[Apologies for cross-posting]
IJCAI 2025 Workshop on User-Aligned Assessment of Adaptive AI Systems
Montreal, QC, Canada | August 16-18, 2025
Workshop Website
Although there is a growing need for independent assessment and regulation of AI systems, broad questions remain on the processes and technical approaches that would be required to conceptualize, express, manage, assess, and enforce such regulations for adaptive AI systems.
This workshop addresses research gaps in assessing the compliance of adaptive AI systems (systems capable of planning/learning) in the presence of post-deployment changes in requirements, in user-specific objectives, in deployment environments, and in the AI systems themselves.
These research problems go beyond the classical notions of verification and validation, where operational requirements and system specifications are available a priori. In contrast, adaptive AI systems such as household robots are expected to be designed to adapt to day-to-day changes in the requirements (which can be user-provided), environments, and as a result of system updates and learning. The workshop will feature invited talks by researchers from AI and formal methods, as well as talks on contributed papers.
Topics of interest include:
Assessment of AI system capabilities.
Algorithmic paradigms for assessment of safety and/or compliance of AI systems with evolving regulations.
Learning predictive models of agent capabilities.
Self-assessment and monitoring.
Differential assessment of AI systems following system updates or learning.
Assessment of black-box AI systems.
Types of assessment frameworks and ecosystems.
Specification languages and representations for specifying requirements on AI systems.
Assessment of LLM-based agents.
Specification and assessment of compliance w.r.t. ethics/ethical properties.
Regulation, management, and enforcement of AI assessment paradigms.
INVITED SPEAKERS (TENTATIVE)
Chuchu Fan, Massachusetts Institute of Technology
David Krueger, Mila and University of Montreal
Ruqi Zhang, Purdue University
WORKSHOP FORMAT
The workshop will feature invited talks, a selected set of contributed talks, and discussions. The workshop will be in-person and is scheduled for one day. IJCAI 2025 will be an in-person event this year, and the workshop will follow the same format as the conference.
SUBMISSION INSTRUCTIONS
Submissions can describe either work in progress or mature work that has already been published at another research venue. We also welcome “highlights” papers summarizing and highlighting results from multiple recent papers by the authors. Submissions of papers being reviewed at other venues (NeurIPS, CoRL, ECAI, KR, etc.) are welcome since AIA 2025 is a non-archival venue and we will not require a transfer of copyright. If such papers are currently under blind review, please anonymize the submission.
Submissions should use the IJCAI 2025 style. Papers under review at other venues can use the style file of that venue, but the camera-ready versions of accepted papers will be required in the IJCAI 2025 format by the camera-ready deadline. The papers should adhere to the IJCAI Code of Conduct for the Authors, the IJCAI Code of Ethics, and the NeurIPS 2025 policy on using LLMs.
Three types of papers can be submitted:
New full technical papers with the length of up to 7 pages + references
New short papers with the length between 2 and 4 pages + references
Previously published papers in their original format (ICML, ICLR, R:SS, etc.). For these submissions, if the match with workshop topics is not immediately clear, we recommend editing the introduction to clarify relevance.
Papers can be submitted via OpenReview at https://openreview.net/group?id=ijcai.org/IJCAI/2025/Workshop/AIA. Additional details are available on the workshop website.
IMPORTANT DATES
Paper submission deadline: May 16, 2025 (AoE, 11:59 PM UTC-12)
Author notification: June 06, 2025
Workshop date: August 16-18, 2025 (Exact date TBD)
ORGANIZING COMMITTEE
Pulkit Verma, Massachusetts Institute of Technology
YooJung Choi, Arizona State University
Georgios Fainekos, Toyota Motor North America R&D
Siddharth Srivastava, Arizona State University
Hazem Torfah, Chalmers University of Technology