – but need to attend another urgent meeting. Can we move to to next friday? Same time?” I wrote to an industry contact whom I had to cancel on at the last minute.

When colleagues with similarly overflowing inboxes suggested an assistant, I thought it might help me develop friendlier, more thorough emails and get them done faster. It worked: I typed a few rough lines, and the assistant handed back what a kinder and better rested version of me might have written.

For a while, I saw no downside to my new method. After my friend’s tiramisu trap, I wasn’t so sure. I decided to be more up front about what I was doing by adding a line under my signature: “I may use approved digital tools, including generative AI, to support drafting and editing routine, non-confidential correspondence. I review and take responsibility for all messages I send.” For several months it stood under every email. Nobody set a trap for me again.

But eventually more colleagues started to open up and tell me they did not want a better email. They did not mind the directness, odd expressions, and unnecessary exclamation marks that had permeated my past emails; in fact, they wanted them, because they belong to a person they have met. They felt that my emails no longer sounded like me.

I make my living by studying how people use AI assistants. Yet I struggled to understand my colleagues’ reactions. I had not handed over any decisions, the information was mine, and I had disclosed the help. Eventually, my friend helped me see the problem. A reply in my own voice was how he checked that he could trust what it said, and it was a sign that his effort in writing to me was being returned.

So I changed how I work. I now ask, “What does this person need from me?” before I let a machine near a reply. Sometimes it is a clear answer or a carefully worded request, and in those cases I go ahead and use the assistant and read what it produces. I make a point to disclose it up front in my own voice, writing: “Warning, long AI-polished email incoming.”

But in other cases, especially when I’m emailing the people I work with most closely, I now send replies in my own voice again, filled with strange punctuation and the occasional typo. (This essay is one of those cases as well. I wrote it, and my editor polished it.)

I still find the AI assistant helpful for refining routine correspondence. But I have found it can get in the way of connecting with the people closest to me. Sometimes, a few mangled sentences are all they need.

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I used to be homeless. That experience shapes my science

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From ScienceMag:

Checking emails between flights at the airport, I was excited to see long-awaited reviews for a paper I had submitted with my Ph.D. adviser. It was an editorial in which I proposed a framework for identifying and mitigating conflict between urban coyotes and people experiencing unsheltered homelessness. Based on my thesis research, it contained more of my heart and soul than any I had previously written. But the reviews were resoundingly negative. I appreciated the valid scientific criticisms, but I struggled with comments questioning our qualifications and expertise. One in particular froze me: “The authors are naïve about homelessness.” Nothing could be further from the truth.

Following a tumultuous home life, I spent my late teenage years and early 20s in and out of homelessness, sometimes living on the street, camping illegally, and living in a car. I earned a 2-year college diploma while working full time and living in an unheated camper without water or power through Canadian winters. I finished my undergraduate degree while working as a wilderness guide, camping through the summers and retreating to a different moldy basement bedroom each winter. Some combination of stubbornness, inertia, and a genuine curiosity about the natural world kept me going. I loved time outdoors, watching animals. I wanted a job where I could ask and answer my own ecological questions.

By the time grad school was an option, it was an obvious choice—after all, I would get paid for it! I accepted a position studying the effects of urbanization on coyote behavior. Fieldwork for this project led to the editorial.

It wasn’t easy to write. My sentences struggled to capture the enormity of the problems I had observed. In my fieldwork, I’d seen coyotes scavenging from encampments, eating low-quality food that would make them sick. Elsewhere, I’d collected coyote scat infected with a potentially deadly tapeworm, knowing the people in the encampments could be exposed but would struggle to access health care. These observations mingled with memories I wish I didn’t have. The unique smell of dumpster diving in a sleeping city. Laughing and braiding the hair of a friend who later died violently in the streets. I pushed those memories away to write as cleanly and objectively as possible.

Homelessness took things from me, but it also gave me things. I am observant. I am resourceful. I am phenomenal at camping. I thrive in bad weather. These skills have helped me walk so many worthwhile roads—as a professional wilderness guide, a recreationist comfortable solo camping in wild places, and, crucially, as an urban ecologist. I am comfortable conducting fieldwork in urban spaces where others might not be. It’s exactly this aptitude that let me notice the things I had described in my paper, which was eventually published at another journal.

