Luis Lo

Why am I obsessed with this? LLMs do not preserve our intentions or diversity of thought in writing, and they’re already being adopted en masse. More than 1 billion people worldwide use them on a weekly basis. Existing work has shown that for individual scientists, using LLMs to generate papers increases your productivity and impact, even though it constricts science’s overall focus. In our study we show that even though participants who rely on LLMs say their writing is significantly less creative and not in their voice, they are paradoxically equally satisfied with the output. So, the adoption of LLMs is not going to slow any time soon. But it’s already affecting our cultural institutions and the way we conduct science. We urgently need more research into how massive, widespread LLM adoption will affect our science, politics, and culture.

This is a problem, because LLM-generated text is already infiltrating a lot of our cultural and scientific institutions. For example, we look at the 21% of ICLR 2026 reviews that were found to be LLM-generated, and find that they actually focus on different scientific criteria than human reviews! e.g. LLMs increase focus on scalability by +111% vs. humans.

The paper I’ve been most obsessed with lately is finally out: nbcnews.com/tech/tech-news…! Check out this beautiful plot: it shows how much LLMs distort human writing when making edits, compared to how humans would revise the same content. We take a dataset of human-written essays from 2021, before the release of ChatGPT. We compare how people revise draft v1 -> v2 given expert feedback, with how an LLM revises the same v1 given the same feedback. This enables a counterfactual comparison: how much does the LLM alter the essay compared to what the human was originally intending to write? We find LLMs consistently induce massive distortions, even changing the actual meaning and conclusions argued for.

Si escribir ya no exige esfuerzo mental, el aprendizaje desaparece. Hay una crisis silenciosa en las universidades: el uso masivo de IA para hacer tareas. No basta con prohibirla ni con detectores fallidos. Hay que rediseñar la evaluación. 🎓🤖 The New York Times: Cuando “incluso los alumnos buenos” usan IA para evitar el trabajo, el problema no es disciplina: es diseño institucional. La universidad debe volver a exigir demostraciones en tiempo real: ensayos en clase, exámenes orales, evaluación auténtica. nytimes.com/es/2025/08/27/…

#ringroyale por un promedio de 3 por TV 📺 Gracias de corazón. Viene lo mejor 👑🥊

Juggling too many AI research tools? Here's your research toolkit, organized by function AND price so you know exactly what you're paying for. Some tools cost $500+ per year. Others are completely free. 𝗙𝗿𝗲𝗲 𝗽𝗼𝘄𝗲𝗿𝗵𝗼𝘂𝘀𝗲𝘀 𝗜'𝗱 𝘀𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵: — Semantic Scholar (search engine that actually understands context) — Research Rabbit (maps citation connections/ network) — NotebookLM (turns your papers into conversations) — Consensus (generous free version that gives instant scientific consensus) 𝗙𝗼𝗿 𝘀𝗲𝗿𝗶𝗼𝘂𝘀 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝘁𝗲𝗮𝗺𝘀: — SciSpace ($20/month: great multi-purpose tool) — Undermind ($20/month: finds papers you'd never discover) — Litmaps ($12.50/month: visual literature mapping that saves hours) — Jenni ($20/month: AI writing assistant built for academic papers) The best research tool is the one you actually use consistently. Not the most expensive one! Here are my recommended tools with discount codes: 🔗 aitools.razia-aliani.com 💬 Tell your favorite tool(s) ----------------------- Useful find? Pass it on! 🔄 𝐑𝐞𝐩𝐨𝐬𝐭 & click @RaziaAliani + follow + 🔔 I test AI tools to simplify your #research & #analysis (& 𝘤𝘰𝘯𝘥𝘶𝘤𝘵 𝘵𝘳𝘢𝘪𝘯𝘪𝘯𝘨𝘴 𝘰𝘯 𝘵𝘩𝘦𝘮)

🔴 Hugo López-Gatell ocupa un cargo como ministro en la misión permanente de México en Ginebra; con bajo perfil, no participa en reuniones, consultas ni foros, pese a percibir más de 12 mil euros mensuales y prestaciones. 📺 #MILENIO22h con @AlexDominguezB

50% of all relationship advice on Reddit is “leave.” 15 years of data, 52 million comments, and the trend line only goes one direction. A researcher filtered r/relationship_advice down to 1,166,592 quality comments and tracked what people actually recommend. In 2010, “End Relationship” sat around 30%. By 2025, it’s approaching 50%. “Communicate” dropped from 22% to 14%. “Compromise” collapsed from 7% to 3%. “Give Space” fell from 25% to 13%. Every category that requires patience lost ground every single year. The one category growing faster than “leave” is “Seek Therapy,” which went from 1% to 6%. The subreddit is slowly learning to say “this is above my pay grade.” Train a model on this dataset and it would absolutely tell people to break up. The training data is 50% “leave” and climbing. The model wouldn’t be broken. It would be accurately reflecting what 52 million commenters actually believe about your relationship. A 50% prior that you should leave, a 14% prior that you should talk about it, and a 6% prior that you need a professional. That’s not LLM psychosis. That’s the median human opinion on your relationship, backed by the largest advice dataset ever assembled.

