Stephen Downes

"It has become essential," write the authors, "to clarify where automation ends and agency begins." This paper (44 page PDF) identifies five essential characteristics of agency: "goal, identity, decision-making, self-regulation, and learning." The authors distinguish between "agentic systems, which complete tasks through externally orchestrated tools and workflows, and agentive systems, whose capabilities arise from internal organization." They then introduce a "GIC (Goal-Identity-Configurator) architecture, which provides concrete proposals for each of the five aspects of artificial agency and resultant capabilities within a single adaptive system. The importance of learning in this context is clear: "a more complete notion of agency... treats learning as continuous and endogenous, taking two complementary forms: learning from real interaction, where the agent updates its parameters θ based on deployment experience, and learning from simulated experience, where the agent generates hypothetical trajectories through its world model f and trains on them without real-world interaction." Experience and Prediction: takes me back to my undergrad days reading Hans Reichenbach.