AAAI 2023 Fall Symposium
Artificial Intelligence and Climate: The Role of AI in a Climate-Smart Sustainable Future
About
Climate change is one of the most pressing challenges of our time, posing an existential threat to civilization and the planet. Artificial Intelligence (AI) can and, when appropriate, must play a key role in accelerating the transition to a low-carbon economy in order to stave off the risk of catastrophic warming. Recent advances in AI should be harnessed in order to increase the scale and speed at which low-carbon technologies are developed and deployed. AI can also help civilization to adapt to a warming planet and provide a greater understanding of climate science and climate impacts including floods, droughts, wildfires, negative effects on agriculture (such as soil erosion and irrigation problems), extreme wind and temperature fluctuations, and their effect on society. At the same time, AI is a multi-purpose tool, which means it can also be used to accelerate many applications that increase greenhouse gas emissions, as well as having a carbon footprint itself.
We hope the symposium will provide a forum to present novel AI use-cases, technical advances in the state-of-the-art, approaches and lessons learned from current implementations, and broader policy and governance frameworks. The forum will invite participation from academia, industry, government, and civil society to better understand how different sectors can work together to overcome the challenges faced when using AI to address climate challenges.
About the AAAI Fall Symposium Series
This symposium is part of the AAAI Fall Symposium Series, which aims to provide a forum to present ongoing work, hold focused discussions, build new communities for emerging disciplines, and build ties between existing disciplines. The Symposium Series is run via the Association for the Advancement of Artificial Intelligence (AAAI), the premier international scientific society devoted to promoting research in, and the responsible use of, artificial intelligence. Symposia are open to the public; it is not necessary to submit to the symposium in order to attend, though submissions are strongly encouraged.
About the Symposium
The goal of this Fall Symposium is to bring together participants from academia, industry, and government to explore how AI is currently being used and can be expanded to support its key role in addressing climate-related challenges. The symposium will discuss work in the area of AI applied to climate change, the implications of this work, and both the difficulties that arise as well as successes. We will also cover best practices, issues, barriers to success, risk, and policy issues associated with the broad relationship between AI and climate change. This year, we will include discussion on the use of generative AI and LLMs for climate change use cases as well as the ethical frameworks that may be specific to this context.
- Dates: Wednesday, Oct 25 - Friday, Oct 27 2023
- Location: Westin Arlington Gateway, Arlington, Virginia, USA
- Paper submission deadline:
August 11th, 23:59 Anywhere on Earth (AOE)- We will consider extended abstracts of 500 words or more if you are unable to submit a full paper by the deadline (please email climatechange.aaaifss2023@gmail.com).
- Paper submission website: https://easychair.org/my/conference?conf=fss230 (track: “Artificial Intelligence and Climate: The Role of AI in a Climate-Smart Sustainable Future”)
- Notification of accepted papers/proposals: Sept 11
- Invited participants registration deadline: Sept 15
- Registration: Registration is open to the public.
- Registration site: https://aaai.org/conference/fall-symposia/aaai-2023-fall-symposium-series/
- Camera-ready final submissions due to organizers: Oct 1
- Contact: climatechange.aaaifss2023@gmail.com
COVID Policy
The 2023 Fall Symposium Series will be a primarily in-person event. We take COVID-19 very seriously, and will at minimum strictly adhere to all guidelines suggested by AAAI. More detailed updates will be posted here and on the AAAI fall symposium website as they become available.
Schedule
The symposium runs from October 25-27 in Arlington, VA, USA, and includes keynote talks, panels, presentations of contributed work, poster sessions, and discussion sessions.
