2nd Workshop on
Sustainable AI
Description
of workshop: the main objectives
While AI has made remarkable achievements across various domains, there
remain legitimate concerns regarding its sustainability. The pursuit of
enhanced accuracy in tackling large-scale problems has led to the adoption of
increasingly deep neural networks, resulting in elevated energy consumption and
the emission of carbon dioxide, which contributes to climate change. As an
illustration, researchers estimated that the training of a state-of-the-art
deep learning NLP model alone generated approximately 626,000 pounds of carbon
dioxide emissions. The environmental sustainability of AI is not the only
concern; its societal impact is equally significant. Ethical considerations
surrounding AI, including fairness, privacy, explainability,
and safety, have gained increasing attention. For instance, biases and privacy
issues associated with AI can limit its widespread application in various
domains. Without a comprehensive understanding of AI's decision-making
processes, it may not be suitable for sensitive areas like healthcare and
autonomous driving. Furthermore, AI has the potential to make a profound
societal impact by directly addressing contemporary sustainability challenges.
Climate modeling, urban planning, and design (for mitigating urban heat islands
or optimizing renewable energy deployment, such as solar power), as well as the
development of green technologies (such as advanced battery materials or
optimized wind/ocean turbine
design), are areas where AI techniques can be extensively applied. Leveraging
AI in these areas is crucial for ensuring a net benefit to sustainability.
Topics
Resource-efficient AI
Efficient and low-carbon AI
Data-efficient AI
Model compression
Power-aware efficient AI accelerators
Nature-inspired optimization for
sustainable AI
Explainable & trustworthy AI, and
fairness, privacy and safety of AI, with the
sustainable societal impact
AI algorithms for resources sustaining and
management, smart grids scheduling, climate modeling, smart transportation,
recycling and maximizing the efficiency of heating and cooling, manufacturing
to reduce waste, and energy and sustainable material development.
Why the topic
is of particular interest
AAAI plays a critical role in addressing grand societal challenges
across different domains, and it should pay attention to important
interdisciplinary areas that can achieve societal impact especially for climate
change, sustainability etc. Specifically, for sustainability of AI, we aim to
reduce carbon emissions and huge computing power consumption, as well as
addressing AI-related ethical issues, via developing advanced AI technology.
This workshop aims to prompt state-of-the-art approaches on sustainable AI
research and propagates data/resource-efficient methods and possible
applications in the sustainability domain that can advance United Nations
Sustainable Development Goals (SDGs). For example, submissions that are at the
intersection of AI and society like use of AI for ensuring affordable and clean
energy (SDG Goal 7), sustainable cities and communities (SDG Goal 11) and
motivating climate action (SDG Goal 13) will be particularly welcome.
Sustainable AI is a freshly emerging field that is hardly covered by any
existing workshop. The proposed workshop will offer a timely collection of
information to benefit the researchers and practitioners working in the broad
research fields of AI, optimization community. All the aforementioned
issues are well covered by the topic of Interest in AAAI 2024.
Workshop Chairs
Xiaoli
Li (Nanyang Technological University/A*STAR, Singapore) xlli@i2r.a-star.edu.sg; xlli@ntu.edu.sg
Joey
Tianyi Zhou (A*STAR CFAR, Singapore) zhouty@cfar.a-star.edu.sg
Callie
Hao (Georgia Institute of Technology, USA) callie.hao@ece.gatech.edu
Vijay Janapa Redi (Harvard University, USA) vj@eecs.harvard.edu.
Yung-Hsiang
Lu (Purdue University, USA) yunglu@purdue.edu.
Programme Chair
Zhenghua Chen (A*STAR, Singapore) Chen_Zhenghua@i2r.a-star.edu.sg.
Programme Committee members
Abhinav Goel
Moyun Liu
Mohamed Ragab
Feifei Shao
Zhuoyi Lin
Ruibing Jin
Xue Geng
WANGLU
Emadeldeen Eldele
Jun Cheng
Hao Liu
Yifang Yin
Xulei Yang
QING XU
Xu Kaixin
Hao Chen
Wang Zhe Mark
Caleb Tung
Accepted Oral Papers
Veronica Chatrath, Shaina Raza, "She had Cobalt Blue Eyes: Prompt Testing to Create Aligned and Sustainable Language Models"
Nianhui Guo, Joseph Bethge, Haojin Yang, Kai Zhong, Xuefei Ning, Christoph Meinel, Yu Wang, "BoolNet: Towards Energy-Efficient Binary Neural Networks Design and Optimization"
Daniel Gei ler, Bo Zhou, Mengxi Liu, Sungho Suh, Paul Lukowicz, "The Power of Training: How Different Neural Network Setups Influence the Energy Demand"
Shiyang Li, Jianshu Chen, Yelong shen, Zhiyu Chen, Xinlu Zhang, Zekun Li, Hong Wang, Jing Qian, Baolin Peng, Yi Mao, Wenhu Chen, Xifeng Yan, "Explanations from Large Language Models Make Small Reasoners Better"
Mengxi Liu, Zimin Zhao, Daniel Gei ler, Bo Zhou, Sungho Suh, Paul Lukowicz, "CoSS: Co-optimizing Sensor and Sampling Rate for Data-Efficient AI in Human Activity Recognition"
Hasib-Al Rashid, Tinoosh Mohsenin, "TinyM$^2$Net-V3: Memory-Aware Compressed Multimodal Deep Neural Networks for Sustainable Edge Deployment"
Accepted Poster Papers
Seoungyoon Kang, Yunji Jung, Hyunjung Shim, "Local Expert Diffusion Models for Efficient Training in Denoising Diffusion Probabilistic Models"
Yuhan Wang, Zijian Lei, Liang Lan, "Effective and Sparse Count-Sketch via k-means clustering"
Chi Zhang, Ang Li, Scott Allen Mueller, Rumen Iliev, "Causal AI Framework for Unit Selection in Optimizing Electric Vehicle Procurement"
Keying Zhang, "MADA: Mask Aware Domain Adaptation for Open-set Semantic Segmentation"
Hongyong Han, Wei Wang, Gaowei Zhang, Mingjie Li, Yi Wang, "CR-Cross: A Novel Approach for Cross Domain Coral Recognitions with Reject Options"
Workshop Format and Schedule
The Sustainable AI workshop is designed as a comprehensive full-day
event that aims to foster knowledge sharing and collaboration among
participants. Our program is carefully curated to provide a platform where
experts from both academia and industry can contribute their insights. We plan
to invite two distinguished keynote speakers who are renowned authorities in
the field.
To encourage meaningful
discussions, we will organize a panel discussion where participants can engage
in an exchange of ideas on critical topics related to sustainable AI.
Additionally, we will consider all submissions for both oral and poster
presentations. The format of presentation will be determined based on the level
of interest and the quality of the submissions.
Recognizing outstanding
contributions, we are actively seeking sponsorships to establish prestigious
awards for the best paper and best poster. Selected recipients of these awards
will have the opportunity to submit their work to a special issue on
Sustainable AI in collaboration with our partnering journal, IEEE
Transactions on Emerging Topics in Computational Intelligence (TETCI), as
well as the World Scientific Annual Review of AI. This provides a
remarkable opportunity for their research to gain further recognition and reach
a wider audience.
Deadlines and Sumission Site
Workshop Submissions Due: Friday, November 24, 2023
Notifications Sent to
Authors (by organizers): Monday, December 15, 2023
Workshop Programme