Data Ecofeminism

2025-02-16

AI Summary

The high energy consumption of generative artificial intelligence (GenAI) exacerbates climate change, water scarcity, and ecological injustice. Method: Drawing on data ecofeminism—a theoretical synthesis of ecofeminism and data feminism—the study develops a critical ethical framework for AI governance, articulating seven foundational principles through an interdisciplinary analysis grounded in critical technology studies, feminist epistemology, environmental justice, and the political economy of AI. Rather than focusing on algorithmic implementation, it interrogates underlying power structures and epistemic assumptions. Contribution/Results: The framework advances anti-growth, decolonial, and multispecies-oriented technological praxis; provides actionable value-embedding strategies for policymakers, developers, and community practitioners; and advocates for alternative AI infrastructures centered on respect for human and non-human life and planetary boundaries. This work reorients AI development from techno-hegemony toward life-centeredness, social justice, and ecological sustainability.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Humans and AI: Other Foundations of Human Computation & AI
• Machine Learning: Ethics, Bias, and Fairness

Application Category

• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Security and Privacy: Data transparency and provenance

Abstract

Generative Artificial Intelligence (GenAI) is driving significant environmental impacts. The rapid development and deployment of increasingly larger algorithmic models capable of analysing vast amounts of data are contributing to rising carbon emissions, water withdrawal, and waste generation. Generative models often consume substantially more energy than traditional models, with major tech firms increasingly turning to nuclear power to sustain these systems -- an approach that could have profound environmental consequences. This paper introduces seven data ecofeminist principles delineating a pathway for developing technological alternatives of eco-societal transformations within the AI research context. Rooted in data feminism and ecofeminist frameworks, which interrogate about the historical and social construction of epistemologies underlying the hegemonic development of science and technology that disrupt communities and nature, these principles emphasise the integration of social and environmental justice within a critical AI agenda. The paper calls for an urgent reassessment of the GenAI innovation race, advocating for ecofeminist algorithmic and infrastructural projects that prioritise and respect life, the people, and the planet.

Problem

• Environmental impact of Generative AI
• Need for ecofeminist AI principles
• Reassessment of GenAI innovation race

Innovation

• Ecofeminist principles guide AI
• Integrate social-environmental justice
• Reassess Generative AI impacts