Related papers: A Green(er) World for A.I
AI research is increasingly moving toward complex problem solving, where models are optimized not only for pattern recognition but for multi-step reasoning. Historically, computing's global energy footprint has been stabilized by sustained…
The latest advancements in machine learning, specifically in foundation models, are revolutionizing the frontiers of existing software engineering (SE) processes. This is a bi-directional phenomona, where 1) software systems are now…
As global challenges of population growth, climate change, and resource scarcity intensify, the agricultural landscape is at a critical juncture. Sustainable vertical farming emerges as a transformative solution to address these challenges…
The accelerating development and deployment of AI technologies depend on the continued ability to scale their infrastructure. This has implied increasing amounts of monetary investment and natural resources. Frontier AI applications have…
Growing awareness of the environmental impact of digital technologies has led to several isolated initiatives to promote sustainable practices. However, despite these efforts, the environmental footprint of generative AI, particularly in…
The rise of Artificial Intelligence (AI) will bring with it an ever-increasing willingness to cede decision-making to machines. But rather than just giving machines the power to make decisions that affect us, we need ways to work…
The recent developments of artificial intelligence increase its capability for the creation of arts in both largely autonomous and collaborative contexts. In both contexts, Ai aims to imitate, combine, and extend existing artistic styles,…
Across the Artificial Intelligence (AI) lifecycle - from hardware to development, deployment, and reuse - burdens span energy, carbon, water, and embodied impacts. Cloud provider tools improve transparency but remain heterogeneous and often…
Background: The construction, evolution and usage of complex artificial intelligence (AI) models demand expensive computational resources. While currently available high-performance computing environments support well this complexity, the…
Organizations increasingly need to reassess their supply chain strategies in the rapidly modernizing world towards sustainability. This is particularly true in the United States, where supply chains are very extensive and consume a large…
The increasing attention on Artificial Intelligence (AI) regulation has led to the definition of a set of ethical principles grouped into the Sustainable AI framework. In this article, we identify Continual Learning, an active area of AI…
As the possibilities for Artificial Intelligence (AI) have grown, so have concerns regarding its impacts on society and the environment. However, these issues are often raised separately; i.e. carbon footprint analyses of AI models…
Artificial intelligence (AI) is a key enabler of innovation against climate change. In this study, we investigate the intersection of AI and climate adaptation and mitigation technologies through patent analyses of a novel dataset of…
Recent progress in artificial intelligence (AI) using deep learning techniques has triggered its wide-scale use across a broad range of applications. These systems can already perform tasks such as natural language processing of voice and…
The emergence of artificial intelligence (AI) and its progressively wider impact on many sectors across the society requires an assessment of its effect on sustainable development. Here we analyze published evidence of positive or negative…
The rapid expansion of artificial intelligence has significantly increased the electricity, water, and carbon demands of modern data centers, raising sustainability concerns. This study evaluates the environmental footprint of AI server…
The technology industry promotes artificial intelligence (AI) as a key enabler to solve a vast number of problems, including the environmental crisis. However, when looking at the emissions of datacenters from worldwide service providers,…
Large Language Models (LLMs) have transformed numerous domains by providing advanced capabilities in natural language understanding, generation, and reasoning. Despite their groundbreaking applications across industries such as research,…
Reduced environmental effect, lower operating costs, and a stable and sustainable energy supply for current and future generations are the main reasons why power optimization is important. Power optimization makes ensuring that energy is…
Global food systems must deliver nutritious, sustainable foods while sharply reducing environmental impact. Yet, food innovation remains slow, empirical, and fragmented. Artificial intelligence (AI) offers a transformative path to link…