AAAI 2024 Spring Symposium on

User-Aligned Assessment of
Adaptive AI Systems


Stanford University, Stanford, CA, USA

March 25-27, 2024

Overview

AI systems are increasingly interacting with users who are not experts in AI. This has led to growing calls for better safety assessment and regulation of AI systems. However, broad questions remain on the processes and technical approaches that would be required to conceptualize, express, manage, and enforce such regulations for adaptive AI systems, which by nature, are expected to exhibit different behaviors while adapting to evolving user requirements and deployment environments.

This symposim will foster research and development of new paradigms for assessment and design of AI systems that are not only efficient according to a task-based performance measure, but also safe to use by diverse groups of users and compliant with the relevant regulatory frameworks. It will highlight and engender research on new paradigms and algorithms for assessing AI systems' compliance with a variety of evolving safety and regulatory requirements, along with methods for expressing such requirements.

We also expect that the symposium will lead to a productive exchange of ideas across two highly active fields of research, viz., AI and formal methods. The organization team includes active researchers from both fields and our pool of invited speakers features prominent researchers from both areas.

Please feel free to send workshop related queries at: aia2024.symposium@gmail.com.

Call for Papers

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 symposium 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 symposium will feature invited talks by researchers from AI and formal methods, as well as talks on contributed papers.

We welcome submissions on topics such as:


Submission Guidelines

Submissions will take the form of extended abstracts with a first author who will be the speaker, and each speaker cannot have more than one submission as first author. Each submission must be 1-2 pages long, excluding references (in the AAAI 2024 style available here), and may refer to joint work with other collaborators. Co-authored papers should list the expected speaker as the first author of the paper.

Submissions can be a summary/survey of recent results, new research, or a position paper. There are no formal proceedings, and we encourage submissions of work presented or submitted elsewhere (no copyright transfer is required, only permission to post the abstract on the symposium site).

Papers can be submitted via EasyChair at https://easychair.org/my/conference?conf=aia2024.

Important Dates

Submission deadline January 15 January 22, 2024 (11:59 PM UTC-12)
Author notification January 31 February 09, 2024
Symposium March 25-27, 2024

Invited Speakers

(Tentative)



Kamalika Chaudhuri
Kamalika Chaudhuri
University of California San Diego, USA and Meta AI


Sriraam Natarajan
Sriraam Natarajan
University of Texas Dallas, USA


Sriram Sankaranarayanan
Sriram Sankaranarayanan
University of Colorado Boulder, USA


Sanjit A. Seshia
Sanjit A. Seshia
University of California Berkeley, USA




Accepted Papers

Committees

Organizing Committee


Pulkit Verma
Pulkit Verma
Arizona State University, USA


Rohan Chitnis
Rohan Chitnis
Meta AI, USA


Georgios Fainekos
Georgios Fainekos
Toyota Motor North America R&D, USA




Hazem Torfah
Hazem Torfah
Chalmers University of Technology, Sweden


Pulkit Verma
Siddharth Srivastava
Arizona State University, USA