After 6 months of using NotebookLM, I can say it's the research tool that has revolutionized my workflow the most. But only because I learned these 10 prompts. Here's the complete system that turns 200 pages into clear answers in under an hour:

Puedo expresar que como Mexicana por primera vez escucho entonar el Himno Nacional Mexicano de una manera asombrosa a alguien durante una pelea de box las notas entonadas a la perfección no hubo ningún error al cantarlo, felicidades Elaine lo hiciste increíble

I found a way to read a research paper the way academics actually read them. A friend of mine at Cambridge showed me her Claude workflow. I thought she was just fast. Then I watched her pull apart a methodology section in twenty minutes that her seminar group had spent a week discussing without fully understanding. Here's exactly what she did: First: she didn't ask Claude to summarise the paper. That's what everyone does. They paste in a paper and ask for a summary. They get a clean paragraph. They feel like they've read it. They move on. That's not reading. That's skimming with extra steps. She did something completely different. She read the paper herself first. All of it. Without Claude. Then she asked: "Based on the methodology and results sections alone, what can and cannot be legitimately concluded from this study? Now read the abstract and tell me where the authors overreach." She wasn't asking Claude to read the paper for her. She was using it to test whether the paper was actually saying what it claimed to be saying. The gap between those two things is where most students get lost. They read what the authors claim and treat it as what the authors found. An experienced academic never does that. She learned not to in twenty minutes. But the next part is what I keep thinking about. She asked: "What did this study not measure that would have significantly strengthened or weakened the central claim? What is the authors' methodology quietly assuming without ever stating it?" Most students read a methodology section to understand what the researchers did. She read it to find what they didn't do and what they hoped nobody would notice. Those are completely different acts of reading. One produces a student who can describe a study. The other produces a researcher who can evaluate one. Her seminar group spent a week on the same paper and never reached that question. Then she did something most students never think to do. She tested the paper against itself. "If I tried to replicate this study with a different population in a different context, what would most likely change about the results? What does that tell me about how far the authors' conclusions actually travel?" Most published claims are presented as general. Most are actually specific. That question finds the line between the two every time. Once you see it you cannot read a paper without looking for it. It changes what you take from every study you ever read after that. Then she mapped the paper's place in the conversation. She asked: "What debate is this paper entering? Who wrote the work this paper is responding to and what would those authors say back? Where does this paper sit in the argument that was already happening before it was written?" She stopped reading papers as standalone objects that day. Every paper is a reply to something. Most students never find out what. She found out in five minutes and it changed the way the paper meant something entirely. A paper you understand in isolation is information. A paper you understand inside its conversation is knowledge. Then she ran the final check. Before closing the paper she asked: "What is the single most important citation missing from this paper that every serious researcher in this field would consider essential? What conversation is this author not in that they should be?" She found a foundational paper the authors had never cited. Not because they were careless. Because they came from a slightly different tradition and had a blind spot they weren't aware of. That blind spot explained a gap in their argument she hadn't been able to name until that moment. She walked into the seminar and named it. Her supervisor stopped the discussion and asked her to explain how she'd found it. She told him she'd asked the right questions of the paper instead of just reading it. He told her that was exactly what twenty years in academia teaches you to do. She'd been doing it for three weeks. Here is the actual workflow. Five questions. In order. Question one: what can and cannot be legitimately concluded from the methodology and results alone? Where does the abstract overreach? Question two: what did this study not measure that would have changed what it found? What is the methodology quietly assuming it never defends? Question three: if you replicated this with a different population or context, what changes? How far do the conclusions actually travel? Question four: what debate is this paper entering? Who is it responding to and what would those people say back? Question five: what is the most important paper missing from the bibliography? What conversation is this author not in? Most students spend three years at university reading papers from the outside. Those five questions put you on the inside in twenty minutes. Claude didn't read the paper for her. It taught her the questions that experienced academics ask automatically after years in a field. She just learned them earlier. The papers didn't change. The questions did. Most students finish a paper feeling like they've understood it. She finished a paper knowing exactly what it proved, what it didn't prove, where it sat in the field, and what it was quietly hoping nobody would ask. That is not a faster way to read. It's a completely different thing to do with a paper. And almost nobody teaches it directly.

🍿Paralelismos Cinematográficos... #RingRoyale

Con que así se ve La Paz mundial #RingRoyale Grande Adame y Trejo

Ni la IA tiene estos crossovers jajaja #RingRoyale

I think refereeing papers is increasingly going to require enough knowledge and judgment to tell when an author has actually read the literature they are citing. I’d say half of my reject recommendations lately have come from the fact that the authors evidently don’t understand the context.