I can’t know exactly what the reviewer who accused us of naïvety was thinking, but they seemingly never imagined an author of such a piece might have firsthand experience of homelessness. That assumption shook me: It suggested someone with my history did not belong in academia. It was not the first time I have felt that way. I recalled the way fellow grad students had expressed fear of a man sleeping in the entrance to a university building, and an urban ecology safety briefing that focused on the dangers of homeless people rather than on ways to communicate with or support people in need.

Many of the life experiences that bring diversity to science are invisible, or are sufficiently personal and taboo that we don’t talk about them—abuse, poverty, rape, addiction, a schizophrenic family member, a history of homelessness. Our assumptions about who researchers are and what their past lives looked like create an isolating landscape of erasure—an environment where certain histories are assumed to be absent, keeping the people who hold those histories from feeling they belong.

For years, I worked hard to hide my history of homelessness. Now, I am more neutral—it was a challenging and sometimes unpleasant chapter, like puberty, or, more recently, learning Bayesian statistics. I am committed to not letting my history define me. But I also don’t want my colleagues to assume no scientist could have a past like mine.

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Science’s ‘Dance Your Ph.D.’ contest is open again

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From ScienceMag:

Do you have what it takes to win Science’s “Dance Your Ph.D.” competition? We want you to top this year’s winning entry from a scientist who translated physics’ piezoelectric effect into dance. 

As always, we’re challenging scientists to explain their research obsession with fancy footwork, but no PowerPoint slides or jargon. It doesn’t matter whether you’re just starting your Ph.D. or you completed it decades ago; you just need imagination and the ability to keep a beat.

The annual contest, in its 19th year and again sponsored by the AI and quantum technology company SandboxAQ, features four traditional categories (physics, biology, chemistry, and social science). Winners in each category take home $750. The overall winner of those categories gets an extra $2000. You can see the full slate of past winners here and the rules and other key information here.

Beyond that, it’s simple: Go dance some science, create a video of it, and upload it to YouTube. The deadline for submissions is 29 January 2027.

To enter the contest, submit here. We’ll announce the winner by March 2027.

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Could your chatbot tip off a scientific rival? It’s possible, researchers say

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From ScienceMag:

A familiar pattern is beginning to emerge when artificial intelligence (AI) makes a scientific breakthrough. After an AI company announces the feat, a researcher who uses that company’s tool claims it may have ripped off their work.

On 8 September, for example, OpenAI said its agents had solved the Navier-Stokes problem, one of the biggest open challenges in math. But mathematician Tristan Buckmaster of New York University publicly suggested the company had benefited from extensive work he and a colleague, Levent Alpöge, had done using OpenAI’s coding assistant, Codex.

Two weeks later, Anthropic said its model, Claude, had found a new enzyme system. Mario Rodríguez Mestre, a computational biologist at the University of Copenhagen, soon told The New York Times his group had been studying the same systems since 2022, and had shared unpublished drafts with Claude.

OpenAI says an investigation confirmed Buckmaster’s Codex work from the prior 2 months could not “have influenced the model or the math results it produced in any way.” Anthropic says Claude was “not trained on any user transcripts.” Neither researcher says they can prove otherwise.

Still, scientists are now asking an uncomfortable question about tools many use daily. When you type an unpublished idea into a chatbot or coding agent, could it end up being used by the company that built the model—or a rival who asks the right question a year later? And what can you do to reduce the risk?

Many AI companies give researchers—who are also potential customers—free or reduced-price access to their tools, and some worry there is a quid pro quo. “People working in a university environment are a much more valuable segment of the market,” says Mohammad Hosseini, who studies the ethical implications of using AI in research at Northwestern University. “And perhaps their information is used more frequently to train these models.”

In principle, an unpublished proof or paper could become a part of a model’s next training run, he and others say. But can such a tiny drop in the vast ocean of training material still make a splash? There’s some evidence it can. For example, a preprint published in January showed chatbots could reproduce most of a Harry Potter novel nearly word for word.

But such memorization isn’t really the threat for research, says A. Feder Cooper, an AI researcher at Yale University and co-author of the study. “The data sets that these models are trained on are absolutely massive … too large from an information theoretic standpoint for the models to memorize all of it,” Cooper says. But he adds that an AI model doesn’t need to memorize a chat word for word for it to be useful. “It just needs to get enough of an understanding from the chat … to use that information.”

Indeed, a single user’s chats may not matter at all. What may matter more is how thousands of chats add up. AI companies routinely analyze conversations in bulk to see how people use their products. Anthropic, for example, has described a system called Anthropic Insights that summarizes millions of chats and sorts them into clusters. To protect privacy, it discards clusters with small numbers of users, but it doesn’t say what that threshold is.

