In 2005, back with @lance.fortnow.com wrote that blog post, citations in CS were all numeric. I hope he would have the good sense now to prefer author-year citations and \citet where the citation is used as a noun. Which, importantly, do not require flipping to the end.
@pkrugman.bsky.social raises a vital point.
At $1 billion/day, six weeks of the air war on Iran would cost as much as a year of US military support for Ukraine. Which would do more for US national security?
The answer may be debated, but the question is essential for America.
@poleconukinar.bsky.social returns with a series of great seminars, some of which are theory-focused 👇
Call for ACM SIGAI Autonomous Agents Research Award 2025
The award is made for research excellence in autonomous agents, to recognise researchers in autonomous agents whose current work is an important influence
Nominations Deadline: 15th Jan 2025
Details: https://buff.ly/4ir8hJR
#SIGAIAward
If you are a senior researcher (i.e., associate prof level or later), and you're interested in moving to the University of Waterloo (best CS program in Canada) for the Canada Impact+ Research Chair (biggest chair position in Canada, $$$$$), email me. Discretion guaranteed.
DOJ "is seeking to intervene in state bar assocs’ disciplinary proceedings against its lawyers." "The move comes as career lawyers in the department have repeatedly balked at carrying out orders they view as unethical or which could cause them to lose their licenses." www.nytimes.com/2026/03/04/u...
Pragmatic & actionable interpretability are buzzwords arguing for mech interp to study concrete tasks.
It's the right instinct, but still underspecified. What counts as a concrete task? What's upper bound on performance? What do users need to know? Decision theory has answers!
A good reminder for academics always to scrutinize where potential research funding comes from. www.science.org/content/arti...
Krishna Dasaratha, Anant Shah
Network Interventions: Targeting Agents or Targeting Links?
https://arxiv.org/abs/2602.12897
[Thurs, 8:30-9:45am PT] CSLaw 2026: Empirics
Empirics session at #CSLaw2026:
- “Quantifying the Benefits of Securities Regulation”
- “Mining Legal Arguments to Study Judicial Formalism”
- “AI-Assisted Moot Courts: Simulating Justice-Specific Questioning for Supreme Court Oral Arguments”
#socialcal
[Wednesday, March 11, 1-7pm CT] IDEAL Workshop on Automation in the Workforce: Ethics, AI, and the Reconfiguration of Labor
Great speaker lineup at this IDEAL-Loyola workshop. Part of the IDEAL Special Program on Data Science with Strategic Agents. www.luc.edu/quinlan/whyq... #socialcal
(I'm not on the organizing team.) Posting to get it on my calendar, and hoping to see many of you there!
[June 3-5] FORC 2026 (at Harvard)
The 7th annual Symposium on Foundations of Responsible Computing (@forcconf.bsky.social) will be held on June 3-5, 2026 at Harvard University. responsiblecomputing.org/forc-2026/ #forc2026 #socialcal
I'll be honest, while I really enjoyed #NeurIPS2025, the sheer scale made it hard to get a ton of scientific value out of it.
Looking forward to attending more small and intimate events like #ALT2026 and #FORC2026, where one can engage deeply with the pertinent communities.
I'd love to have a collection of empirical AI papers that do a great job of this. If you know any, please share!
In papers studying empirical outcomes of AI in various situations, e.g. game theory, the *first thing* I want to know is: What in the study is still relevant on completely different models with superior abilities? Research must still be relevant next week. I won't read if the paper doesn't say.
A line graph showing NSF grant awards made through 2/27/26 for fiscal year 2026 compared with grant awards for fiscal years 2021-2025.
NSF Update (Awards through 2/27/26)
Directorates to follow
1/10
[Nov 8-11] FOCS (in NYC) #socialcal
The Call for Papers and submission server for #FOCS2026 are up!
⏰ Deadline: April 1, 5:00 PM EDT (21:00 UTC)
sanjeevkhanna.org/FOCS2026_CFP...
[April 1] FOCS Deadline #socialcal
It is also in this technical report by Marissa Beck and Marion Ott
"Revenue Monotonicity in Core-Selecting Package Auctions"
which gives necessary and sufficient conditions for monotonicity in core-selecting auctions. Hopefully it will be published somewhere more official soon.
Thanks the the dissemination reach of arxiv, I now have a reference for this, imho, important result. It can be found in Chapter 4 of Marion Ott's 2009 Ph.D. Thesis
"Second-price proxy auctions in bidder-seller networks"
I will cite it accordingly. publikationen.bibliothek.kit.edu/1000013645
Anti-fascism should have broad support across the American political spectrum. Elections need to be defended. Here's an open letter from retired professors at HBS in which we call for business leaders to address that need.
#econsky #academicsky
marketdesigner.blogspot.com/2026/02/an-a...
Hello Bluesky friends, I would be happy to have some more people trying out #socialcal for turning Bluesky posts into calendar events. Details. 👇
Prof. Curry presenting "Aligned Textual Scoring Rule".
Great presentation by UIC Prof. Michael Curry on
"Language Models and Text Elicitation Mechanisms"
We have an upcoming #IDEAL workshop on this topic on May 1. Pictured, Prof. Curry is overviewing our recent joint paper "Aligned Textual Scoring Rules". arxiv.org/abs/2507.06221
Prof. Curry presenting "Aligned Textual Scoring Rule".
Great presentation by UIC Prof. Michael Curry on
"Language Models and Text Elicitation Mechanisms"
We have an upcoming #IDEAL workshop on this topic on May 1. Pictured, Prof. Curry is overviewing our recent joint paper "Aligned Textual Scoring Rules". arxiv.org/abs/2507.06221
Speaker with slide: What's different about data: non-rival, freely replicable, costly to share, and value a priori unknown.
Great presentation by Northwestern postdoc Pooja Kulkarni on
"Emerging Markets: Data, Models, and Tokens"
What's different about data: non-rival, freely replicable, costly to share, and value a priori unknown. #IDEAL
Speaker with slide: What's different about data: non-rival, freely replicable, costly to share, and value a priori unknown.
Great presentation by Northwestern postdoc Pooja Kulkarni on
"Emerging Markets: Data, Models, and Tokens"
What's different about data: non-rival, freely replicable, costly to share, and value a priori unknown. #IDEAL
[Monday, 12:15-1:30pm PT] AFOG Seminar: Hartline and Wexler on "AI Suppression: E-Discovery Software and Brady" #socialcal
Looking forward to visiting the Algorithmic Fairness and Opacity Group at UC-Berkeley on Monday with my fabulous coauthor Rebecca Wexler to present
"AI Suppression: E-Discovery Software and Brady"
Event details: afog.berkeley.edu/events
Paper: papers.ssrn.com/sol3/papers....
