Abstract
As environmental systems cross critical thresholds, organizational and governance responses are increasingly shaped by AI tools and automated decision-support systems. From biodiversity modeling to sustainability scoring, these systems promise objectivity, but often reproduce narrow optimization logics that obscure deeper ecological interdependencies. This paper draws on empirical and conceptual work in human-AI teaming and behavioral design to ask: how do humans make sense with machines under conditions of planetary uncertainty? Drawing on insights from a number of ongoing projects, we examine how emerging technologies quietly shape what is recognized, prioritized, and acted upon in environmental governance. The study highlights how technical infrastructures can unintentionally reinforce a kind of “carbon tunnel vision,” diverting attention from slower, less measurable threats such as soil degradation, freshwater collapse, or biodiversity loss. These systems, while useful, risk encoding a narrow worldview at a time when we urgently need integrative thinking. Rather than proposing technical fixes, the paper makes a case for more reflexive forms of collaboration between humans, institutions, and computational systems that foreground ecological context, political responsibility, and the diversity of knowledge needed to navigate environmental complexity. The aim is not to reject AI, but to better align its role with the broader demands of ecological and democratic responsibilit and to help reframe sustainability governance as an ongoing process of situated judgment, rather than an optimization problem to be solved.
Presenters
Dirk Van RooyProfessor, Antwerp Centre for Responsible AI (ACRAI), University of Antwerp, Belgium
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
KEYWORDS
Environmental Governance, Ecological Complexity, Human-Machine Collaboration, Sustainability Framing, Epistemic Diversity