Jump to: Wednesday (25th), Thursday (26th), Friday (27th)
Wednesday, October 25
| Time (ET) | Event |
|---|---|
| Welcome and Opening Remarks | |
| Overview of Conference Themes | |
| Thomas Brunschwiler, "Sustainable Inference of Remote Sensing Data by Recursive Semantic Segmentation - A Flood Extent Mapping Study" | |
| Usman Nazir, "Spatio-Temporal driven Attention Graph Neural Network with Block Adjacency matrix (STAG-NN-BA) for Remote Land-use Change Detection" | |
| Sarthak Chaturvedi, "A Generative AI Approach to Pricing Mechanisms and Consumer Behavior in the Electric Vehicle Charging Market" | |
| Coffee Break | |
| Geoffrey Guest, "Scaling Carbon Footprinting: Challenges and Opportunities" | |
| Ryo Koblitz, "Reducing the Environmental Impact of Wireless Communication via Probabilistic Machine Learning" | |
| Jennifer Sleeman, "Deep Learning Ensembles for Improved Atmospheric Composition Modeling" | |
| Alex Stevenson, "Efficient Reinforcement Learning for Real Time Hardware-based Energy System Experiments" | |
| Lunch | |
Keynote: Anima Anandkumar
Details: (click to expand)Anima Anandkumar is Bren Professor of Computing at California Institute of Technology and Director of ML Research at NVIDIA |
|
| Maximillan Nitsche, "AB2CD: AI for Building Climate Damage Classification and Detection" | |
| Bayu Adhi Tama, "Tracing Englacial Layers in Radargram via Semi- supervised Method: A Preliminary Result" | |
| Break | |
| Feras Batarseh, "NeuralFlood: An AI-Driven Flood Susceptibility Index" | |
| Catharina Hollauer, "Generative AI and Discovery of Preferences for Single-Use Plastics Regulations" | |
| Jose González-Abad, "Multi-variable Hard Physical Constraints for Climate Model Downscaling" | |
| Panel: AI, Climate & Policy | |
| Stefanie Falconi, Emerging Tech Advisor at USAID | |
| Dann Sklarew, Professor, Environmental Science & Policy, GMU | |
| Johannes Kirnberger, OECD (Remote) | |
| Soribel Feliz, AAAS Congressional Fellow | |
| Carlos Martinez, AAAS S&T Policy Fellow | |
| Moderator: Jennifer Sklarew, Professor, Environmental Science & Policy, GMU | |
| Reception |
Thursday, October 26th
| Time (ET) | Event |
|---|---|
| Day 2 Welcome | |
| Deepank Singh, "Climate Resilience through AI-driven Hurricane Damage Assessments" | |
| Biao Luo, "AutoPCF: A Novel Automatic Product Carbon Footprint Estimation Framework Based on Large Language Models" | |
| Amal Nammouchi,"Quantum Machine Learning in Climate Change and Sustainability: A Short Review" | |
| Break | |
| Lekha Patel, "Deep learning aerosol-cloud interactions from satellite imagery" | |
| Seyed Mousavi, "AI-driven E-Liability Knowledge Graphs: A Comprehensive Framework for Supply Chain Carbon Accounting and Emissions Liability Management" | |
| Seyed Mousavi, "Leveraging AI-derived Data for Carbon Accounting: Information Extraction from Alternative Sources" | |
| Joshua Steier, Sally Calengor, Sai Prathyush Katragadda, "Adversarial Threats in Climate AI: Navigating Challenges and Crafting Resilience" | |
| Lunch | |
| Panel: Foundation Models | |
| Rahul Ramachandran, NASA | |
| Bianca Zadrozny, IBM Research - Brazil | |
| Aditya Grover, UCLA | |
| Matthew Chantry, ECMWF | |
| Sasha Luccioni, HuggingFace | |
| Marquita Ellis, IBM Research - Yorktown | |
| Moderator: Thomas Brunschwiler, IBM | |
Keynote: Vipin Kumar, "Role of Big Data and Machine Learning for Addressing Global Environmental Challenges"
Details: (click to expand)Vipin Kumar is an AAAI Fellow and Regents Professor and William Norris Chair in Large Scale Computing Department of Computer Science and Engineering Director, CSE Data Science Initiative, University of Minnesota. |
|
| Break | |
| Maximillan Touzel, "Ideology as topic correlation structure: Inference method and example application to carbon tax public opinion" | |
| Benjamin Huynh,"AI for Anticipatory Action: Moving Beyond Climate Forecasting" | |
| Panel: Financing AI for Climate | |
| James Mister, Bavarian US Offices for Economic Development | |
| Honour Masters, Energize Capital | |
| Josh Rapperport, Innovation Endeavors | |
| Matt Blain, Voyager VC | |
| Sylvia Spengler, National Science Foundation | |
| Moderator: Jim Spohrer, ISSIP.org | |
| Workshop Discussion & Readout Prep | |
| Cross Symposium Plenary Session |
Friday, October 27th
| Time (ET) | Event |
|---|---|
Group Workshop: Identifying Critical Data Gaps for AI & Climate
Details: (click to expand)Join us for a group breakout discussion to identify critical data gaps impeding the application of AI for climate.Moderator: Xiaojuan Liu, Climate Change AI and Olivia Mendivil Ramos, Climate Change AI |
|
| Break | |
Keynote: Erwin Rose, "International Cooperation on Artificial Intelligence and Climate at the 2023 UN Climate Conference (COP28) and Beyond"
Details: (click to expand)Erwin Rose is Chair, UN Climate Technology Center & Network Advisory Board and Foreign Affairs Officer, U.S. Department of State |
|
| Group Breakout Discussion Continued & Sharing of Next Steps |
