Knowing Isn't Understanding: Re-grounding Generative Proactivity with Epistemic and Behavioral Insight

TL;DR

Drawing on the philosophy of ignorance and research on proactive behavior, it is argued that these theories offer critical guidance for designing agents that can engage responsibly and foster meaningful partnerships.

Abstract

Generative AI agents equate understanding with resolving explicit queries, an assumption that confines interaction to what users can articulate. This assumption breaks down when users themselves lack awareness of what is missing, risky, or worth considering. In such conditions, proactivity is not merely an efficiency enhancement, but an epistemic necessity. We refer to this condition as epistemic incompleteness: where progress depends on engaging with unknown unknowns for effective partnership. Existing approaches to proactivity remain narrowly anticipatory, extrapolating from past behavior and presuming that goals are already well defined, thereby failing to support users meaningfully. However, surfacing possibilities beyond a user's current awareness is not inherently beneficial. Unconstrained proactive interventions can misdirect attention, overwhelm users, or introduce harm. Proactive agents, therefore, require behavioral grounding: principled constraints on when, how, and to what extent an agent should intervene. We advance the position that generative proactivity must be grounded both epistemically and behaviorally. Drawing on the philosophy of ignorance and research on proactive behavior, we argue that these theories offer critical guidance for designing agents that can engage responsibly and foster meaningful partnerships.

Figures (6)

• Figure 1: Epistemic proactivity under uncertainty. A proactive agent surfaces gaps within a user’s epistemic landscape, reorganizing known and partially known regions (KK, KU, UK) and incrementally engaging the epistemic frontier under uncertainty.
• Figure 2: Proactivity regimes organized by the variable governing initiative: prediction in anticipatory systems, regulation in mixed-initiative systems, and commitment in autonomous systems.
• Figure 3: Inverted doughnut model of proactive behavior.
• Figure 4: Epistemic--behavioral coupling space.
• Figure 5: Epistemic partnership through proactive gap surfacing. Illustrative example of how proactive agents can support inquiry by surfacing latent epistemic gaps rather than executing premature action. Known facts do not by themselves determine the governing relationship; progress emerges when missing relations are identified and articulated through interaction. Proactive surfacing of such gaps expands the inquiry space, generating newly articulated unknowns and enabling joint discovery.