ARTIFICIAL INTELLIGENCE IN ENVIRONMENTAL GOVERNANCE IN THE LEGAL AMAZON: A SOCIOTECHNICAL FRAMEWORK AND SAFEGUARDS FOR RESPONSIBLE USE

Abstract

The incorporation of artificial intelligence systems into the environmental governance of the Brazilian Legal Amazon has advanced at a pace that outstrips the production of conceptual frameworks capable of guiding their responsible use, creating a gap between technical capability and institutional accountability that this article seeks to address. The objective was to propose a layered sociotechnical framework and a set of operational safeguards for the use of AI in this domain, organizing existing applications into an analytical typology and mapping the risks associated with each area of use. To this end, an integrative literature review was conducted using Scopus, Web of Science, SciELO, and Google Scholar databases, covering the period from 2015 to 2026, with thematic synthesis organized around four conceptual axes: Data, Models, Decision, and Governance & Accountability. The results comprise a framework structured around these four interdependent layers, a summary matrix correlating applications, risks, safeguards, and monitoring indicators, and an evidence chain representing the flow from automated detection to the corresponding administrative act. It is concluded that the potential of AI in Amazonian environmental governance is real, but strictly contingent on the existence of audit trails, contestation mechanisms, and structured institutional accountability — without which the adoption of these technologies tends to increase the opacity of decision-making processes without producing effective gains in environmental protection.