The 38th Annual AAAI Conference on Artificial Intelligence
February 20-27, 2024 | Vancouver, Canada
Main Conference Timetable for Authors
Note: all deadlines are “anywhere on earth” (UTC-12)
November 2-5, 2023
Author feedback window
December 9, 2023
Notification of final acceptance or rejection
December 19, 2023
Submission of paper preprints for inclusion in electronic conference materials
February 20 – February 27, 2024
July 4, 2023
AAAI-24 web site open for author registration
July 11, 2023
AAAI-24 web site open for paper submission
August 8, 2023
Abstracts due at 11:59 PM UTC-12
August 15, 2023
Full papers due at 11:59 PM UTC-12
August 18, 2023
Supplementary material and code due by 11:59 PM UTC-12
September 25, 2023
Registration, abstracts and full papers for NeurIPS fast track submissions due by 11:59 PM UTC-12
September 27, 2023
Notification of Phase 1 rejections
September 28, 2023
Supplementary material and code for NeurIPS fast track submissions due by 11:59 PM UTC-12
Call for the Special Track on AI for Social Impact
AAAI-24 is pleased to continue a special track focused on Artificial Intelligence for Social Impact (AISI). This track recognizes that high quality research conducted in social impact domains often leads to papers that differ from traditional AAAI submissions in multiple dimensions. We invite authors to submit papers that prioritize and delve deeper into one or more of the following key aspects:
- Data collection: Addressing the challenges associated with gathering data in social impact domains, such as innovative methods, validation techniques, and strategies to mitigate biases and ensure fairness.
- Problem modeling: Recognizing the intricate nature of problem formulation in social impact contexts, which requires close collaborations with domain experts and balancing various trade-offs in decision-making.
- Field tests and evaluation: Highlighting the significance of rigorous experimentation in real-world settings to assess social impact, encompassing well-designed experimental designs, complex evaluation methodologies, and comprehensive analysis.
The goal of this track at AAAI-24 is to highlight these technical challenges and opportunities and to showcase the social benefits of artificial intelligence.
This page outlines the specific track focus of the Special Track on AI for Social Impact (AISI), as well as review criteria unique to this track. For complete information about the following topics pertaining to all technical tracks and focus areas, including AISI, especially with regard to submission and deadline information, please refer to the main AAAI-24 Call for Papers.
Submissions to this special track will follow the regular AAAI technical paper submission procedure but the authors need to select the AISI special track. There will be no transfer of papers between the AAAI-24 main track and the AISI special track; therefore, authors will need to decide to which track they want to submit their paper (note that only this special track offers a set of AISI keywords). Papers submitted to this track will be evaluated using the following criteria which are different from the criteria for the main track. For acceptance into this track, typically we would expect papers to have a high score on some (but not necessarily all) of these criteria. As a reference, see the papers accepted for AAAI-22 AISI special track.
Significance of the problem
- The social impact problem considered by this paper is significant and has not been adequately addressed by the AI community.
- This paper represents a new take on a significant social impact problem that has been considered in the AI community before.
- The social impact problem considered by this paper has some significance and this paper represents a new take on the problem.
- This paper’s contribution was elsewhere: it follows up on an existing problem formulation or introduces a new problem with limited immediate potential for social impact.
Engagement with literature
- Shows an excellent understanding of other literature on the problem, including that outside computer science.
- Shows a strong understanding of other literature on the problem, perhaps focusing on various subtopics or on the CS literature.
- Shows a moderate understanding of other literature on the topic, but does not engage in depth.
- Does not engage sufficiently with other literature on the topic.
Novelty of approach
- Introduces a new model, data gathering technique, algorithm, and/or data analysis technique.
- Substantially improves upon an existing model, data gathering technique, algorithm, and/or data analysis technique.
- Makes a moderate improvement to an existing model, data gathering technique, algorithm, and/or data analysis technique.
- This paper’s contribution was elsewhere: it employs existing models, data gathering techniques, algorithms, and/or data analysis techniques (e.g., the paper presents a new experimental design and evaluation procedure).
Justification of approach
- Thoroughly and convincingly justifies the approach taken, explaining strengths and weaknesses as compared to other alternatives.
- The justification of the approach is convincing overall, but could have been more thorough and/or alternatives could have been considered in more detail.
- The justification of the approach is relatively convincing, but has weaknesses.
- The justification of the approach is flawed and/or not convincing.
Quality of evaluation
- Evaluation was exemplary: data described the real world and was analyzed thoroughly.
- Evaluation was convincing: datasets were realistic; analysis was solid.
- Evaluation was adequate, but had significant flaws: datasets were unrealistic and/or analysis was insufficient.
- Evaluation was unconvincing.
Facilitation of follow-up work
- Excellent facilitation of follow-up work: open-source code; public datasets; and a very clear description of how to use these elements in practice.
- Strong facilitation of follow-up work: some elements are shared publicly (data, code, or a running system) and little effort would be required to replicate the results or apply them to a new domain.
- Adequate facilitation of follow-up work: moderate effort would be required to replicate the results or apply them to a new domain.
- Weak facilitation of follow-up work: considerable effort would be required to replicate the results or apply them to a new domain.
Scope and promise for social impact
- Likelihood of social impact is extremely high: the paper’s ideas are already being used in practice or could be immediately.
- Likelihood of social impact is high: relatively little effort would be required to put this paper’s ideas into practice, at least for a pilot study.
- Likelihood of social impact is moderate: this paper gets us closer to its goal, but considerably more work would be required before the paper’s ideas could be implemented in practice.
- Likelihood of social impact is low: the ideas proposed in this paper are unlikely to make a significant impact on the proposed problem.
AAAI-24 is enforcing a strict submission limit. Each individual author is limited to no more than 10 submissions to the AAAI-24 main track and two special tracks (AISI and SRRAI), and authors may not be added to papers following submission (see the main AAAI-24 Call for Papers for policies about author changes).
Questions and Suggestions
Concerning author instructions and conference registration, write to email@example.com. Concerning suggestions for the program and other inquiries, write to the AAAI-24 AISI Program Cochairs:
Bistra Dilkina (University of Southern California, USA)
Xiaoli Fern (Oregon State University, USA)
AI for Social Impact Keywords
- AISI: Agriculture and Food
- AISI: Climate
- AISI: Computational Social Science and Humanities
- AISI: Disaster Mitigation and Response
- AISI: Education
- AISI: Energy
- AISI: Environmental Sustainability
- AISI: Low and Middle-Income Countries / Underserved Communities
- AISI: Mobility / Transportation
- AISI: Natural Sciences
- AISI: Philosophical and Ethical Issues
- AISI: Public Health
- AISI: Security and Privacy
- AISI: Social Development
- AISI: Social Networks and Social Media
- AISI: Social Welfare, Justice, Fairness and Equality
- AISI: Urban Planning
- AISI: Other Social Impact