Organizers
Utkarsha Agwan (UC Berkeley)
Feras A. Batarseh (Virginia Tech)
Dr. Thomas Brunschwiler (IBM Research Europe - Zurich)
Priya L. Donti (Carnegie Mellon) - Co-Chair
Christoph Funk (Centre for International Development and Environmental Research (ZEU))
Melissa Hatton (Capgemini Government Solutions) - Co-Chair
Srinivasan Keshav (University of Cambridge)
Alice Lépissier (Brown University)
Marina Lesse (Energy Academic Group, Naval Postgraduate School)
Peetak Mitra (PARC)
Jorge Montalvo (Centrica)
Sebastian Ruf (Intercontinental Exchange (ICE))
Jim Spohrer (ISSIP)
Frank Stein (Virginia Tech) - Co-Chair
Gege Wen (Stanford)
Andrew Williams (Mila - Quebec Artifical Intelligence Institute)
Ziyi Yin (Georgia Institute of Technology)
Call for Submissions
We invite submissions of position, review, and research papers in two formats: short papers (2-4 pages) and full papers (6-8 pages). Submissions are due on Jul 28 by 23:59 AOE (Anywhere on Earth).
Topics may include, but are not limited to:
- MITIGATION
- AI to accelerate decarbonization in the main greenhouse gas-emitting sectors such as industry, transportation, buildings, energy systems, agriculture, forestry and land use, and others
- AI for the development of negative emissions technologies (natural and engineered), such as carbon capture and sequestration (CCS) and carbon dioxide removal (CDR)
- AI to monitor reforestation and illegal logging, as well as to estimate green-house-gas emissions from satellite imagery or other techniques.
- AI for the accelerated development of clean technologies such as batteries, electrofuels, and green hydrogen
- ADAPTATION
- AI to better predict, measure, and respond to climate hazards (e.g., flooding, fires, extreme temperatures, and droughts)
- AI to understand, predict and reduce climate security (environmental security) risks, such as conflict risk; compounding food, water, and human insecurity; strained institutions, mass displacement of persons; and reshaped geopolitics.
- AI to develop climate-resilient societal infrastructure (e.g., hurricane-proof buildings, resilient power grids, and protections against sea level rise)
- AI for biodiversity preservation and ecological awareness, including from a sociopolitical perspective (e.g., AI to increase stakeholder ownership in local environmental commons and AI to supercharge the dissemination of information among communities)
- AI for crisis readiness, disaster response, resilient livelihoods, and public health
- AI for food security, water security, and climate-resilient agriculture
- CLIMATE SCIENCE
- AI for improving or augmenting Earth system models
- AI for extreme event prediction
- CROSS-CUTTING ISSUES
- Governance and ethics for AI and climate
- AI for climate finance, e.g., to improve physical climate and transition risk assessments and corporate sustainability disclosures
- Climate policy, including AI for causal evaluation of policy interventions and AI to identify optimal policy sequencing and deployment
- Methodological issues and frameworks
- Standardizing AI metrics and approaches for climate action
- Developing standards on the quality and integrity of data used in AI for climate action
- Increasing interoperability of AI frameworks across diverse application domains
- MLOps: how to transition AI climate models from a research state to an operational level at scale
- Cybersecurity and cyber-biosecurity risks associated with increased digitalization and AI integration within climate workflows
- Barriers, bottlenecks, and structural challenges associated with developing, deploying, integrating, fostering adoption, and scaling AI-based climate solutions, including financing such work.
- Aligning AI with sustainable societal pathways and Sustainable Development Goals (SDGs), including approaches from AI and digitalization policy, climate policy, capacity building, and science and innovation policy
- Tools, benchmarks, and datasets to advance the field
- Initial results and future potential of geospatial and climate foundation models
- AI’s IMPACTS ON CLIMATE
- Measurement, verification, and uncertainty quantification of potential benefits provided by AI-based climate solutions
- Assessing direct carbon footprint of AI (including compute- and hardware-related impacts)
- Assessing AI’s use in accelerating emissions-intensive industries (e.g., oil and gas, mining, cattle farming)
- Impact assessment of AI-related systemic shifts (e.g., increased consumption due to targeted advertising, effects of autonomous vehicles and ridesharing)
- Dissemination of (mis)information, including effects of LLMs and generative AI
- Implications of AI for climate justice, including tech transfer-related considerations
All submissions must make clear their connection to these topics and/or the broader theme of the workshop. Extended versions of articles in submission at other venues are acceptable as long as they do not violate the dual-submission policy of the other venue.
