generoidun
Generoidun is a coined term used in speculative AI discourse to describe a class of generative systems designed to construct, rank, and evaluate alternative futures for a defined set of agents within a simulated environment. The concept is intentionally abstract, and there is no single canonical implementation; instead, it serves as a generative framework for exploring how combinations of modeling, constraints, and feedback can influence imagined outcomes.
Core components typically include a generative module that samples system states and agent behaviors, a constraint
Origin and usage: The term arose in theoretical discussions surrounding AI alignment and scenario analysis in
Applications: Generoidun-inspired approaches support scenario planning for policy, risk assessment for autonomous systems, and educational tools
Critique: Critics note that generoidun can produce unwieldy or misleading results if not carefully bounded, and