Sustainable AI: AI for sustainability and the sustainability of AI

Abstract

While there is a growing effort towards AI for Sustainability (e.g. towards the sustainable development goals) it is time to move beyond that and to address the sustainability of developing and using AI systems. In this paper I propose a definition of Sustainable AI; Sustainable AI is a movement to foster change in the entire lifecycle of AI products (i.e. idea generation, training, re-tuning, implementation, governance) towards greater ecological integrity and social justice. As such, Sustainable AI is focused on more than AI applications; rather, it addresses the whole sociotechnical system of AI. I have suggested here that Sustainable AI is not about how to sustain the development of AI per say but it is about how to develop AI that is compatible with sustaining environmental resources for current and future generations; economic models for societies; and societal values that are fundamental to a given society. I have articulated that the phrase Sustainable AI be understood as having two branches; AI for sustainability and sustainability of AI (e.g. reduction of carbon emissions and computing power). I propose that Sustainable AI take sustainable development at the core of its definition with three accompanying tensions between AI innovation and equitable resource distribution; inter and intra-generational justice; and, between environment, society, and economy. This paper is not meant to engage with each of the three pillars of sustainability (i.e. social, economic, environment), and as such the pillars of sustainable AI. Rather, this paper is meant to inspire the reader, the policy maker, the AI ethicist, the AI developer to connect with the environment—to remember that there are environmental costs to AI. Further, to direct funding towards sustainable methods of AI.

AI ethics: A framework for measuring embodied carbon in AI systems

“…One aspect of AI ethics that has not been as strongly assessed, however, is its overall climate impact [2,3], i.e., its impact on the planet and the role that it has in contributing to climate change. The significant majority of the discussions focus rather on its positive effects on measuring or improving humanities response to climate change [4,5].…”

Engaging with Artificial Intelligence (AI) with a Bottom-Up Approach for the Purpose of Sustainability: Victorian Farmers Market Association, Melbourne Australia

“…More scrutiny about the environmental impacts of the technology is still required to ensure they are appropriately accounted for in sustainability terms. While research of AI for sustainability (towards the UN's sustainable development goals) is the subject of numerous articles, questions about the sustainability of AI (through the reduction of its carbon emissions and computing power) are still hidden in the development process [95].…”

Artificial intelligence in research and development for sustainability: the centrality of explicability and research data management

“…Thereby, AI -in its simplest sense, defined as "ability of computers or other machines in performing activities that require human intelligence" [1] -has become a transformative power across a wide range of industrial, social, and intellectual contexts [11]. It offers vast opportunities for innovations [4,5], engenders new solutions to complex problems [39], and enables to address major societal issues, including sustainable development, and environmental sustainability [33,41,42]. Particularly, the data-intensive research and applications benefit from AI due to the possibility to process and analyze massive amounts of structured and unstructured (big) data [10,23].…”

“…Sustainability features a central ethical principle and objective related to the development and deployment of AI [14,21,41]. Generally, the increasing pervasiveness and impact AI on the individual, economic, and societal level have sparked the debate of ethical principles guiding AI development and use [8,13,14,17,21,29,31].…”