Emre Kıcıman

‘It’s a nightmare.’ U.S. funding cuts threaten academic science jobs at all levels “There is a lot of pressure to essentially leave the country or not pursue research,” one Ph.D. student says

I can't stress enough how close U.S. science is to the cliff.

"Numbers released in May by the National Science Foundation (NSF) indicate that if Congress approves the cuts to the agency proposed by the White House, the number of early-career researchers it supports could fall by 78%" (@science.org)

Very true. In our causal tutorial slides we point at the edges in a DAG and say the edges we included aren’t the assumptions, the edges we deleted are the assumptions. (Never mind nodes!)

Having said that, LLMs are a useful tool for brainstorming what might be missing, complementing domain experts

Congratulations @kous2v.bsky.social!

Want to learn more? Check out our paper! written with a fantastic group of coauthors Su Lin Blodgett @amabalayn.bsky.social @angelinawang.bsky.social @841io.bsky.social @fcalmon.bsky.social @mmitchell.bsky.social @md.ekstrandom.net @rdbinns.bsky.social @s010n.bsky.social arxiv.org/pdf/2506.14652 7/7

Print screen of the first page of a paper pre-print titled "Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor" by Olteanu et al. Paper abstract: "In AI research and practice, rigor remains largely understood in terms of methodological rigor -- such as whether mathematical, statistical, or computational methods are correctly applied. We argue that this narrow conception of rigor has contributed to the concerns raised by the responsible AI community, including overblown claims about AI capabilities. Our position is that a broader conception of what rigorous AI research and practice should entail is needed. We believe such a conception -- in addition to a more expansive understanding of (1) methodological rigor -- should include aspects related to (2) what background knowledge informs what to work on (epistemic rigor); (3) how disciplinary, community, or personal norms, standards, or beliefs influence the work (normative rigor); (4) how clearly articulated the theoretical constructs under use are (conceptual rigor); (5) what is reported and how (reporting rigor); and (6) how well-supported the inferences from existing evidence are (interpretative rigor). In doing so, we also aim to provide useful language and a framework for much-needed dialogue about the AI community's work by researchers, policymakers, journalists, and other stakeholders."

We have to talk about rigor in AI work and what it should entail. The reality is that impoverished notions of rigor do not only lead to some one-off undesirable outcomes but can have a deeply formative impact on the scientific integrity and quality of both AI research and practice 1/

A chocolate cake with red and white decorations and lit candles shaped as the number 75. Bold text reads: ‘The NSF Turns 75 Today. What has it done over the past 7 decades?’ The background is a celebratory red with a spray-paint texture.

HAPPY 75th, NSF!

We’re celebrating this milestone by highlighting some of NSF’s most transformative accomplishments—innovations that have shaped our world and continue to drive progress in health, technology, the environment, and beyond.

Read on 🧵(1/11):

In this issue: our CHI 2025 & ICLR 2025 contributions, plus research on causal reasoning & LLMs; countering LLM jailbreak attacks; and how people use AI vs. AI-alone. Also, SVP of Microsoft Health Jim Weinstein talks rural healthcare innovation: msft.it/6013SHuu1

Carl Sagan when asked, "Are you a Socialist?"

Even more so when compared with the books left on the shelves.

Gift idea: what do you get for the AI researcher who has everything? 👇

Tariffs xkcd.com/3073

Seattle right now

Looking fwd to discussing career paths next week at the Society of Causal Inference & Online Causal Inference Seminar's joint webinar:

Exploring Career Paths in Pharma, Government, and Technology
w/Gabriel Loewinger and Natalie Levy
Tue Apr 15, 11:30am-12:45pm ET
sci-info.org/online-events/

Trump 2.0: an assault on science anywhere is an assault on science everywhere US President Donald Trump is taking a wrecking ball to science and to international institutions. The global research community must take a stand against these attacks.

Excellent statement from Nature’s editorial board.

The last section on “How to respond” is the most important.

www.nature.com/articles/d41...

IU's Observatory on Social Media defends citizens from online manipulation – the opposite of censorship When thousands of fake accounts controlled by an unknown actor flood social media with some story, and platform algorithms amplify these messages, real...

My friends and colleagues at IU are being intimidated for their work on social media’s harmful impacts on civic discourse. Here is why their work is vital.

osome.iu.edu/research/blo...

Sharing an announcement from the Society for Causal Inference annual meeting --- they are looking for student volunteers, in exchange for complimentary registration

More info: sci-info.org/annual-meeti...

The abstract deadline for SIGIR's Industry Track is coming up in just a few days, with a final deadline of Feb 27.

So I'm a big fan of Claude, and anyone can goof up, but this did make me laugh.

Collage of images from Microsoft Research India.

Since its launch two decades ago, Microsoft Research India produced extraordinary innovation in areas from health and education to agriculture and accessibility. Learn about the lab’s track record of technological advances: www.microsoft.com/en-us/resear...

Contrastive focus reduplication is such a fun construction.

languagelog.ldc.upenn.edu/myl/llog/Sal...

Happy International Day of Women in Science. The National Science Foundation’s list of flagged words includes both “Women” and “Female.”

We should not be allowing non-government employees to waltz in to government offices, and illegally get access to sensitive government and personal data, and get read and write access to critical software systems in multiple government agencies.

www.npr.org/2025/02/08/g...

YouTube video by The Obama White House White House Frontiers Conference

Obama, speaking in October 2016: "Government will never run the way Silicon Valley runs because, by definition, democracy is messy. And part of government's job, by the way, is dealing with problems that nobody else wants to deal with." 1/6 youtu.be/BikQFWNYct4?...

📣My team at Microsoft Research New York is hiring a senior researcher in AI, both broadly in AI/ML, and in some specific areas including science of deep learning and modular transfer learning.

Apply by February 7, 2025 on the link below.

jobs.careers.microsoft.com/global/en/jo...

Just like it's not a real Batman movie unless... bsky.app/profile/why....

Hi Alex, you'll have to help me out. Are you commenting only on my word choice in the msg above or are you responding to the content in the perspective article? Thanks

Artificial Intelligence–Based Copilots to Generate Causal Evidence While there is growing consensus that real-world data should play a larger role in generating causal evidence for health care, it is less clear whether and how AI can help. Current approaches to AI...

Real world data (RWD) analyses need diverse expertise in medicine/stats/causality. As a result, RWD causal analysis is slow and prone to error. AI tools can help.

Perspective in NEJM AI w/Maya Petersen, @amalaa.bsky.social, Chris Holmes, Mark van der Laan

ai.nejm.org/stoken/defau...

Good news for your end-of-year reading list: We've just released the Microsoft 2024 New Future of Work Report! It's packed with insights on how AI is transforming work.

aka.ms/nfw2024

#NewFutureOfWork #NFW2024 #AIResearch #WorkplaceInnovation #GenAI