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The sharply increasing sizes of artificial intelligence (AI) models come with significant energy consumption and environmental footprints, which can disproportionately impact certain (often marginalized) regions and hence create…
The skyrocketing demand for artificial intelligence (AI) has created an enormous appetite for globally deployed power-hungry servers. As a result, the environmental footprint of AI systems has come under increasing scrutiny. More crucially,…
Generative AI is spreading rapidly, creating significant social and economic value while also raising concerns about its high energy use and environmental sustainability. While prior studies have predominantly focused on the…
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…
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…
The rapid growth of artificial intelligence (AI), particularly Large Language Models (LLMs), has raised concerns regarding its global environmental impact that extends beyond greenhouse gas emissions to include consideration of hardware…
In the past ten years, artificial intelligence has encountered such dramatic progress that it is now seen as a tool of choice to solve environmental issues and in the first place greenhouse gas emissions (GHG). At the same time the deep…
Sustainability encompasses three key facets: economic, environmental, and social. However, the nascent discourse that is emerging on sustainable artificial intelligence (AI) has predominantly focused on the environmental sustainability of…
Prominent works in the field of Natural Language Processing have long attempted to create new innovative models by improving upon previous model training approaches, altering model architecture, and developing more in-depth datasets to…
This paper explores the environmental impact of the super-linear growth trends for AI from a holistic perspective, spanning Data, Algorithms, and System Hardware. We characterize the carbon footprint of AI computing by examining the model…
The rapid adoption of AI in Earth system science promises unprecedented speed and fidelity in the generation of climate information. However, this technological prowess rests on a fragile and unequal foundation: the current trajectory of AI…
The past decade has seen a massive rise in the popularity of AI systems, mainly owing to the developments in Gen AI, which has revolutionized numerous industries and applications. However, this progress comes at a considerable cost to the…
Due to increased computing use, data centers consume and emit a lot of energy and carbon. These contributions are expected to rise as big data analytics, digitization, and large AI models grow and become major components of daily working…
Artificial Intelligence, machine learning (AI/ML) has allowed exploring solutions for a variety of environmental and climate questions ranging from natural disasters, greenhouse gas emission, monitoring biodiversity, agriculture, to weather…
Philosophers of technology have recently started paying more attention to the environmental impacts of AI, in particular of large language models (LLMs) and generative AI (genAI) applications. Meanwhile, few developers of AI give concrete…
Artificial intelligence (AI) systems impose substantial and growing environmental costs, yet transparency about these impacts has declined even as their deployment has accelerated. This paper makes three contributions. First, we collate…
Artificial intelligence (AI) is currently spearheaded by machine learning (ML) methods such as deep learning which have accelerated progress on many tasks thought to be out of reach of AI. These recent ML methods are often compute hungry,…
Artificial Intelligence (AI) is changing the world, but its impacts on the environment and human well-being remain uncertain. We conducted a systematic literature review of 1,291 studies selected from 6,655 records, identifying the main…
Artificial intelligence (AI) has made remarkable progress in recent years, yet its rapid expansion brings overlooked environmental and ethical challenges. This review explores four critical areas where AI's impact extends beyond…
The rapid advancement of Artificial Intelligence (AI) has created unprecedented demands for computational power, yet methods for evaluating the performance, efficiency, and environmental impact of deployed models remain fragmented. Current…