Such analyses are the likeliest way sensitive research information could leak, says AI privacy researcher Niloofar Mireshghallah of Carnegie Mellon University. The risk isn’t copying, but a company noticing from aggregate chats that a problem is close to being solved and putting its resources behind it. “That gives them enough hints of: ‘Oh, this is solvable, let’s go do it.’”

The privacy safeguards on these analyses may also fail researchers, Mireshghallah adds. They protect users by hiding them among thousands of others with similar chats, but a small number of researchers sending many queries about the same niche problem can still stand out. “Average case privacy methods don’t protect the outliers,” Mireshghallah says.

No setting makes a chatbot fully private, but researchers say these steps make leaks much less likely:

Use an enterprise account

Universities that license ChatGPT, Claude, or Gemini typically sign contracts that bar the company from training on user data, whereas consumer accounts get no such protection. If “you’ve been using a personal account for your research, switch to your university’s enterprise account,” says Jennifer King, privacy and data policy fellow at Stanford University.

Even with an enterprise account, however, “no training” doesn’t always mean “no use.” California State University’s contract with OpenAI, shared by CalMatters, lets the company “process information derived from [customers] that has been deidentified, anonymized, and/or aggregated.” King suggests researchers check the fine print of their institution’s AI deals.

Turn off training on personal accounts

If you use a personal account, switch on the setting that stops your chats from being used for training.

Watch for exemptions

On ChatGPT, rating a response with a thumbs up or down “can make the entire associated conversation eligible for training,” even if you’ve opted out, Mireshghallah notes in a recent analysis of company policies. Anthropic keeps feedback data, too, including the related conversation, for 5 years, and may use it to train AI models. Other providers have similar policies.

Chats that AI systems flag as potentially unsafe, such as those touching on bioweapons or mental health, are another possible carve-out. For example, when Anthropic’s systems flag a chat, the company keeps the inputs and outputs for up to 2 years, and other kinds of safety-related data for up to 7 years

Practice data hygiene

Once a project is complete, King suggests downloading your chat record, “then maybe delete it.” A log of your AI use may be needed for replication or disputes, but it needn’t stay with your provider. Deleting isn’t watertight. Anthropic, for example, says deleted chats leave its servers within 30 days, but it can hold onto them longer for safety reasons. And deletion doesn’t remove data from models already trained on them.

Host your own model

For those savvy enough, the most private option is running an open-weight model on your own hardware. But that does mean “moving off of some of these platforms that host it for you, have nice tooling, and do a lot of things as part of the product,” Cooper says.

If it’s really sensitive, consider not using AI

The decision often boils down to weighing potential risks against the rewards. But even “not sending stuff [to AI] yourself will only get you so far,” Cooper says, pointing out that a peer reviewer or colleague could run a manuscript through AI even if you don’t.

As for Buckmaster and Mestre, both still use AI, but want much more control over where their work goes. “I still use AI extensively and believe it can be enormously useful,” Mestre says. “What has changed is how much control and visibility I want over the data, infrastructure, and actions of the agent.” Academics, Buckmaster says, “need to somehow push back and take some sort of ownership of our user data.”

Science’s AI in Science reporting initiative is supported by Ray Rothrock & family.
Editor’s note: Niloofar Mireshghallah is a faculty member at the Future of Life Institute, which has provided funding to the Tarbell Center for AI Journalism.

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Former baseball star Brad Lidge rolls the dice on second career as archaeologist

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From ScienceMag:

As a star relief pitcher for the Philadelphia Phillies when they won the 2008 World Series, Brad Lidge would chew gum only in odd-numbered innings and go unshaven for days during a “hot” streak. Professional athletes are notorious for indulging in such quirky behaviors in hopes of improving their chances of success on the playing field. Now an archaeology Ph.D. student at the University of Colorado (CU) Boulder, Lidge thinks the same might have been true of the Etruscans, a pre-Roman civilization in central Italy whose widespread use of dice suggests they were seeking divine intervention 2800 years before Lidge became a sports hero in Philadelphia.

Hints of what would become Lidge’s second career started early. Growing up in Colorado, a rich area for paleontology, Lidge enjoyed searching for dinosaur bones when he wasn’t playing baseball. After hanging up his cleats in 2012, he rekindled his passion for buried treasure as a volunteer on a dig at the site of the ancient Roman city of Carsulae. And he got lucky.

