Working with great students is a very very rewarding aspect of being a professor. And when items like best paper awards come along, its icing on the cake. Congrats to @gavinkerrigan.bsky.social (now at Oxford) and Kai Nelson (now at Berkeley) for their terrific work on our AI-Stats paper.
Padhraic Smyth
@padhraicsmyth.bsky.social
ML researcher, teacher, professor, Dad, Irish, ...
🚨New preprint and our results are rather concerning.. We find the "boiling frog" equivalent of AI use. Using large-scale RCTs, we provide *casual* evidence that AI assistance reduces persistence and hurts independent performance. And these effects emerge after just 10–15 minutes of AI use! 1/
If you are have any interest in the history of ML from the 70s/80's onwards, this podcast series by Tom Mitchell is well worth your attention: www.youtube.com/playlist?lis...
Machine Learning: How Did We Get Here? - YouTube
Tom Mitchell literally wrote the book on machine learning -- the technology that underlies today's trillion dollar artificial intelligence (AI) industry. In ...
youtube.com
if your specific niche is also "bizarre intertwingled anecdotes about 1950s-1990s computer scientists" i have built your holy grail: just took a thousand oral histories from the @computerhistory.bsky.social museum and made them fully searchable and deeply interconnected 🎉welcome to f0lkl0r3.dev
There's growing evidence that LLMs can p-hack. But p-hacking also points to something bigger: a data science multiverse of defensible analytical choices. We wrote a paper (arxiv.org/abs/2602.18710) on using LLM agents to map this multiverse systematically. 🧵
🥁🥁🥁 Newly out from us today in Science Advances: “Biased AI Writing Assistants Shift Users’ Attitudes on Societal Issues”. Large Language Models are providing users with autocomplete writing suggestions on many platforms. Could these suggestions shift users’ own attitudes? (spoiler: YES) (1/7)
Michael @mkearnsphilly.bsky.social ) and I wrote a blog post about our experiences using AI for research, and our thoughts on what these developments will mean for research, publication, and education: www.amazon.science/blog/how-ai-...
How AI is changing the nature of mathematical research
What machine learning theorists learned using AI agents to generate proofs — and what comes next.
amazon.science
This is worth considering, but I'm skeptical. Nobody likes being criticized, and authors are likely to take it out on the criticizer. I expect that this will inflate the positivity of reviews. The "prestige" of being listed as a reviewer is currently so minimal that it's not worth the danger.
Saving peer review from AI slop requires getting rid of anonymous submissions and reviews togelius.blogspot.com/2026/03/savi...
How AI slop is causing a crisis in computer science www.nature.com/articles/d41...
How AI slop is causing a crisis in computer science
Preprint repositories and conference organizers are having to counter a tide of ‘AI slop’ submissions.
nature.com
I was lucky to get a sneak preview of Advait’s talk and it is SO GOOD. I wish everyone building AI would watch this.
Microsoft senior researcher, Advait Sarkar, recently presented at TED AI Vienna, where he spoke about AI’s role in elevating human thought.
The problem is us, with our Paleolithic vulnerabilities, our FOMO, our susceptibility to snake oil salesmen and the ELIZA effect. Say no to anthropomorphized tech solutionism and yes to stronger human institutions, fortified by ordinary technology. (11/11)
“To leave our students to their own devices — which is to say, to the devices of AI companies — is to deprive them of...the means to understand the world they live in or navigate it effectively,” Anastasia Berg writes. www.nytimes.com/2025/10/29/o...
Opinion | Why Even Basic A.I. Use Is So Bad for Students
nytimes.com
I cannot wait to celebrate TWENTY YEARS of #WiML at #NeurIPS in San Diego this December! 🎉🥳 Fun fact: The first #WiML was held in San Diego back in 2006! ❤️ Share your memories below, and come hang out on Dec 2! I will be there! I will be speaking! And have I mentioned I AM EXCITED?!?!?!
WiML turns 20! 🎉 For two decades, WiML has connected, inspired, and supported women around the world who are advancing the field of ML. As we celebrate this incredible milestone, we want to hear your story. 💜 ➡️ Share your reflections: shorturl.at/lxWM2 #WiML #WiML20Years #WiML20th
Nice writeup in @caltech.edu news about the impact of the #Visipedia project in Computer Vision and Citizen Science
Pietro Perona's Vision: Visipedia and Its Lasting Impact on Computer Vision
The machine learning-driven system for identifying visual information has grown the citizen-science apps Merlin and iNaturalist, led to the development of key datasets, and jump-started the field of i...
eas.caltech.edu
Not being an AI-doomer, but having experienced in my own department over the past 7 years a steady erosion of faculty governance norms and diminished prioritization of research-oriented pedagogy, this tracks. Let faculty and faculty interests lead the way, rather than administrators/regents
"AI returns to the university as part of a broad effort to further corporatize universities, vocationalize higher-education instruction, and diminish both research and research-based pedagogy."
