The power of AI: balancing ethics and harm for the environmental justice field

Agni Athreya, Louise Palmer
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Abstract

Artificial intelligence, after the boom of generative AI, is beginning to shape environmental decision-making, at the same moment that environmental justice (EJ) communities face intensifying ecological harm, federal disinvestment, and data erasure. This paper examines the dual tensions AI presents for the EJ field: its potential as a tool for democratizing data access and amplifying community knowledge, and its reproduction of the very hierarchies EJ seeks to dismantle. We document harms across several domains, including the environmental racism embedded in data center siting and energy demand, the extension of fossil fuel industry lifespans, data bias and digital colonialism in AI training, access and literacy inequities, data privacy risks, technological hallucination, and technological solutionism. Drawing on thirty years of community-centered data practice at an EJ nonprofit, we propose an alternative paradigm grounded in the Community Advisory Board model, data democratization, community co-creation, and ethical data governance. This includes community-governed data trusts, accessible data infrastructure, and AI tools designed to build rather than replace community capacity. EJ communities must not only hold AI accountable for its harms but also ask the question of how the technology’s capabilities can serve justice rather than just capital interest.

人工智能的力量:平衡环境正义领域的伦理与危害
在生成式人工智能蓬勃发展之后,人工智能开始影响环境决策,与此同时,环境正义(EJ)社区面临着日益严重的生态危害、联邦撤资和数据删除。本文考察了人工智能为经济学领域呈现的双重紧张关系:它作为数据访问民主化和扩大社区知识的工具的潜力,以及它对经济学试图拆除的等级制度的再现。我们记录了几个领域的危害,包括数据中心选址和能源需求中嵌入的环境种族主义、化石燃料行业寿命的延长、人工智能培训中的数据偏见和数字殖民主义、访问和读写不平等、数据隐私风险、技术幻觉和技术解决方案主义。根据EJ非营利组织三十年来以社区为中心的数据实践,我们提出了一种基于社区咨询委员会模型、数据民主化、社区共同创造和道德数据治理的替代范例。这包括社区管理的数据信任、可访问的数据基础设施以及旨在建立而不是取代社区能力的人工智能工具。EJ社区不仅要让人工智能对其危害负责,还要提出这样一个问题:这项技术的能力如何服务于正义,而不仅仅是资本利益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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