Me parece muy interesante este documento de la @upvehu sobre el uso de la IA generativa en la universidad. No porque prohíba. Sino porque baja a tierra una conversación que muchas universidades todavía no han aterrizado del todo. La EHU deja claro que el uso de IA generativa no está prohibido, pero que debe hacerse con transparencia, atribución adecuada y uso ético. Y hay una idea de fondo que comparto bastante. En la universidad cada vez tiene menos sentido centrar toda la evaluación solo en el entregable final, especialmente cuando hablamos de textos escritos. Lo que gana peso es el proceso de elaboración, la participación del alumnado, las evidencias de aprendizaje y, en muchos casos, las pruebas orales o presenciales. El documento también me parece muy provechoso porque concreta principios que muchas instituciones todavía formulan de manera demasiado genérica. Habla de equidad, ética, confidencialidad, honestidad académica, transparencia, formación, supervisión, sostenibilidad y aportación social. Y además introduce algo clave. El uso de IA en trabajos evaluables debe declararse explícitamente, especialmente en TFG, TFM o tesis. Otro punto que me parece acertado es que la EHU no se queda en la lógica fácil de la prohibición. Reconoce, de forma bastante realista, que detectar el uso de IA no siempre es fiable y que muchos detectores generan errores. En lugar de apoyarse en eso, plantea criterios de uso responsable, ejemplos de citación y orientaciones que sí pueden ayudar a docentes y estudiantes. Ahora bien, publicar principios y recomendaciones es un paso importante, pero no suficiente. La dificultad empieza cuando una universidad tiene que traducir todo eso en criterios compartidos, rediseño de tareas, formación docente, feedback al alumnado y decisiones coherentes entre asignaturas, titulaciones y centros. Ahí es donde muchas instituciones todavía están lejos de una implementación madura. Cada vez tengo más claro que las instituciones que mejor lo están haciendo no son las que reaccionan con miedo ni las que abrazan la IA sin criterio. Son las que están construyendo marco, lenguaje común y decisiones aplicables. Me interesa mucho saber qué estáis haciendo en vuestras universidades o centros educativos. Y también si ya estáis viendo usos interesantes de la IA por parte del profesorado para mejorar el feedback al alumnado sin vaciar de sentido la evaluación. En el primer comentario te dejo el enlace al documento y también a mi newsletter, donde comparto este tipo de recursos, análisis y aplicaciones reales. Gracias a @begobrosa por compartírmelo. #edtech #IA #AI #liderazgo

Sergio Mayer regresó como si el cargo fuera suyo por naturaleza. Ya retomó su oficina y hasta le restringió el acceso a su suplente, que legalmente sigue en funciones como diputado federal. Y ahí está retratado, completito. No entiende el servicio público como un encargo institucional. Lo entiende como propiedad personal, como camerino, como espacio privado al que solo entra quien él decide. Por eso Sergio Mayer representa tan bien al Morenato: soberbia, abuso, confusión entre lo público y lo propio, y una obsesión enfermiza por el control. No importa la ley. No importa la forma. No importa quién esté en funciones. Lo único que importa es el ego del personaje. Más que legislador, Sergio Mayer se comporta como dueño temporal del presupuesto, de la oficina y del show.

Here is a list of eight FREE training modules covering different stages in a systematic review by the Queen's Univeristy Library. Modules on: • Introduction to systematic reviews • Formulating review questions and protocols • Searching for eligible studies • Selecting studies • Extracting data • Assessing risk of bias • Interpreting and disseminating results • Utilizing software tools for reviews Follow Silvi on LinkedIn for more tips and free resources on systematic reviews and academic writing. linkedin.com/feed/update/ur…

➡️ | FISCALÍA RETIRA TODOS LOS CARGOS CONTRA DASHIA ROCÍO Dashia iba a denunciar el abuso de su padre biológico cuando fue detenida y acusada de ser parte del CJNG. Querían encerrarla por varios años, pese a que la carpeta de investigación estaba llena de inconsistencias. El caso tuvo que ser viral para exponer esta injusticia. Primero, le cambiaron la medida cautelar para llevar su proceso en libertad. Salió de Barrientos justo para celebrar Navidad con su familia. Y pues hoy la @FiscaliaEdomex se ha desistido de su acusación y Dashia queda absuelta. Aquí el tema es: ¿Cuántas carpetas de investigación son fabricadas —tanto en esa entidad como en todo el país— con el único objetivo de silenciar inocentes?

@CAMegalopolis De las 19 y lo acaban de poner, no se supone es de las 20 horas. Jajajaja son un chiste, si ni en eso son correctos.

SE SUSPENDE LA CONTINGENCIA AMBIENTAL ATMOSFÉRICA POR OZONO EN LA ZONA METROPOLITANA DEL VALLE DE MÉXICO Más información: gob.mx/comisionambien…