ΑΙhub.org
Proceedings from #AIES2023 now available
The sixth AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) took place in Montreal, Canada, from 8-10 August 2023. The three-day event included keynote talks, contributed talks, panel discussions, and poster sessions.
We had a great turnout at #AIES2023! Thank you to everyone who was in attendance. #AAAI #AI #ArtificialIntelligence pic.twitter.com/eluktw4sLx
— AAAI (@RealAAAI) August 11, 2023
The proceedings from the conference are now available. You can see the complete collection here.
To jump to specific sections, you can follow the links below:
Read more from the conference
- #AIES2023 – panel discussion on large language models – Roxana Daneshjou, Atoosa Kasirzadeh, Kate Larson and Gary Marchant discuss the hype, hopes and harms of LLMs.
- #AIES2023 tweet round-up – Find out what participants got up to at the conference.
tags: AAAI, AIES2023, quick read
Lucy Smith
is Senior Managing Editor for AIhub.
Lucy Smith
is Senior Managing Editor for AIhub.
AUAI is supported by:
Related posts :
Interactive World Simulator for Robot Policy Training and Evaluation
Yixuan Wang
17 Jul 2026
Yixuan Wang discusses his faithful world simulator that allows robots to learn how to push, pick up, and grasp objects.
#ICML2026 social media round-up
AIhub
17 Jul 2026
We take a look at what the participants got up to in Seoul.
François Pachet on music generation with AI
Liliane-Caroline Demers
16 Jul 2026
“The day I hear a song of the quality of the Beatles, I will say: ‘Okay, we are done’. And I’ve never heard anything like that. Never.”
AI for science – talk recordings now available to watch
Lucy Smith
15 Jul 2026
Watch the invited talks from the day on YouTube.
AAAI presidential panel – factuality and trustworthiness
Lucy Smith
14 Jul 2026
Watch the latest panel discussion in the series based on the Future of AI research report from AAAI.
The secret to human ‘brilliance’ that AI just can’t match
Stanford Report
13 Jul 2026
New research reveals how people learn social conventions with minimal data – and why that sets us apart from LLMs.
Pre-training isn’t bitter enough
ML@CMU
10 Jul 2026
Given an unlabeled data stream, and a small set of verifiable downstream examples, can we use those examples during continued pre-training?
Interview with Thi Kieu Khanh Ho: Time-series anomaly detection
Lucy Smith
09 Jul 2026
How can we teach AI systems to recognize when something unusual or abnormal is happening in complex, real-world data streams, without relying on large amounts of labeled examples?