“On my first day I flipped over some soil and there lay some Roman coins—a fourth century [C.E.] coin from [when] Constantine [was emperor],” he recalls. “I couldn’t believe they were right there underneath our feet. It brought me an extreme sense of joy, and at that point, I kind of knew what I wanted to do next.”

Lidge didn’t have to worry about making a living as an archaeologist, having earned some $55 million during his 11 seasons as a major leaguer. But he didn’t want to rely on his fame to break into the profession. “There’s a lot of imposter syndrome for a retired athlete entering into a new field, and I wanted to do it the right way,” he explains. So while he continued to work as a volunteer on digs in Italy, he enrolled in an online master’s program at the University of Leicester and earned his degree in 2017.

Now, 2 months from his 50th birthday, Lidge hopes obtaining a Ph.D. will be the final step in a path to directing his own dig. “If you don’t have those initials after your name,” he says, “it is very difficult to work with the governing bodies that must give their approval before you can direct a project.”

His adviser, CU anthropologist Gerardo Gutiérrez, has no doubt Lidge will do well if given the chance. “He’s very mature, he’s serious about his goals, and he’s already famous, so he’s not doing it for his ego,” Gutiérrez says. “I wasn’t aware that he was a famous baseball player because he didn’t mention it in his application.”

While working in Italy, Lidge became fascinated with the inscriptions on Etruscan artifacts. That eventually led him to Anthony Tuck, a University of Massachusetts Amherst archaeologist who directs excavations at Poggio Civitate, an Etruscan settlement dating from the eighth century B.C.E.

“Brad is deeply curious and incredibly committed to learning how research is done,” Tuck says. “So it took him no time at all to get up to speed on what we do.” That work includes a summer school for undergraduates from around the world that Tuck runs at the site.

Being a mentor to younger players in the Phillies’s organization, Lidge believes, has served him well when teaching at Poggio Civitate. “With the Phillies I loved being able to sit down with the young guys and teach them the nuances of the game,” he explains. “Those leadership skills have helped me when we’re out there at an excavation and in the classroom. … It’s also really cool to see the look in their eyes when a student discovers something really old and I can help them understand how special and unique it is.”

Poggio Civitate is where Lidge and Tuck found those dice. In February they co-authored a paper discussing how the dice might have been part of rituals to divine upcoming events as well as for gaming or other recreational activities.

In describing their quest to understand what those objects might have meant to its residents, Tuck and Lidge note the potential similarity to another set of “irrational, ritualized behaviors designed to ameliorate performance … among a subset of baseball players, relief pitchers.” It’s almost certainly the only reference in the scientific literature to flame-throwing hurlers like Lidge, who earned the nickname “Lights Out” after he posted a perfect record—41 saves in 41 appearances—during that magical 2008 season.

Brad Lidge celebrates a World Series championship
In 2008, Brad Lidge celebrated striking out the final opposing batter to win the World Series for the Philadelphia Phillies.Jerry Lodriguss/The Philadelphia Inquirer/TNS via Zuma

To gain additional expertise, Lidge also sought out Italian archaeologist Luca Nejrotti, who directs another Etruscan site. “I went there to up my game in terms of understanding data sets and geographic information systems and x-ray fluxes.” Lidge bought himself a portable x-ray fluorescence machine, a purchase enabled by his baseball earnings, which can be used to determine the elemental signature of certain kinds of materials. That can come in handy, say, for identifying the clay used in a particular piece of pottery and, thus, its likely origins.

His earnings as a baseball player have also helped Lidge literally pay back the warm welcome he enjoyed from archaeologists in launching his second career. In 2010, while Lidge was still on the Phillies, archaeologists Jennifer Houser Wegner and Josef Wegner, curators in the Egyptian section of the Penn Museum, gave him a tour of the museum. Now, Lidge is helping fund Josef Wegner’s ongoing excavation at Abydos, one of the oldest cities in ancient Egypt. He’s also become a major donor to the museum, which this year appointed him to its Board of Advisors.

Interpreting ancient Etruscan symbols may seem worlds away from throwing a small orb past other elite athletes. But Lidge says he’s never been satisfied doing only one thing.

“As a professional baseball player, you’re at the field for 9 or 10 hours a day, and you need time off,” he says. “So having something different to do that you really enjoy is really important. That’s what archaeology has been for me. And I’m just lucky to have had a chance to pursue my passion.”

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