Position: Knowing Isn’t Understanding: Re-grounding Generative Proactivity with Epistemic and Behavioral Insight
Kirandeep Kaur, Xingda Lyu, Chirag Shah
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.
BibTeX
@inproceedings{icml2026_positionknowingi,
title = {Position: Knowing Isn’t Understanding: Re-grounding Generative Proactivity with Epistemic and Behavioral Insight},
author = {Kirandeep Kaur and Xingda Lyu and Chirag Shah},
booktitle = {ICML 2026},
year = {2026}
}