All submissions must be made through the EasyChair submission website (select “Artificial Intelligence and Climate: The Role of AI in a Climate-Smart Sustainable Future” track), and should be formatted according to the AAAI style template. All submissions will undergo single-blind peer review (that is, submissions should not be anonymized). Authors will have the option to publish their work in an open access proceedings site.
Please also see the FAQ, and contact climatechange.aaaifss2023@gmail.com with questions.
Submission Types
We invite submissions of position, review, and research papers (more details below).
We invite both short papers (2-4 pages) and full papers (6-8 pages). All figures, tables, and graphics must be contained within these page limits; however, references may extend onto additional pages. Supplementary appendices are allowed but will be read at the discretion of the reviewers.
Research Papers
Work that is in progress, published, and/or deployed.
Research Papers should describe projects relevant to the intersection of climate change and AI. These may include (but are not limited to) academic research; deployed results from startups, industry, public institutions, etc.; and climate-relevant datasets. In addition to describing the projects themselves, Research Papers should also include discussion of lessons learned, best practices, and areas whether further research and innovation is required.
Submissions applying AI to address a climate-relevant problem should provide experimental or theoretical validation of the method presented, as well as specifying what gap the method fills. Authors should clearly illustrate a pathway to climate impact, i.e., identify the way in which this work fits into broader efforts to address climate change. Algorithms need not be novel from an AI perspective, but should be applied in a climate-relevant setting. Details of methodology need not be revealed if they are proprietary, though transparency is highly encouraged.
Submissions presenting novel climate-relevant datasets are welcomed. Datasets should be designed to permit AI and machine learning research (e.g., formatted with clear benchmarks for evaluation). In this case, baseline experimental results on the dataset are preferred, but not required.
Review Papers
Overviews of relevant topics or fields.
Review Papers should provide overviews of topics or fields at the intersection of climate change and AI (e.g., pertaining to the topics listed in the call for submissions).
Submissions of this form should synthesize existing literature, and additionally provide insights on gaps, salient considerations, and future directions to be considered by symposium attendees and the broader community.
Position Papers
Opinions or critiques on relevant topics or directions.
Position Papers should provide opinions or critiques on topics or directions at the intersection of climate change and AI (e.g., pertaining to the topics listed in the call for submissions).
Submissions of this form should present important frameworks or considerations for work at the intersection of climate change and AI, and should be well-grounded in existing literature and/or practice.
Frequently Asked Questions
Q: I’m not an AI researcher or practitioner. Can I still submit?
A: Yes, absolutely! We welcome submissions from a diverse set of stakeholders.
Q: What if my submission is accepted but I can’t attend the symposium in person?
A: A co-author or colleague can present for you, or you may be able to present via Zoom if that is supported this year (TBD).
Q: Do I need to use the AAAI style files for my submission?
A: Yes, they are required.
Q: It’s hard for me to fit my submission within the page limits. What should I do?
A: Feel free to include appendices with additional material (these should be part of the same file as the main submission). Do not, however, put essential material in an appendix, as it will be read at the discretion of the reviewers.
Q: Can I send submissions directly by email?
A: No, please use the EasyChair website to make submissions, and select the track on “Artificial Intelligence and Climate: The Role of AI in a Climate-Smart Sustainable Future” when creating your submission. If you are having trouble with the EasyChair website, please contact: climatechange.aaaifss2023@gmail.com.
Q: Can I submit previously published work to this symposium?
A: Yes, though under limited circumstances. In particular, extended versions of articles in submission at other venues are acceptable as long as they do not violate the dual-submission policy of the other venue. Please contact climatechange.aaaifss2023@gmail.com with any questions.
Q: Can I submit work to this symposium if I am also submitting to another 2023 AAAI Fall Symposium session?
A: Yes. We cannot, however, guarantee that your assigned presentation time will not conflict with the other symposium.
Q: What is the COVID policy of the event?
A: We take COVID-19 very seriously, and will at minimum strictly adhere to all guidelines provided by AAAI. More detailed updates will be posted here and on the AAAI fall symposium website as they become available.
Q: How can I keep up to date on these issues?
A: We encourage you to sign up for the Climate Change AI newsletter to receive information about opportunities and events at the intersection of climate change and AI.