We (UC Irvine) are hiring for a faculty position (any level) in AI/ML/vision/NLP/etc. If you would like to work in a great department with great colleagues please apply! and please distribute to students, researchers, faculty who may be interested. More info here: drive.google.com/file/d/1ZyY5...
Now that school is starting for lots of folks, it's time for a new release of Speech and Language Processing! Jim and I added all sorts of material for the August 2025 release! With slides to match! Check it out here: web.stanford.edu/~jurafsky/sl...
Speech and Language Processing
Speech and Language Processing
web.stanford.edu
📣 Please share: We invite submissions to the 29th International Conference on Artificial Intelligence and Statistics (#AISTATS 2026) and welcome paper submissions at the intersection of AI, machine learning, statistics, and related areas. [1/3]
Every rich person is going to tell *you* how great AI teaching is while sending *their* kids to the kind of schooling the Ancient Greeks would recognize. I just wish everyone would think about why that is.
I think we’re on the cusp of mass attempts to automate teaching, and I also think it is going to be a massive wasteful failure in ways that will make the “learning loss” of the pandemic look like a speed bump next to a mountain.
Our computer vision textbook is now available for free online here: visionbook.mit.edu We are working on adding some interactive components like search and (beta) integration with LLMs. Hope this is useful and feel free to submit Github issues to help us improve the text!
Foundations of Computer Vision
The print version was published by
visionbook.mit.edu
I've heard this personally from multiple PMs at AI companies. Students are one of the biggest demographics and they need to "break in" and have even more usage to improve their metrics. Classic corporate economic incentives
AI companies in the US gave access to their systems to students for free during college exams China disabled access to AI systems during nationwide college exams www.theverge.com/news/682737/... Feel free to draw your own conclusions
This Senate proposal advanced by Sen Cruz would cancel new and existing State laws on any aspect of tech use including civil rights, consumer protection, privacy, fraud, safety for kids, accessibility, and more. In short, we’d lose the few laws we have that ensure responsible AI use. #killthebill
Don’t be confused: The Senate Republican AI language includes the EXACT SAME AI moratorium as the House bill. Almost word-for-word. This is a complete, 10-year ban on state AI regulation. Period.
People keep plugging AI "Co-Scientists," so what happens when you ask them to do an important task like finding errors in papers? We built SPOT, a dataset of STEM manuscripts across 10 fields annotated with real errors to find out. (tl;dr not even close to usable) #NLProc arxiv.org/abs/2505.11855
Llama 3.1 70B contains copies of nearly the entirety of some books. Harry Potter is just one of them. I don’t know if this means it’s an infringing copy. But the first question to answer is if it’s a copy at all/in the first place. That’s what our new results suggest: arxiv.org/abs/2505.12546
Extracting memorized pieces of (copyrighted) books from open-weight language models
Plaintiffs and defendants in copyright lawsuits over generative AI often make sweeping, opposing claims about the extent to which large language models (LLMs) have memorized plaintiffs' protected expr...
arxiv.org
A call for scientists to stand up for scientific freedom as well as funding: www.nature.com/articles/d41...
@candicemorey.bsky.social and I were just talking about this. Students, I think, are still (rightly) nervous about submitting LLM-produced work, but they are using it to summarise papers they struggle to read. And it shows in their subsequent writing. It's "just reading the abstracts", but worse.
This paper makes important point that we're not talking about impact of AI on reading enough. Marking work that's full of AI is demoralising but in some ways, the threat AI poses to comprehension is bigger than the threat to what students produce... www.tandfonline.com/doi/full/10.... #AcademicSky
Because we must build good things while we scream about the bad, I have started a "Data for Good" team @data-for-good-team.bsky.social that partners with organizations needing short-term data science help. We have three projects ongoing & will add more as our capacity grows. data-for-good-team.org
Congratulations to Rich Sutton and Andrew Barto on receiving the Turing Award in recognition of their significant contributions to ML. I also stand with them: Releasing models to the public without the right technical and societal safeguards is irresponsible. www.ft.com/content/d8f8...
Turing Award winners warn over unsafe deployment of AI models
Two pioneers of reinforcement learning have won the $1mn prize from the Association for Computing Machinery
ft.com
My new paper "Deep Learning is Not So Mysterious or Different": arxiv.org/abs/2503.02113. Generalization behaviours in deep learning can be intuitively understood through a notion of soft inductive biases, and formally characterized with countable hypothesis bounds! 1/12