Connectionists: [CFP] Green artificial intelligence at IJCNN 2024

[Óscar Fontenla Romero]

[Apologies if you receive multiple copies of this CFP]


Call for papers: Special Session on "Green artificial intelligence: towards a more sustainable future" at IJCNN 2024

The session will be part of the program of the “IEEE World Congress on Computational Intelligence WCCI-2024”, which will be held in Yokohama, Japan, June 30 - July 5, 2024

Green artificial intelligence: towards a more sustainable future. Organized by: Veronica Bolon-Canedo, Amparo Alonso-Betanzos, Óscar Fontenla-Romero (CITIC - University of A Coruña, Spain), Alicia Troncos Lora (Universidad Pablo de Olavide, Spain), José C. Riquelme (University of Seville, Spain).


In recent years, we have witnessed remarkable advances in the field of Artificial Intelligence (AI), primarily driven by the advent of deep learning models. However, it is irrefutable that deep learning comes with a substantial carbon footprint, as underscored by a 2019 paper which asserted that training a language model could release nearly five times the lifetime emissions of an average car.

The term "Green AI" denotes AI research that prioritizes environmental sustainability and inclusivity. This paradigm shift extends beyond the mere pursuit of groundbreaking results without inflating computational demands; it also seeks to empower every researcher, regardless of their resources, to conduct high-quality research using a regular laptop. Conventional AI research, often termed "Red AI," predominantly focuses on achieving cutting-edge results at the expense of substantial computational power, relying on huge amounts of training data and extensive experimentation.


Emerging from this landscape are more efficient machine learning approaches, particularly within the field of deep learning, which have recently garnered attention in the research community. However, the prevailing issue is that these endeavors frequently lack an explicit environmental motivation. Therefore, there exists an important need to encourage the AI community to acknowledge and value the work of researchers who diverge from the established path, emphasizing efficiency alongside, or even above, accuracy.

Topics such as low-resolution algorithms, edge computing, efficient platforms, and, more broadly, scalable and sustainable algorithms and their applications, all contribute to a comprehensive vision of Green AI. Embracing these topics not only underscores the

commitment to eco-conscious AI but also lays the foundation for a future where AI innovation aligns with environmental stewardship.

In this special session, we invite papers on both practical and theoretical issues about developing new artificial intelligence and machine learning methods that are sustainable and green, as well as review papers with the state-of-the-art techniques and the open challenges encountered in this field. In particular, topics of interest include, but are not limited to:


  *   Developing energy-efficient algorithms for training and/or inference.

  *   Investigating sustainable data management and storage techniques.

  *   Exploring the use of renewable energy sources for machine learning.

  *   Examining the ethical and social implications of green machine learning.

  *   Investigating methods for reducing the carbon footprint of machine learning systems.

  *   Studying the impact of green machine learning on various industries and applications


Information on paper submission can be found here:

https://2024.ieeewcci.org/submission


All accepted papers will be included in the WCCI-2024 proceedings, published on the IEEE Xplore Digital Library.


Paper submission deadline is January 15, 2024.


Best regards.

Oscar Fontenla-Romero
LIDIA lab
Computer Science Department
University of A Coruña
Email: oscar.fontenla at udc.es<mailto:%20oscar.fontenla at udc.es>
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