Hadi Hosseini

100% agree on this. The most challenging problems in AI are related to learning/understanding human values.

Btw, this is one of my favorite books in the genre!

We are organizing the 8th Games, Agents, and Incentives Workshop
(GAIW) @aamasconf.bsky.social 2026; this time in Cyprus!

Submit your amazing papers (published, unpublished, and even half-baked but well-written ideas)

Webpage: gtep-workshops.github.io/gaiw2026/

There's only one solution: reject due to academic misconduct.

It's not about correctness of findings or proofs, as scholars we need to be educators as well. A good paper is not just about it's results, it's equally about providing educational value.

Milind Tambe is giving an eye opening talk on the use of AI for health intervention. At @RealAAAI doctoral consortium.

@milindtambe-ai.bsky.social is giving an eye opening talk on the use of AI for health intervention. At @aaai.org doctoral consortium.

What does 'agentic' AI mean? Tech's newest buzzword is a mix of marketing fluff and real promise For technology adopters looking for the next big thing, “agentic AI” is the future. At least, that’s what the marketing pitches and tech industry T-shirts say.

My views on "agentic" here in this AP article on "agentic AI"

apnews.com/article/agen...

I am recruiting PhD students at NYU Courant to conduct research in learning theory, algorithmic statistics, and trustworthy machine learning, starting Fall 2026. Please share widely! Deadline to apply is December 12, 2025.

Hadi Hosseini, Shraddha Pathak, Yu Zhou
Non-Monotonicity in Fair Division of Graphs
https://arxiv.org/abs/2511.03629

His rules/intuitions are based on simple observations and are often elegant.
Not sure this time; the stock market value is primarily based on overall expectations and not necessarily actual value created.

Nominate your final-year TCS PhD students or postdoc for the 2025 Chicago Junior Theorists Workshop (hosted by Northwestern and TTIC).

theory.cs.northwestern.edu/2025/10/30/2...

Toby Walsh’s ‘The Shortest History of AI’: Your 6-Hour AI Guide Artificial Intelligence (AI) was born on International Panic Day. Slightly weird, but then babies do cry when they come out of the womb. Whether that was an omen for today’s disruptive black …

Toby Walsh's 'The Shortest History of AI': Your 6-Hour AI Guide queenoftreasures.com/2025/10/01/t...

Matching Markets Meet LLMs: Algorithmic Reasoning with Ranked Preferences The rise of Large Language Models (LLMs) has driven progress in reasoning tasks -- from program synthesis to scientific hypothesis generation -- yet their ability to handle ranked preferences and stru...

Read paper: arxiv.org/abs/2506.04478

This is a joint work with two of my great students, Samarth and Ronak!

Verdict:
Even top-tier reasoning models struggle when:
- generating stable solutions,
- detecting blocking pairs (instabilities),
- repairing unstable matchings, or
- scaling reasoning to larger markets.

Why matching markets?

1. They require reasoning over ranked preferences (who prefers whom) while following iterative algorithms. They’re the ideal stress test for LLM reasoning.
2. They’re everywhere: assigning students to schools, workers to jobs, riders to drivers, and even content to users.

2️⃣ Algorithmic, step-by-step reasoning. In computer science education, we call this algorithmic thinking, i.e. the capacity to follow and adapt structured procedures. It’s what allows us to detect errors, repair them, and maintain logical consistency.

🤖 Two abilities are essential:

1️⃣ Understanding and reasoning about preferences.
They must grasp which option is more desirable: Is a 9 AM meeting better than 7 AM? Is candidate A preferred to B? This is about comprehending relative value and priority, not just data.

🧠 Can large language models actually reason? Not just in math or logic puzzles, but in structured, algorithmic domains?

Our new @neuripsconf.bsky.social paper "Matching Markets Meet LLMs: Algorithmic Reasoning with Ranked Preferences", explores this question.

Podcast: “Generations in Dialogue: Bridging Perspectives in AI.” - AAAI About AAAI: Dedicated to advancing the understanding of the thought and intelligent behavior and their embodiment in machines.

We are thrilled to announce the new podcast series, “Generations in Dialogue: Bridging Perspectives in AI.” Through this series, we aim to represent diverse perspectives across generations, fostering rich conversations about the ever changing landscape of AI. aaai.org/generations-...

Distributive Fairness in Large Language Models: Evaluating Alignment with Human Values The growing interest in employing large language models (LLMs) for decision-making in social and economic contexts has raised questions about their potential to function as agents in these domains. A ...

Read the full paper: arxiv.org/abs/2502.00313

#NeurIPS2025 #AIAlignment #Fairness #LLMs #EthicsInAI #HumanValues

3️⃣ Selection from a menu aligns better than generation. When asked to select from a preselected menu of options, some models (GPT-4o and Claude-3.5) display more human-like fairness, prioritizing equitability.

1️⃣ LLMs are often misaligned with human notions of fairness. They seldom minimize inequality (equitability), instead favoring envy-freeness or efficiency.

2️⃣ When money is available, humans use it to restore balance, equalizing utilities; most LLMs do not.

As LLMs increasingly act in social and economic domains, normative alignment—ensuring their outputs reflect human values—becomes critical. Our findings:

When we ask large language models to make or recommend decisions, who gets resources, opportunities, or aid, whose values are they representing?

A short🧵on our new #NeurIPS2025 paper: “Distributive Fairness in Large Language Models: Evaluating Alignment with Human Values.”

The abstracts submission deadline for the main technical tracks is fast approaching! Don't miss your chance to present your research in Cyprus and connect with top experts in Autonomous Agents and Multiagent Systems🔔

📅 Submission deadline: October 1, 2025
#AAMAS2026 #Cyprus #AutonomousAgents

AAAI-26 Undergraduate Consortium: Call for Participation - AAAI

The Undergraduate Consortium hosted at the AAAI-26 is a two-day program held in conjunction with the main conference. The AAAI-UC features speakers, workshops, and events tailored to undergraduate students that will immerse them in the field of artificial intelligence. aaai.org/conference/a...

Haha, I am waiting for a day that we can train AI to model your young self. Then we get to use the sharp mind (and argue all day about dumb choices), lol

Are you secretly hiding inside the code? Lol

I'm hiring again! Please share. I'm recruiting a postdoc research fellow in human-centred AI for scalable decision support. Join us to investigate how to balance scalability and human control in medical decision support. Closing date: 4 October (AEST).
uqtmiller.github.io/recruitment/

Only if they knew that about contrapositives!

🎓 Are you interested in participating in #AAMAS2026?

🔹 Blue Sky Ideas Special Track
🔹 JAAMAS Track
🔹 AAAI Track
🔹 Demonstrations

👉 Explore the details and join us in shaping the future of autonomous agents and multiagent systems: cyprusconferences.org/aamas2026

#ArtificialIntelligence

Thirty-First AAAI/SIGAI Doctoral Consortium: Call for Proposals - AAAI

📢 Call for AAAI-26 Doctoral Consortium Submissions
(Deadline: September 30 AoE)

Doctoral students in the AI community are invited to apply to the Doctoral Consortium at #AAAI26, held on January 20-21 2026 in Singapore!

aaai.org/conference/a...